System, management platform, and program

Abstract

Provided is a system comprising a plurality of distributed platforms that cooperatively process one simulation process including a plurality of tasks, and a management platform that manages the plurality of distributed platforms. Each distributed platform of the plurality of distributed platforms includes: an execution unit that includes a RAN control function that executes an AI process (RAN Intelligent Controller (RIC)) or the like to control the function of a RAN and a task processing function that processes a task included in one simulation process; and an acquisition unit that acquires use state information indicating the usage state of the execution unit. The management platform allocates a task to each distributed platform, receives usage status information from each distributed platform, determines whether or not the usage status of the execution unit of each distributed platform is in a tight situation on the basis of the usage status information of each distributed platform, and migrates a migratable task of one distributed platform, of which the usage status of the execution unit is determined to be in the tight situation, from the one distributed platform to some other distributed platform of which the usage status of the execution unit is determined to be not in a tight situation.

Description

Systems, management infrastructure, and programs

[0001] The present invention relates to a system, a management platform, and a program.

[0002] Patent Document 1 describes a technology for more efficiently using computing resources by appropriately scheduling the use of computing resources in multiple regions. Patent Document 2 describes a technology for automatically improving the response time of each user terminal and enabling appropriate allocation of virtual machines to physical machines. [Prior Art Literature] [Patent Documents] [Patent Document 1] International Publication No. 2019 / 078331 [Patent Document 2] Japanese Patent Application Laid-Open No. 2013-178682

[0003] In the past, large-scale spatial simulations were often geographically divided to reduce the processing load. This is effective for achieving low latency even in distributed computing environments. However, if the geographic division is static, it is not possible to change the resources used for simulation processing in response to increased simulation load in a specific region. As a result, there is a risk that real-time simulations will reach their limits.

[0004] In the system according to this embodiment, for example, by running the functions of a RAN (Radio Access Network) on a high-performance GPU (Graphics Processing Unit) server rather than on a general-purpose server, the surplus computing resources can be utilized for AI (Artificial Intelligence) processing. Types of AI processing include AI processing related to RAN control (sometimes referred to as RAN control AI processing) and AI processing not related to RAN control (sometimes referred to as non-RAN control AI processing).

[0005] An example of RAN control AI processing is RIC (RAN Intelligent Controller). RIC is a technology that uses AI to optimize RAN radio resources and automate RAN operations. RIC includes Non-RT RIC and Near-RT RIC (Near-Real Time RIC). Non-RT RIC is sometimes called Centralized RIC. Non-RT RIC is located inside SMO (Service Management and Orchestration), which manages and orchestrates the RAN. Non-RT RIC generates and notifies policies related to RAN control and sends information to Near-RT RIC. For example, the Non-RT RIC performs machine learning using data collected from the RAN to generate a trained model for RAN control and transmits it to the Near-RT RIC. The Near-RT RIC is sometimes called a Distributed RIC. Compared to the Non-RT RIC, the Near-RT RIC is located closer to the RAN nodes (RU (Radio Unit), DU (Distributed Unit), CU (Central Unit)) and controls the RAN nodes, resources, etc. The Near-RT RIC performs processing with higher real-time performance than the Non-RT RIC. The Near-RT RIC performs inference processing related to RAN control using, for example, a trained model acquired from the Non-RT RIC. RAN control AI processing is not limited to the RIC.

[0006] Non-RAN control AI processing may correspond to a so-called MEC (Multi-access Edge Computing) application. Examples of non-RAN control AI processing include digital twin AI execution processing that reproduces the environment of a real space in a virtual space based on data collected from the real space, monitoring AI execution processing that determines the situation within the imaging range of an input captured image, and response AI execution processing that outputs a response to an input user inquiry, but are not limited to these.

[0007] In the system according to this embodiment, for example, a simulation space is divided into small pieces in advance so that one distributed data center processes multiple simulation containers, and a mechanism is adopted in which simulation containers in a distributed data center with a high processing load are live-migrated from that distributed data center to a distributed data center located nearby and with a low processing load. This allows the number of simulation containers processed by a distributed data center to be adjusted, thereby realizing load balancing of spatial simulations using multiple distributed data centers.

[0008] According to one embodiment of the present invention, there is provided a system. The system may include a plurality of distributed platforms that cooperatively process a single simulation process including a plurality of tasks. The system may include a management platform that manages the plurality of distributed platforms. Each of the plurality of distributed platforms may include an execution unit that includes a RAN control function that controls a RAN (Radio Access Network) function and a task processing function that processes tasks included in the single simulation process, an acquisition unit that acquires usage status information indicating a usage status of the execution unit, and a transmission unit that transmits the usage status information. The management infrastructure may include a task allocation unit that assigns the tasks to each of the distributed infrastructures, a receiving unit that receives the usage status information from each of the distributed infrastructures, a determination unit that determines whether the usage status of the execution unit of each of the distributed infrastructures is under pressure or not based on the usage status information of each of the distributed infrastructures, and a task migration unit that, when the determination unit determines that the usage status of the execution unit of one of the plurality of distributed infrastructures is under pressure, migrates migration target tasks, which are at least some of the tasks assigned to the one distributed infrastructure, from the one distributed infrastructure to another of the plurality of distributed infrastructures for which the determination unit has determined that the usage status of the execution unit is not under pressure.

[0009] In the system, the task migration unit may migrate the task to be migrated from one distributed platform to the other distributed platform by live migrating a virtual machine used by the one distributed platform to execute the task to be migrated from the one distributed platform to the other distributed platform.

[0010] In any of the above systems, the multiple distributed platforms may cooperatively process the one simulation process, which is a spatial simulation process that generates a virtual space corresponding to a real space including multiple partitions, and each of the multiple segments included in the virtual space may correspond to each of the multiple partitions, the task allocation unit may assign the task of generating at least two of the multiple segments to each of the distributed platforms based on the location of each of the distributed platforms and the location of each of the partitions, and the task migration unit may migrate the migration target task, which is the task of generating at least one segment of the tasks assigned to the one distributed platform, from the one distributed platform to the other distributed platform.

[0011] In any of the above systems, the management infrastructure may further have a selection unit that, when the determination unit determines that the usage status of the execution unit of the one distributed infrastructure is under pressure, preferentially selects, as the migration target task, from among the tasks assigned to the one distributed infrastructure, a task that generates at least one segment adjacent to a segment that is the generation target of the task assigned to the other distributed infrastructure, and the task migration unit may migrate the migration target task selected by the selection unit from the one distributed infrastructure to the other distributed infrastructure.

[0012] In any of the above systems, the task allocation unit may assign the tasks to each distributed infrastructure based further on the coverage area of ​​the RAN that is the control target of each distributed infrastructure, so that at least two partitions corresponding to the at least two segments that are the targets for generating the tasks to be assigned to each distributed infrastructure more closely match the coverage area of ​​the RAN that is the control target of each distributed infrastructure.

[0013] In any of the above systems, the management infrastructure may further have a selection unit that, when the determination unit determines that the usage status of the execution unit of the one distributed infrastructure is in a constrained state, preferentially selects, as the migration target task, a task that generates at least one segment corresponding to the overlapping area among the tasks assigned to the one distributed infrastructure when the coverage area of ​​the RAN that is the control target of the one distributed infrastructure includes an overlapping area that overlaps with the coverage area of ​​the RAN that is the control target of the other distributed infrastructure, and the task migration unit may migrate the migration target task selected by the selection unit from the one distributed infrastructure to the other distributed infrastructure.

[0014] In any of the above systems, the multiple distributed infrastructures may cooperatively process the spatial simulation process that simulates the communication environment of the RAN that is the control target of each of the distributed infrastructures, and the RAN control function of each of the distributed infrastructures may control the functions of the RAN based on the task processing results obtained by the task processing function processing the task.

[0015] In any of the above systems, the management infrastructure may further have a selection unit that, when the determination unit determines that the usage status of the execution unit of the one distributed infrastructure is in a constrained state, and if there are multiple other distributed infrastructures, preferentially selects, as the destination of the task to be migrated, one of the multiple other distributed infrastructures that is located at a shorter distance from the location of the one distributed infrastructure, and the task migration unit may migrate the task to be migrated from the one distributed infrastructure to the other distributed infrastructure selected by the selection unit.

[0016] In any of the above systems, the management infrastructure may further have a selection unit that, when the determination unit determines that the usage status of the execution unit of the one distributed infrastructure is under pressure, and if there are multiple other distributed infrastructures, preferentially selects one of the multiple other distributed infrastructures that has a greater amount of free resources in its execution unit as the destination for the migration target task, and the task migration unit may migrate the migration target task from the one distributed infrastructure to the other distributed infrastructure selected by the selection unit.

[0017] In any of the above systems, the management infrastructure may further have an offload unit that, when the determination unit determines that the usage status of the execution unit of one of the distributed infrastructures is under pressure, offloads at least a portion of the processing load of the RAN control function of the one of the distributed infrastructures from the one of the distributed infrastructures to another of the multiple distributed infrastructures for which the determination unit determines that the usage status of the execution unit is not under pressure.

[0018] According to one embodiment of the present invention, there is provided a management infrastructure that manages multiple distributed infrastructures that cooperatively process a single simulation process including multiple tasks, each of the multiple distributed infrastructures having an execution unit including a RAN control function that controls RAN functions and a task processing function that processes tasks included in the single simulation process, an acquisition unit that acquires usage status information that indicates usage status of the execution unit, and a transmission unit that transmits the usage status information. The management infrastructure may include a task allocation unit that assigns the tasks to each of the distributed infrastructures. The management infrastructure may include a receiving unit that receives the usage status information from each of the distributed infrastructures. The management infrastructure may include a determination unit that determines whether the usage status of the execution unit of each of the distributed infrastructures is in a constrained state or not, based on the usage status information of each of the distributed infrastructures. The management infrastructure may include a task migration unit that, when the determination unit determines that the usage status of the execution unit of one of the plurality of distributed infrastructures is under pressure, migrates tasks to be migrated, which are at least some of the tasks assigned to the one distributed infrastructure, from the one distributed infrastructure to another distributed infrastructure of the plurality of distributed infrastructures for which the determination unit determines that the usage status of the execution unit is not under pressure.

[0019] According to one embodiment of the present invention, there is provided a program that, when executed by a computer, causes the computer to function as the management infrastructure.

[0020] The above summary of the invention does not list all of the necessary features of the present invention, and subcombinations of these features may also constitute inventions.

[0021] FIG. 1 is a schematic diagram illustrating an example of a system 10. FIG. 2 is an explanatory diagram illustrating an example of task allocation. FIG. 3 is an explanatory diagram illustrating an example of a process flow for migrating a task. FIG. 4 is an explanatory diagram illustrating an example of live migration. FIG. 5 is an explanatory diagram illustrating another example of a process flow for migrating a task. FIG. 6 is an explanatory diagram illustrating another example of live migration. FIG. 7 is an explanatory diagram illustrating another example of a process flow for migrating a task. FIG. 8 is an explanatory diagram illustrating another example of a process flow for migrating a task. FIG. 9 is an explanatory diagram illustrating another example of a process flow for migrating a task. FIG. 10 is an explanatory diagram illustrating an example of a functional configuration of a management infrastructure 100. FIG. 11 is an explanatory diagram illustrating an example of a functional configuration of a distribution infrastructure 200. FIG. 12 is an explanatory diagram illustrating an example of a process flow for the system 10. FIG. 13 is an explanatory diagram illustrating another example of a process flow for the system 10. FIG. 14 is an explanatory diagram illustrating an example of a hardware configuration of a computer 1200 that functions as the management infrastructure 100 or the distribution infrastructure 200.

[0022] The present invention will be described below through embodiments of the invention, but the following embodiments do not limit the scope of the invention as claimed. Furthermore, not all of the combinations of features described in the embodiments are necessarily essential to the solution of the invention.

[0023] 1 schematically illustrates an example of a system 10. The system 10 includes a distributed infrastructure 200. The system 10 may include multiple distributed infrastructures 200. The system 10 may include a management infrastructure 100 that manages the multiple distributed infrastructures 200. In the system 10 according to this embodiment, for example, the management infrastructure 100 and the multiple distributed infrastructures 200 may cooperate to control the RAN 300 and perform AI processing.

[0024] The RAN 300 may be a virtualized vRAN (Virtual RAN), and the system 10 may control the vRAN. The RAN 300 may be a physical RAN, and the system 10 may control the physical RAN. In this embodiment, a case where the RAN 300 is a vRAN will be mainly described as an example.

[0025] The AI ​​processing performed by the system 10 may include RAN-controlled AI processing (sometimes referred to as RAN_AI). The AI ​​processing performed by the system 10 may include non-RAN-controlled AI processing (sometimes referred to as non-RAN_AI).

[0026] The distributed infrastructure 200 may be a data center located in various locations. The distributed infrastructure 200 may be configured with multiple devices. The distributed infrastructure 200 may be realized on a virtualization platform made up of multiple devices. The distributed infrastructure 200 may also be realized by a single device. In other words, the distributed infrastructure 200 may be a distributed device.

[0027] The distribution infrastructure 200 is, for example, located on a core network. The term "on the core network" includes both inside and outside the core network.

[0028] The core network may be compliant with any mobile communication system. For example, the core network may be compliant with a 5G (5th Generation) communication system. The core network may be compliant with a 6G (6th Generation) communication system or later mobile communication system. The core network may be compliant with a 3G (3rd Generation) communication system or an LTE (Long Term Evolution) communication system.

[0029] The management infrastructure 100 may be a data center that manages multiple distributed infrastructures 200. The management infrastructure 100 may be configured with multiple devices. The management infrastructure 100 may be realized on a virtualization infrastructure made up of multiple devices. The management infrastructure 100 may also be realized by a single device. In other words, the management infrastructure 100 may be a management device.

[0030] The management infrastructure 100 is disposed on, for example, a core network. If the management infrastructure 100 is a management device, the management infrastructure 100 may be disposed on the Internet.

[0031] The management infrastructure 100 may be referred to as a Core Brain, and the distributed infrastructure 200 may be referred to as a Regional Brain. While FIG. 1 illustrates an example in which a single-level management infrastructure 100 is arranged below the management infrastructure 100, this is not limiting. The distributed infrastructure 200 may have multiple levels. For example, when a two-level distributed infrastructure 200 is arranged below the management infrastructure 100, the management infrastructure 100 may be referred to as a Core Brain, the distributed infrastructure 200 at the level below that may be referred to as a Regional Brain, and the distributed infrastructure 200 at the level further below that may be referred to as a Sub-Regional Brain.

[0032] The distributed infrastructure 200 may be provided with one or more central processing units (CPUs). The distributed infrastructure 200 may be provided with one or more GPUs. The distributed infrastructure 200 may be provided with multiple super chips, each of which has a CPU and a GPU connected via an interconnect. The interconnect may have memory consistency and may be capable of achieving high bandwidth and low latency. In this way, the distributed infrastructure 200 may have CPU resources and GPU resources as computational resources.

[0033] The multiple distributed infrastructures 200, for example, cooperate to process one simulation process including multiple tasks. The multiple distributed infrastructures 200, for example, cooperate to process a space simulation process that generates a virtual space corresponding to a real space including multiple partitions. Each of the multiple segments included in the virtual space may correspond to each of the multiple partitions. The multiple distributed infrastructures 200, for example, cooperate to process a digital twin simulation process.

[0034] The multiple distributed infrastructures 200, for example, cooperate to process a spatial simulation process that simulates the communication environment of the RAN 300 of each distributed infrastructure. The multiple distributed infrastructures 200, for example, cooperate to process a spatial simulation process that simulates radio wave propagation. The multiple distributed infrastructures 200, for example, cooperate to process a spatial simulation process that simulates traffic conditions. The multiple distributed infrastructures 200, for example, cooperate to process a spatial simulation process that simulates autonomous driving. The multiple distributed infrastructures 200 may also cooperate to process a spatial simulation process that simulates weather conditions.

[0035] The plurality of distributed infrastructures 200, for example, process non-RAN_AIs in a cooperative manner. The plurality of distributed infrastructures 200, for example, process RAN_AIs in a cooperative manner.

[0036] The distributed infrastructure 200 controls, for example, the functions of the RAN 300. The distributed infrastructure 200 controls, for example, the functions of the RAN 300 by executing the RAN_AI. The distributed infrastructure 200 may control the functions of the RAN 300 by executing any other processing.

[0037] The distributed infrastructure 200 controls, for example, the radio base stations 30 that constitute the RAN 300. The distributed infrastructure 200 controls, for example, the radio base stations 30 so as to form a radio communication area using an antenna and provide mobile communication services to communication terminals 50 within the radio communication area.

[0038] The communication terminal 50 is a mobile phone such as a smartphone. The communication terminal 50 may be a tablet terminal, a PC (Personal Computer), or the like. The communication terminal 50 may be a so-called IoT (Internet of Things) device. The communication terminal 50 may include anything that falls under the so-called IoE (Internet of Everything) category.

[0039] Here, an example will be described in which a plurality of distributed infrastructures 200 cooperate to perform a simulation process. Here, a state in which no simulation process task is assigned to the plurality of distributed infrastructures 200 is taken as a starting state.

[0040] The management infrastructure 100 assigns tasks included in the simulation process to each distributed infrastructure 200. Details of the process by which the management infrastructure 100 assigns tasks to each distributed infrastructure 200 will be described later.

[0041] Each distributed infrastructure 200 starts processing the task in response to being assigned a task by the management infrastructure 100. Thereafter, each distributed infrastructure 200 acquires usage status information indicating the usage status of the computational resources of the distributed infrastructure 200. The computational resources of the distributed infrastructure 200 are used, for example, to control the functions of the RAN 300. The computational resources of the distributed infrastructure 200 are used, for example, to process the task. Each distributed infrastructure 200 has, for example, an execution unit including a RAN control function that controls the functions of the RAN 300 and a task processing function that processes the tasks included in the simulation processing. The distributed infrastructure 200 acquires, for example, usage status information indicating the usage status of the execution unit. Each distributed infrastructure 200 transmits the acquired usage status information to the management infrastructure 100.

[0042] The management infrastructure 100 receives usage status information from each distributed infrastructure 200. Based on the usage status information of each distributed infrastructure 200, the management infrastructure 100 determines whether the usage status of the computational resources of each distributed infrastructure 200 is under pressure or not. Here, the explanation will continue assuming that the management infrastructure 100 has determined that the usage status of the computational resources of one distributed infrastructure 200 out of the multiple distributed infrastructures 200 is under pressure.

[0043] In response to determining that the usage of computing resources of one distributed infrastructure 200 is in a tight state, the management infrastructure 100 migrates at least some of the tasks assigned to the one distributed infrastructure 200 to another distributed infrastructure 200 among the multiple distributed infrastructures 200 for which the usage of computing resources has been determined not to be in a tight state. Note that the at least some of the tasks may be referred to as tasks to be migrated.

[0044] The management infrastructure 100 migrates the task to be migrated from one distributed infrastructure 200 to another distributed infrastructure 200, for example, by live-migrating a virtual machine used by one distributed infrastructure 200 to execute the task to be migrated from one distributed infrastructure 200 to another distributed infrastructure 200. The management infrastructure 100 may migrate the task to be migrated from one distributed infrastructure 200 to another distributed infrastructure 200 by any other method.

[0045] Conventionally, simulation processing has been performed using multiple computational resources located in different geographical locations. However, because simulation processing tasks are statically assigned to each of the multiple computational resources, if a computational resource experiences an excessive processing load after the tasks are assigned, the processing of the task on that computational resource cannot be transferred to another computational resource. As a result, the overall processing speed of the simulation processing is reduced due to a decrease in the task processing speed of that computational resource. In particular, when real-time performance is required for the simulation processing, a decrease in the processing speed of the simulation processing can have a significant adverse effect on the simulation processing. For these reasons, when a simulation processing is performed using multiple computational resources located in different geographical locations, it is desirable to dynamically assign simulation processing tasks to each of the multiple computational resources.

[0046] Furthermore, the radio base stations that make up the RAN must meet very high SLAs (Service Level Agreements), and it is necessary to create mechanisms, such as redundancy, to prevent service disruptions. As a result, only a few tenths of the computational resources on the execution platform that runs the RAN service can be used. In other words, there are many unused computational resources. Furthermore, at night, even though the demand for RAN services decreases, computational resources are wasted in an attempt to maintain the same level of service as during the daytime. In other words, the system is designed to accommodate peak demand.

[0047] In contrast, in the system 10 according to the present embodiment, the management infrastructure 100 manages the usage of computational resources of multiple distributed infrastructures 200 that cooperatively execute a simulation process including multiple tasks. When a distributed infrastructure 200 experiences a computing resource shortage, the management infrastructure 100 migrates the migration target task from the distributed infrastructure 200 experiencing a computing resource shortage to another distributed infrastructure 200 experiencing an undemanding computing resource shortage. Therefore, when a simulation process is executed using multiple distributed infrastructures, the system 10 according to the present embodiment can dynamically allocate simulation process tasks. Therefore, when a distributed infrastructure experiences a computing resource shortage, the system 10 according to the present embodiment can suppress a decrease in the overall processing speed of the simulation process when a distributed infrastructure experiences a computing resource shortage. In particular, the system 10 can migrate the migration target task without stopping its execution by live-migrating the virtual machine executing the migration target task from the distributed infrastructure experiencing a computing resource shortage to another distributed infrastructure experiencing an undemanding computing resource shortage. This allows the system 10 according to the present embodiment to further suppress a decrease in the overall processing speed of the simulation process.

[0048] Furthermore, according to the system 10 of this embodiment, each of the multiple distributed infrastructures 200 uses the same computational resources to control the functions of the RAN 300 and process tasks. Therefore, it is possible to allocate computational resources to task processing within a range in which the SLAs of the radio base stations that make up the RAN are maintained, and therefore the system 10 of this embodiment can improve the utilization efficiency of computational resources while maintaining high SLAs of the radio base stations that make up the RAN.

[0049] 2 is an explanatory diagram for explaining an example of task allocation. Here, an example in which the management infrastructure 100 assigns multiple tasks included in the spatial simulation process to distributed infrastructure 1, distributed infrastructure 2, distributed infrastructure 3, and distributed infrastructure 4, which have the same functions as distributed infrastructure 200, will be mainly explained.

[0050] The management infrastructure 100 assigns tasks to each of the distributed infrastructures 1, 2, 3, and 4, based on, for example, the locations of the distributed infrastructures 1, 2, 3, and 4 and the location of each of the multiple partitions in the real space that is the simulation target of the spatial simulation process. The management infrastructure 100 assigns tasks to each of the distributed infrastructures 1, 2, 3, and 4, such that, for example, the task of generating a segment of virtual space corresponding to a partition is preferentially assigned to the distributed infrastructure that is located at a shorter distance from the location of the partition.

[0051] 2, the management infrastructure 100 assigns tasks to each of the distributed infrastructures 1, 2, 3, and 4 as follows: The spatial simulation process is assumed to be a process for generating a virtual space corresponding to the real space including sections 1 to 16.

[0052] The management infrastructure 100 assigns to the distributed infrastructure 1 tasks including the generation of segment 1 corresponding to partition 1, segment 2 corresponding to partition 2, segment 5 corresponding to partition 5, and segment 6 corresponding to partition 6. The management infrastructure 100 assigns to the distributed infrastructure 2 tasks including the generation of segment 3 corresponding to partition 3, segment 4 corresponding to partition 4, segment 7 corresponding to partition 7, and segment 8 corresponding to partition 8. The management infrastructure 100 assigns to the distributed infrastructure 3 tasks including the generation of segment 9 corresponding to partition 9, segment 10 corresponding to partition 10, segment 13 corresponding to partition 13, and segment 14 corresponding to partition 14. The management infrastructure 100 assigns to the distributed infrastructure 4 tasks including the generation of segment 11 corresponding to partition 11, segment 12 corresponding to partition 12, segment 15 corresponding to partition 15, and segment 16 corresponding to partition 16.

[0053] 3 is an explanatory diagram illustrating an example of a process flow for migrating a task. In the example of the process flow for migrating a task shown in Fig. 3, a state in which the management infrastructure 100 assigns tasks to each of the distributed infrastructures 1, 2, 3, and 4 as shown in Fig. 2 is set as a starting state.

[0054] The left diagram of Fig. 3 shows the usage status of the computational resources of distributed infrastructure 1, distributed infrastructure 2, distributed infrastructure 3, and distributed infrastructure 4 in the starting state. As shown in the left diagram of Fig. 3, the usage status of the computational resources of distributed infrastructure 1, distributed infrastructure 2, distributed infrastructure 3, and distributed infrastructure 4 is not in a tight state.

[0055] The central diagram in Figure 3 shows the usage status of the computational resources of distributed infrastructure 1, distributed infrastructure 2, distributed infrastructure 3, and distributed infrastructure 4 after a certain time has elapsed since the start of task processing. As shown in the central diagram in Figure 3, due to an increase in the amount of computational resources of distributed infrastructure 1 used to control the functions of RAN 300, the amount of free computational resources of distributed infrastructure 1 has decreased, resulting in a tight usage status of the computational resources of distributed infrastructure 1. Therefore, in order to alleviate the tight usage status of the computational resources of distributed infrastructure 1, the management infrastructure 100 live migrates a virtual machine for executing the task to be migrated from distributed infrastructure 1. The management infrastructure 100 selects a live migration destination from, for example, distributed infrastructure 2, distributed infrastructure 3, or distributed infrastructure 4, whose computational resource usage status is not tight. Here, the explanation will continue assuming that the management infrastructure 100 selects distributed infrastructure 3 as the live migration destination.

[0056] The right diagram in Figure 3 shows the usage status of computing resources on distributed infrastructure 1, distributed infrastructure 2, distributed infrastructure 3, and distributed infrastructure 4 after live migration. As shown in the right diagram in Figure 3, the amount of free computing resources on distributed infrastructure 1 increased due to live migration, and as a result, the tightness of computing resources on distributed infrastructure 1 was alleviated. Furthermore, even after the migration target task was live migrated, there was still a sufficient amount of free computing resources on distributed infrastructure 3, so the usage status of computing resources on distributed infrastructure 3 was not tight. As described above, live migration appropriately adjusted the usage status of computing resources between multiple distributed infrastructures.

[0057] 4 is an explanatory diagram for explaining an example of live migration, showing details of the live migration shown in FIG.

[0058] For example, to perform live migration, the management infrastructure 100 selects a live migration destination for a virtual machine to execute a task to be migrated from among distributed infrastructure 2, distributed infrastructure 3, and distributed infrastructure 4, which are not under pressure in terms of usage of computational resources. For example, the management infrastructure 100 preferentially selects, as the live migration destination, a distributed infrastructure among distributed infrastructure 2, distributed infrastructure 3, and distributed infrastructure 4 that is located closer to the location of distributed infrastructure 1, whose usage of computational resources is under pressure. Here, the explanation will continue assuming that the management infrastructure 100 selects, as the live migration destination, distributed infrastructure 3, which is located closest to the location of distributed infrastructure 1.

[0059] For example, to perform live migration, the management infrastructure 100 selects a task to be migrated from among the tasks assigned to distributed infrastructure 1, namely, generating segment 1, generating segment 2, generating segment 5, and generating segment 6. For example, the management infrastructure 100 preferentially selects, as the task to be migrated, the generation of a segment adjacent to any of segments 9, 10, 13, and 14, which are the generation targets of a task assigned to distributed infrastructure 3, the destination of live migration, among the tasks assigned to distributed infrastructure 1. Here, the explanation will continue assuming that the management infrastructure 100 selects, as the task to be migrated, the generation of segment 6 from the generation of segment 5 adjacent to segment 9 and the generation of segment 6 adjacent to segment 10.

[0060] The management infrastructure 100 may perform live migration based on the above selection. As shown in Fig. 4, the management infrastructure 100 live migrates the virtual machine for generating segment 6 from distributed infrastructure 1 to distributed infrastructure 3.

[0061] 3 and 4, when the management infrastructure 100 migrates a task to be migrated from a distributed infrastructure where the usage of computational resources is tight to another distributed infrastructure where the usage of computational resources is not tight, and if there are multiple other distributed infrastructures, the management infrastructure 100 preferentially selects, as the migration destination of the task to be migrated, the other distributed infrastructure that is located closer to the location of the first distributed infrastructure. This enables faster data communication required for the migration of the task to be migrated, and therefore the system 10 according to the embodiment shown in FIG. 3 and 4 can further suppress a decrease in the processing speed of the entire simulation process.

[0062] 3 and 4, when a plurality of distributed platforms 200 cooperatively execute a spatial simulation process, when the management platform 100 migrates a task to be migrated from one distributed platform where the usage of computational resources is tight to another distributed platform where the usage of computational resources is not tight, the management platform 100 preferentially selects, as the task to be migrated, the generation of a segment adjacent to one of the segments that is the generation target of a task assigned to the one distributed platform. As a result, the system 10 according to the embodiment shown in FIG. 3 and 4 can migrate the task to be migrated while maintaining the positional relationship between the plurality of segments.

[0063] 5 is an explanatory diagram illustrating another example of the process flow for migrating a task. In the example of the process flow for migrating a task shown in FIG. 5, the start state is a state in which the management infrastructure 100 assigns tasks to each of distributed infrastructures 1, 2, 3, and 4, as shown in FIG. 2. It is assumed that the usage status of the computational resources of distributed infrastructures 1, 2, 3, and 4 in the start state is the same as that shown in the left diagram of FIG. 3. Here, differences from the example of the process flow for migrating a task described above will be mainly described.

[0064] The left diagram in Figure 5 shows the usage status of computational resources on distributed infrastructure 1, distributed infrastructure 2, distributed infrastructure 3, and distributed infrastructure 4 after a certain time has elapsed since the start of task processing. As shown in the left diagram in Figure 5, the usage status of computational resources on distributed infrastructure 1 is tight. Therefore, in order to alleviate the tightness of computational resources on distributed infrastructure 1, management infrastructure 100 live-migrates a virtual machine for executing the task to be migrated from distributed infrastructure 1. Here, the explanation will continue assuming that management infrastructure 100 has selected distributed infrastructure 2 and distributed infrastructure 3, whose usage status of computational resources is not tight, as the live migration destination.

[0065] The right diagram in Figure 5 shows the usage status of computing resources on distributed infrastructure 1, distributed infrastructure 2, distributed infrastructure 3, and distributed infrastructure 4 after live migration. As shown in the right diagram in Figure 5, the amount of free computing resources on distributed infrastructure 1 increased due to live migration, and as a result, the tightness of computing resources on distributed infrastructure 1 was alleviated. Furthermore, even after the migration target task was live migrated, there was still sufficient free computing resources on distributed infrastructure 2 and distributed infrastructure 3, so the usage status of computing resources on distributed infrastructure 2 and distributed infrastructure 3 was not tight. As described above, live migration appropriately adjusted the usage status of computing resources among multiple distributed infrastructures.

[0066] 6 is an explanatory diagram for explaining another example of live migration, showing details of the live migration shown in FIG.

[0067] For example, to perform live migration, the management infrastructure 100 selects a live migration destination for a virtual machine to execute a task to be migrated from among distributed infrastructure 2, distributed infrastructure 3, and distributed infrastructure 4, which are not under pressure in terms of the usage of computational resources. Here, the explanation will be continued assuming that the management infrastructure 100 selects, as the live migration destination, distributed infrastructure 3, which is located at the shortest distance from the location of distributed infrastructure 1, which is under pressure in terms of the usage of computational resources, and distributed infrastructure 2, which is located at the second shortest distance from the location of distributed infrastructure 1.

[0068] For example, to perform live migration, the management infrastructure 100 selects a migration target task from among the generation of segment 1, the generation of segment 2, the generation of segment 5, and the generation of segment 6, which are included in the tasks assigned to distributed infrastructure 1. Here, the explanation will continue assuming that the management infrastructure 100 selects the generation of segment 6 from the generation of segment 5 adjacent to segment 9 and the generation of segment 6 adjacent to segment 10 as a migration target task for which the live migration destination is distributed infrastructure 3, and selects the generation of segment 2 from the generation of segment 2 adjacent to segment 3 and the generation of segment 6 adjacent to segment 7 as a migration target task for which the live migration destination is distributed infrastructure 2.

[0069] The management infrastructure 100 may perform live migration based on the above-described selection. As shown in Fig. 6, the management infrastructure 100 live migrates the virtual machine for generating segment 6 from distributed infrastructure 1 to distributed infrastructure 3, and live migrates the virtual machine for generating segment 2 from distributed infrastructure 1 to distributed infrastructure 2.

[0070] 7 is an explanatory diagram illustrating another example of the process flow for migrating a task. In the example of the process flow for migrating a task shown in FIG. 7, the start state is a state in which the management infrastructure 100 assigns tasks to each of distributed infrastructures 1, 2, 3, and 4, as shown in FIG. 2. It is assumed that the usage status of the computational resources of distributed infrastructures 1, 2, 3, and 4 in the start state is the same as that shown in the left diagram of FIG. 3. Here, differences from the example of the process flow for migrating a task described above will be mainly described.

[0071] The left diagram of Figure 7 shows the usage status of computational resources on distributed infrastructure 1, distributed infrastructure 2, distributed infrastructure 3, and distributed infrastructure 4 after a certain time has elapsed since the start of task processing. As shown in the left diagram of Figure 7, the usage status of computational resources on distributed infrastructure 1, distributed infrastructure 2, and distributed infrastructure 3 is under pressure. Therefore, in order to alleviate the pressure on computational resources on distributed infrastructure 1, distributed infrastructure 2, and distributed infrastructure 3, the management infrastructure 100 live-migrates the virtual machines for executing the tasks to be migrated on distributed infrastructure 1, the virtual machines for executing the tasks to be migrated on distributed infrastructure 2, and the virtual machines for executing the tasks to be migrated on distributed infrastructure 3 from distributed infrastructure 1, distributed infrastructure 2, and distributed infrastructure 3, respectively. Here, the explanation will be continued assuming that, as a first live migration, the management infrastructure 100 live-migrates the virtual machines for executing the tasks to be migrated on distributed infrastructure 2 and the virtual machines for executing the tasks to be migrated on distributed infrastructure 3 from distributed infrastructure 2 and distributed infrastructure 3, respectively, to distributed infrastructure 4, where the usage status of computational resources is not under pressure.

[0072] The central diagram in Figure 7 shows the usage status of computing resources on distributed infrastructure 1, distributed infrastructure 2, distributed infrastructure 3, and distributed infrastructure 4 after the first live migration. As shown in the central diagram in Figure 7, the first live migration increased the amount of free computing resources on distributed infrastructure 2 and distributed infrastructure 3, thereby resolving the tight computing resources on distributed infrastructure 2 and distributed infrastructure 3. Furthermore, even after the migration target task is live migrated, there is still a sufficient amount of free computing resources on distributed infrastructure 4, so the usage status of computing resources on distributed infrastructure 4 is not tight. Here, the explanation will be continued assuming that, as the second live migration, the management infrastructure 100 live migrates a virtual machine for executing the migration target task on distributed infrastructure 1 from distributed infrastructure 1 to distributed infrastructure 3, where the usage status of computing resources is not tight.

[0073] The right diagram in Figure 7 shows the usage status of computing resources on distributed infrastructure 1, distributed infrastructure 2, distributed infrastructure 3, and distributed infrastructure 4 after the second live migration. As shown in the right diagram in Figure 7, the second live migration increased the amount of free computing resources on distributed infrastructure 1, and as a result, the tight computing resource situation on distributed infrastructure 1 was resolved. Furthermore, even after the migration target task was live migrated, there was still a sufficient amount of free computing resources on distributed infrastructure 3, so the usage status of computing resources on distributed infrastructure 3 was not tight. As described above, the two live migrations properly adjusted the usage status of computing resources among multiple distributed infrastructures.

[0074] 8 is an explanatory diagram for explaining another example of live migration, showing details of the live migration shown in FIG.

[0075] For example, to perform the first live migration, the management infrastructure 100 selects a task to be migrated from among the tasks assigned to the distributed infrastructure 2, namely, the generation of segment 3, the generation of segment 4, the generation of segment 7, and the generation of segment 8. For example, the management infrastructure 100 preferentially selects, as the task to be migrated, the generation of a segment adjacent to any of segments 11, 12, 15, and 16, which are the generation targets of the task assigned to the distributed infrastructure 2, which is the live migration destination of the first live migration. Here, the explanation will continue assuming that the management infrastructure 100 selects, as the task to be migrated, the generation of segment 8 from the generation of segment 7 adjacent to segment 11 and the generation of segment 8 adjacent to segment 12.

[0076] Next, to perform the first live migration, the management infrastructure 100 selects a task to be migrated from among the tasks assigned to the distributed infrastructure 3, namely, the generation of segment 9, the generation of segment 10, the generation of segment 13, and the generation of segment 14. For example, the management infrastructure 100 preferentially selects, as the task to be migrated, the generation of a segment adjacent to any of segments 11, 12, 15, and 16, which are the generation targets of the task assigned to the distributed infrastructure 3, which is the live migration destination of the first live migration. Here, the explanation will continue assuming that the management infrastructure 100 has selected, as the tasks to be migrated, the generation of segment 10 adjacent to segment 11 and the generation of segment 14 adjacent to segment 15.

[0077] The management infrastructure 100 may perform a first live migration based on the above-described selection. As shown in Fig. 8 , the management infrastructure 100 live-migrates the virtual machine for generating segment 8 from distributed infrastructure 2 to distributed infrastructure 4, and live-migrates the virtual machines for generating segments 10 and 14 from distributed infrastructure 2 to distributed infrastructure 4.

[0078] For example, to perform the second live migration, the management infrastructure 100 selects a live migration destination for the virtual machine to execute the task to be migrated from among distributed infrastructure 2, distributed infrastructure 3, and distributed infrastructure 4, which have not tight computing resource usage conditions. For example, the management infrastructure 100 preferentially selects, as the live migration destination, a distributed infrastructure with a larger amount of free computing resources from among distributed infrastructure 2, distributed infrastructure 3, and distributed infrastructure 4. Here, the explanation will continue assuming that the management infrastructure 100 selects distributed infrastructure 3, which has the largest amount of free computing resources, as the live migration destination.

[0079] For example, to perform the second live migration, the management infrastructure 100 selects a task to be migrated from among the tasks assigned to distributed infrastructure 1, namely, generating segment 1, generating segment 2, generating segment 5, and generating segment 6. For example, the management infrastructure 100 preferentially selects, as the task to be migrated, the generation of a segment adjacent to either segment 9 or segment 13, which is the generation target of the task assigned to distributed infrastructure 3, among the tasks assigned to distributed infrastructure 1. Here, the explanation will continue assuming that the management infrastructure 100 selects, as the task to be migrated, the generation of segment 5 adjacent to segment 9.

[0080] The management infrastructure 100 may perform a second live migration based on the above-described selection. As shown in Fig. 8, the management infrastructure 100 live-migrates the virtual machine for generating segment 5 from distributed infrastructure 1 to distributed infrastructure 3.

[0081] 7 and 8, even if there are multiple distributed platforms with tight computing resource usage, the management platform 100 can ultimately appropriately adjust the computing resource usage among the multiple distributed platforms by performing live migration multiple times. As a result, the system 10 according to the embodiment shown in FIG. 7 and 8 can suppress a decrease in the processing speed of the entire simulation process even if there are multiple distributed platforms with tight computing resource usage.

[0082] 9 is an explanatory diagram illustrating another example of the process flow for migrating a task. In the example of the process flow for migrating a task shown in FIG. 9, the start state is a state in which the management infrastructure 100 assigns tasks to each of distributed infrastructures 1, 2, 3, and 4, as shown in FIG. 2. It is assumed that the usage status of the computational resources of distributed infrastructures 1, 2, 3, and 4 in the start state is the same as that shown in the left diagram of FIG. 3. Here, differences from the example of the process flow for migrating a task described above will be mainly described.

[0083] The left diagram in Figure 9 shows the usage status of computational resources on distributed infrastructure 1, distributed infrastructure 2, distributed infrastructure 3, and distributed infrastructure 4 after a certain time has elapsed since the start of task processing. As shown in the left diagram in Figure 9, the usage status of computational resources on distributed infrastructure 1 is tight. Therefore, in order to alleviate the tightness of computational resources on distributed infrastructure 1, the management infrastructure 100 live-migrates a virtual machine for executing the task to be migrated from distributed infrastructure 1. Here, the explanation will continue assuming that the management infrastructure 100 has selected distributed infrastructure 3, whose usage status of computational resources is not tight, as the live migration destination of the virtual machine.

[0084] Furthermore, the management infrastructure 100 performs parameter tuning of the RAN control function, thereby offloading at least a portion of the processing load of the RAN control function of distributed infrastructure 1 to any one of distributed infrastructures 2, 3, and 4, where the usage of computing resources is not under pressure. Here, the explanation will continue assuming that the management infrastructure 100 offloads at least a portion of the processing load of the RAN control function of distributed infrastructure 1 to distributed infrastructure 2.

[0085] The right diagram in Figure 9 shows the usage status of computing resources on distributed infrastructure 1, distributed infrastructure 2, distributed infrastructure 3, and distributed infrastructure 4 after live migration and offloading. As shown in the right diagram in Figure 9, the amount of free computing resources on distributed infrastructure 1 increased due to live migration and offloading, and the tight computing resource situation on distributed infrastructure 1 was resolved. Furthermore, even after the migration target task was live migrated, there was still a sufficient amount of free computing resources on distributed infrastructure 3, and even after the processing load was offloaded, there was still a sufficient amount of free computing resources on distributed infrastructure 2, so the usage status of computing resources on distributed infrastructure 2 and distributed infrastructure 3 is not tight. As described above, live migration and offloading have appropriately adjusted the usage status of computing resources among multiple distributed infrastructures.

[0086] According to the system 10 of the embodiment shown in Fig. 9, in addition to migrating the migration target tasks, the system 10 offloads the processing load of the RAN control function, thereby enabling a more flexible response when a distributed infrastructure with tight computing resource usage occurs. As a result, the system 10 of the embodiment shown in Fig. 9 can realize simulation processing that is less susceptible to external influences.

[0087] 9 , the management infrastructure 100 selects a distributed infrastructure that is different from the distributed infrastructure that is the live migration destination as the offload destination distributed infrastructure. The management infrastructure 100 may select the same distributed infrastructure as the live migration destination distributed infrastructure as the offload destination distributed infrastructure. Furthermore, the management infrastructure 100 may perform only offloading without performing live migration.

[0088] 10 shows an example of the functional configuration of the management infrastructure 100. The management infrastructure 100 includes a storage unit 102, a task allocation unit 104, a transmission unit 106, a reception unit 108, a determination unit 110, a task migration unit 112, a selection unit 114, an offload unit 116, and an integration unit 118. Note that it is not essential for the management infrastructure 100 to include all of these components.

[0089] The storage unit 102 stores various types of information. For example, the storage unit 102 stores location information indicating the location of each of the multiple distributed infrastructures 200. For example, the storage unit 102 stores total resource amount information indicating the total resource amount of the execution unit of each distributed infrastructure 200.

[0090] The task allocating unit 104 allocates tasks included in the simulation process to each distributed infrastructure 200 of the multiple distributed infrastructures 200. The task allocating unit 104 allocates tasks to each distributed infrastructure 200, for example, based on the location of each distributed infrastructure 200 indicated by the location information stored in the storage unit 102. The task allocating unit 104 allocates tasks to each distributed infrastructure 200, for example, such that the task volume of tasks allocated to distributed infrastructures 200 located in rural areas is greater than the task volume of tasks allocated to distributed infrastructures 200 located in urban areas.

[0091] For example, when multiple distributed infrastructures 200 cooperatively process a spatial simulation process, the task allocating unit 104 allocates a task of generating at least two of the multiple segments to each distributed infrastructure 200 based on the location of each distributed infrastructure 200 and the location of each partition. The task allocating unit 104 allocates tasks to each distributed infrastructure 200 such that, for example, a task of generating a segment corresponding to a partition is preferentially allocated to a distributed infrastructure 200 located at a shorter distance from the location of the partition.

[0092] For example, when multiple distributed infrastructures 200 cooperatively process spatial simulation processing, the task allocating unit 104 allocates tasks to each distributed infrastructure 200 based further on the coverage area of ​​the RAN 300 that is the control target of each distributed infrastructure 200. For example, the task allocating unit 104 allocates tasks to each distributed infrastructure 200 so that at least two partitions corresponding to at least two segments that are the generation targets of tasks to be allocated to each distributed infrastructure 200 more closely match the coverage area of ​​the RAN 300 that is the control target of each distributed infrastructure 200.

[0093] The transmitting unit 106 transmits various types of information. The transmitting unit 106 transmits various types of information via, for example, a core network. The transmitting unit 106 transmits various types of information via, for example, the Internet.

[0094] The transmitting unit 106 transmits, for example, various types of information to each distributed infrastructure 200 of the multiple distributed infrastructures 200. The transmitting unit 106 transmits, for example, task information indicating tasks assigned to each distributed infrastructure 200 to each distributed infrastructure 200. The transmitting unit 106 may also transmit various types of information to any other device.

[0095] The receiving unit 108 receives various types of information. The receiving unit 108 receives various types of information, for example, via a core network. The receiving unit 108 receives various types of information, for example, via the Internet. The receiving unit 108 may store the received various types of information in the various information storage unit 102.

[0096] The receiving unit 108 receives various types of information from each distributed infrastructure 200 of the multiple distributed infrastructures 200. The receiving unit 108 receives, for example, usage status information indicating the usage status of the computational resources of the distributed infrastructure 200 from each distributed infrastructure 200. The receiving unit 108 receives, for example, usage status information indicating the usage status of the execution unit of the distributed infrastructure 200 from each distributed infrastructure. The receiving unit 108 receives, for example, task processing results from each distributed infrastructure in which the distributed infrastructure 200 processed a task.

[0097] The determination unit 110 executes various determination processes. The determination unit 110 executes various determination processes periodically.

[0098] The determining unit 110 determines, for example, the usage status of the computational resources of each distributed infrastructure 200. The determining unit 110 determines, for example, the usage status of the execution unit of each distributed infrastructure 200.

[0099] The determination unit 110 determines the usage status of the execution unit of each distributed infrastructure 200, for example, based on the usage status information of each distributed infrastructure 200. The determination unit 110 determines, for example, whether the usage status of the execution unit of each distributed infrastructure 200 is under pressure or not.

[0100] For example, if the amount of free resources in the execution unit of the distributed infrastructure 200 is less than a predetermined first resource amount threshold, the determination unit 110 determines that the usage status of the execution unit of the distributed infrastructure 200 is under pressure. On the other hand, if the amount of free resources in the execution unit of the distributed infrastructure 200 is greater than the first resource amount threshold, the determination unit 110 determines that the usage status of the execution unit of the distributed infrastructure 200 is not under pressure.

[0101] The determination unit 110 determines the amount of free resources of the execution unit of the distributed infrastructure 200, for example, based on the total resource amount information stored in the storage unit 102. The determination unit 110 determines the amount of free resources of the execution unit of the distributed infrastructure 200, for example, by subtracting the amount of resources used by the execution unit of the distributed infrastructure 200, which is indicated by the usage status information of the distributed infrastructure 200, from the total resource amount of the execution unit of the distributed infrastructure 200, which is indicated by the total resource amount information.

[0102] The task migration unit 112 migrates a task assigned to each of the multiple distributed infrastructures 200. For example, the task migration unit 112 migrates a task assigned to each of the multiple distributed infrastructures 200 multiple times.

[0103] For example, when the determination unit 110 determines that the usage status of the execution unit of one of the multiple distributed infrastructures 200 is under pressure, the task migration unit 112 migrates a migration target task, which is at least a part of the tasks assigned to the one distributed infrastructure 200, from the one distributed infrastructure to another of the multiple distributed infrastructures 200 for which the determination unit 110 has determined that the usage status of the execution unit is not under pressure. For example, when there are multiple other distributed infrastructures 200 for which the determination unit 110 has determined that the usage status of the execution unit is not under pressure, the task migration unit 112 migrates the migration target task from the one distributed infrastructure to the multiple distributed infrastructures 200. When there are no other distributed infrastructures 200 for which the determination unit 110 has determined that the usage status of the execution unit is not under pressure, the task migration unit 112 may temporarily suspend the multiple distributed infrastructures 200 from processing tasks.

[0104] For example, when multiple distributed infrastructures 200 cooperatively process a spatial simulation process, the task migration unit 112 migrates a migration target task, which is a task that generates at least one segment of the tasks assigned to the one distributed infrastructure 200, from the one distributed infrastructure 200 to the other distributed infrastructure 200. In this case, the migration target task is, for example, a task that generates one segment of the tasks assigned to the one distributed infrastructure 200. The migration target task may be a task that generates two or more segments of the tasks assigned to the one distributed infrastructure 200.

[0105] The task migration unit 112 determines the task amount of the task to be migrated, for example, based on the amount of free resources of the other distributed infrastructure 200. For example, the task migration unit 112 increases the task amount of the task to be migrated as the amount of free resources of the other distributed infrastructure 200 increases.

[0106] For example, when the amount of free resources of the other distributed infrastructure 200 is greater than a predetermined second resource amount threshold, the task migration unit 112 increases the task amount of the task to be migrated compared to when the amount of free resources of the other distributed infrastructure 200 is less than the second resource amount threshold. Note that the second resource amount threshold is greater than the first resource amount threshold.

[0107] For example, when multiple distributed infrastructures 200 cooperatively process a spatial simulation process, the task migration unit 112 determines the task amount of the task to be migrated by determining the number of segments to be generated for the task to be migrated based on the amount of free resources of the other distributed infrastructures 200. For example, the task migration unit 112 increases the number of segments to be generated for the task to be migrated as the amount of free resources of the other distributed infrastructures 200 increases. For example, when the amount of free resources of the other distributed infrastructures 200 is greater than a second resource amount threshold, the task migration unit 112 increases the number of segments to be generated for the task to be migrated compared to when the amount of free resources of the other distributed infrastructures 200 is less than the second resource amount threshold.

[0108] The task migration unit 112 migrates the migration target task from the one distributed infrastructure 200 to the other distributed infrastructure 200, for example, by live-migrating a virtual machine used by the one distributed infrastructure 200 to execute the migration target task from the one distributed infrastructure 200 to the other distributed infrastructure 200. The task migration unit 112 may migrate the migration target task from the one distributed infrastructure 200 to the other distributed infrastructure 200 by any other method.

[0109] The selection unit 114 executes various selection processes, such as selection processes related to the migration of tasks assigned to each of the multiple distributed infrastructures 200 .

[0110] For example, the selection unit 114 selects a migration destination for a migration target task of one distributed infrastructure 200 for which the determination unit 110 has determined that the usage status of the execution unit is under pressure. For example, when there are multiple other distributed infrastructures 200 for which the determination unit 110 has determined that the usage status of the execution unit is not under pressure, the selection unit 114 selects a migration destination for a migration target task of the one distributed infrastructure 200. The task migration unit 112 may migrate the migration target task of the one distributed infrastructure 200 from the one distributed infrastructure 200 to the other distributed infrastructure 200 selected by the selection unit 114.

[0111] For example, the selection unit 114 preferentially selects, as the migration destination of the migration target task of the one distributed infrastructure 200, one of the plurality of other distributed infrastructures 200 that is located at a position closer to the position of the one distributed infrastructure 200. For example, the selection unit 114 preferentially selects, as the migration destination of the migration target task of the one distributed infrastructure 200, one of the plurality of other distributed infrastructures 200 that has a larger amount of free resources in the execution unit.

[0112] For example, when multiple distributed platforms 200 cooperatively process a spatial simulation process, the selection unit 114 selects a migration target task of one distributed platform 200 for which the determination unit 110 has determined that the usage status of the execution unit is under pressure. The selection unit 114 selects the migration target task by, for example, selecting a generation target segment for the migration target task from generation target segments for tasks assigned to the one distributed platform 200. The selection unit 114 selects the migration target task by, for example, selecting a number of generation target segments for the migration target task from generation target segments for tasks assigned to the one distributed platform 200, determined by the task migration unit 112. The task migration unit 112 migrates the migration target task selected by the selection unit 114 from the one distributed platform to another distributed platform for which the determination unit 110 has determined that the usage status of the execution unit is not under pressure.

[0113] For example, the selection unit 114 preferentially selects, as the migration target task, a task that generates at least one segment adjacent to a segment that is the generation target of a task assigned to the other distributed infrastructure 200, from among the tasks assigned to the one distributed infrastructure 200. For example, when the coverage area of ​​the RAN 300 that is the control target of the one distributed infrastructure 200 includes an overlapping area that overlaps with the coverage area of ​​the RAN 300 that is the control target of the other distributed infrastructure 200, the selection unit 114 preferentially selects, as the migration target task, a task that generates at least one segment that corresponds to the overlapping area from among the tasks assigned to the one RAN 300.

[0114] The offload unit 116 offloads the processing load of the RAN control function of the distributed infrastructure 200. For example, the offload unit 116 offloads the processing load of the RAN control function of the distributed infrastructure 200 multiple times.

[0115] For example, the offload unit 116 offloads at least a portion of the processing load of the RAN control function of one distributed infrastructure 200 for which the determination unit 110 has determined that the usage status of the execution unit is under pressure, from the one distributed infrastructure 200 to another distributed infrastructure 200 for which the determination unit 110 has determined that the usage status of the execution unit is not under pressure. The offload unit 116 offloads the at least a portion of the processing load from the one distributed infrastructure 200 to the other distributed infrastructure 200 by, for example, performing parameter tuning of the RAN control function of the one distributed infrastructure 200 and the RAN control function of the other distributed infrastructure 200. The offload unit 116 may offload the at least a portion of the processing load from the one distributed infrastructure 200 to the other distributed infrastructure 200 by any other method.

[0116] The offload unit 116 determines the processing amount of the at least a portion of the processing load, for example, based on the amount of free resources of the other distributed infrastructure 200. For example, the offload unit 116 increases the processing amount of the at least a portion of the processing load the greater the amount of free resources of the other distributed infrastructure 200. For example, when the amount of free resources of the other distributed infrastructure 200 is greater than a second resource amount threshold, the offload unit 116 increases the processing amount of the at least a portion of the processing load compared to when the amount of free resources of the other distributed infrastructure 200 is less than the second resource amount threshold.

[0117] The selection unit 114 may execute a selection process related to offloading the processing load of the RAN control function of each of the multiple distributed infrastructures 200. The offload unit 116 may offload at least a portion of the processing load from the one distributed infrastructure 200 to the other distributed infrastructure 200 selected by the selection unit 114.

[0118] For example, when there are multiple other distributed infrastructures 200, the selection unit 114 selects an offload destination for at least a portion of the processing load. For example, the selection unit 114 preferentially selects, as the offload destination, one of the multiple other distributed infrastructures 200 that has a larger amount of free resources in the execution unit.

[0119] For example, the selection unit 114 selects, as the offload destination, a distributed infrastructure 200 that is different from the distributed infrastructure 200 that is the migration destination of the migration target task of the one distributed infrastructure 200. The selection unit 114 may select, as the offload destination, the same distributed infrastructure 200 as the migration destination distributed infrastructure 200 of the migration target task of the one distributed infrastructure 200.

[0120] The integrating unit 118 integrates task processing results obtained by each distributed infrastructure 200 of the multiple distributed infrastructures 200 processing a task. The integrating unit 118 integrates, for example, each task processing result stored in the storage unit 102. The transmitting unit 106 may transmit an integrated task processing result, which is the task processing result integrated by the integrating unit 118, to each distributed infrastructure 200 of the multiple distributed infrastructures 200.

[0121] 11 shows an example of the functional configuration of the distributed infrastructure 200. The distributed infrastructure 200 includes a storage unit 202, an acquisition unit 204, an execution unit 206, a transmission unit 210, and a determination unit 212. Note that it is not essential that the distributed infrastructure 200 include all of these components.

[0122] The storage unit 202 stores various types of information, such as candidate distributed infrastructure information indicating candidate distributed infrastructures 200 to which the migration target tasks are to be migrated.

[0123] The acquisition unit 204 acquires various types of information. For example, the acquisition unit 204 acquires various types of information by receiving the various types of information via a core network. For example, the acquisition unit 204 acquires various types of information by receiving the various types of information via the Internet. The acquisition unit 204 may store the acquired information in the storage unit 202.

[0124] The acquisition unit 204 acquires, for example, various types of information from the management board 100. The acquisition unit 204 acquires, for example, task information from the management board 100. The acquisition unit 204 receives, for example, an integrated task processing result from the management board 100.

[0125] The execution unit 206 executes various processes. The execution unit 206 includes, for example, a RAN control function 207 and a task processing function 209. The RAN control function 207 and the task processing function 209 may use the same computational resources.

[0126] The RAN control function 207 controls the functions of the RAN 300. The RAN control function 207 controls the functions of the RAN 300, for example, by executing a RAN_AI. The RAN control function 207 may control the functions of the RAN 300 by executing any other process.

[0127] The task processing function 209 processes a task. For example, the task processing function 209 processes a task included in a simulation process that is performed in cooperation with multiple distributed infrastructures 200. For example, the task processing function 209 processes a task indicated by task information. The task processing function 209 may store the task processing results obtained by processing the task in the storage unit 202.

[0128] The task processing function 209 processes a task, for example, by executing an application. The task processing function 209 processes a task, for example, by executing an AI application. The task processing function 209 processes a task, for example, by executing a non-RAN AI application.

[0129] The acquisition unit 204 acquires, for example, usage status information indicating the usage status of the execution unit 206. The usage status information of the execution unit 206 includes, for example, used resource amount information indicating the amount of resources being used by the execution unit 206. The usage status information of the execution unit 206 includes, for example, free resource amount information indicating the amount of free resources of the execution unit 206.

[0130] The RAN control function 207 controls the functions of the RAN 300 based on task processing results, for example, when multiple distributed infrastructures 200 cooperatively process a spatial simulation process that simulates the communication environment of the RAN 300 that is the control target of each distributed infrastructure 200. The RAN control function 207 controls the functions of the RAN 300 based on task processing results, for example, when the task processing function 209 processes a task. The RAN control function 207 may control the functions of the RAN 300 based on the integrated task processing results.

[0131] The transmitting unit 210 transmits various types of information. The transmitting unit 210 transmits various types of information via, for example, a core network. The transmitting unit 210 transmits various types of information via, for example, the Internet.

[0132] The transmitting unit 210 transmits various information to, for example, the management board 100. The transmitting unit 210 may transmit various information to any other device.

[0133] The transmission unit 210 transmits, for example, usage status information of the execution unit 206. The transmission unit 210 transmits, for example, a task processing result obtained when the task processing function 209 processes a task.

[0134] The determination unit 212 executes various determination processes. The determination unit 212 executes various determination processes periodically.

[0135] The determining unit 212 determines the usage status of the execution unit 206, for example, based on usage status information of the execution unit 206. The determining unit 212 determines, for example, whether the usage status of the execution unit 206 is under pressure or not.

[0136] For example, if the amount of free resources in the execution unit 206 is less than a predetermined first resource amount threshold, the determination unit 212 determines that the usage status of the execution unit 206 is under pressure. On the other hand, if the amount of free resources in the execution unit 206 is greater than the first resource amount threshold, the determination unit 212 determines that the usage status of the execution unit 206 is not under pressure.

[0137] When the determination unit 212 determines that the usage status of the execution unit 206 is in a tight situation, the transmission unit 210 transmits tight situation information indicating that the usage status of the execution unit 206 is in a tight situation to the management infrastructure 100. The tight situation information includes, for example, candidate distribution infrastructure information. The tight situation information may also include available resource amount information.

[0138] 12 is an explanatory diagram illustrating an example of the processing flow of the system 10. Here, the starting state is a state in which the management infrastructure 100 has not assigned any tasks to the distributed infrastructure 220 and the distributed infrastructure 240. It is assumed that the distributed infrastructure 220 and the distributed infrastructure 240 have the same functions as the distributed infrastructure 200.

[0139] In step (sometimes abbreviated as S) 102, the task allocation unit 104 allocates, to the distributed infrastructure 220, a task included in a simulation process that is to be performed cooperatively by the distributed infrastructure 220 and the distributed infrastructure 240. In S104, the task allocation unit 104 allocates, to the distributed infrastructure 240, a task included in the simulation process.

[0140] In S106, the task processing function 209 of the distributed infrastructure 220 starts processing the task that the acquisition unit 204 of the distributed infrastructure 220 received from the management infrastructure 100 in S102. In S108, the task processing function 209 of the distributed infrastructure 240 starts processing the task that the acquisition unit 204 of the distributed infrastructure 240 received from the management infrastructure 100 in S104.

[0141] At S110, the acquisition unit 204 of the distributed infrastructure 220 acquires usage status information indicating the usage status of the execution unit 206 of the distributed infrastructure 220. The transmission unit 210 of the distributed infrastructure 220 transmits the usage status information to the management infrastructure 100. At S112, the acquisition unit 204 of the distributed infrastructure 240 acquires usage status information indicating the usage status of the execution unit 206 of the distributed infrastructure 240. The transmission unit 210 of the distributed infrastructure 240 transmits the usage status information to the management infrastructure 100.

[0142] In S114, the determination unit 110 determines whether the usage status of the execution unit 206 of the distributed infrastructure 220 is under pressure or not under pressure, based on the usage status information received by the receiving unit 108 from the distributed infrastructure 220 in S110. The determination unit 110 also determines whether the usage status of the execution unit 206 of the distributed infrastructure 240 is under pressure or not under pressure, based on the usage status information received by the receiving unit 108 from the distributed infrastructure 240 in S112. Here, the explanation will continue assuming that the determination unit 110 has determined that the usage status of the execution unit 206 of the distributed infrastructure 220 is under pressure and that the usage status of the execution unit 206 of the distributed infrastructure 240 is not under pressure.

[0143] In S116, the task migration unit 112 migrates the migration target task of the distributed infrastructure 220 for which the determination unit 110 determined in S114 that the usage status of the execution unit 206 is under pressure, from the distributed infrastructure 220 to the distributed infrastructure 240 for which the determination unit 110 determined in S114 that the usage status of the execution unit 206 is not under pressure. The task migration unit 112 migrates the migration target task of the distributed infrastructure 220 from the distributed infrastructure 220 to the distributed infrastructure 240, for example, by instructing the distributed infrastructure 220 to migrate the migration target task. In S118, the task processing function 209 of the distributed infrastructure 220 migrates the migration target task from the distributed infrastructure 220 to the distributed infrastructure 240 in accordance with the instruction received by the acquisition unit 204 from the management infrastructure 100 in S116.

[0144] 13 is an explanatory diagram illustrating another example of the processing flow of the system 10. Here, a state in which the management infrastructure 100 has not assigned any tasks to the distributed infrastructure 220 or the distributed infrastructure 240 is taken as the starting state.

[0145] In S202, the task allocating unit 104 allocates, to the distributed infrastructure 220, a task included in a simulation process that is to be performed cooperatively by the distributed infrastructure 220 and the distributed infrastructure 240. In S204, the task allocating unit 104 allocates, to the distributed infrastructure 240, a task included in the simulation process.

[0146] In S206, the task processing function 209 of the distributed infrastructure 220 starts processing the task that the acquisition unit 204 of the distributed infrastructure 220 received from the management infrastructure 100 in S102. In S208, the task processing function 209 of the distributed infrastructure 240 starts processing the task that the acquisition unit 204 of the distributed infrastructure 240 received from the management infrastructure 100 in S104.

[0147] In S210, the determination unit 212 of the distributed infrastructure 220 determines whether the usage status of the execution unit 206 of the distributed infrastructure 220 is under pressure or not, based on the usage status information acquired by the acquisition unit 204 of the distributed infrastructure 220. Here, the explanation will continue assuming that the determination unit 212 has determined that the usage status of the execution unit 206 is under pressure.

[0148] In S212, the transmitting unit 210 of the distributed infrastructure 220 transmits the pressure situation information to the management infrastructure 100. In S214, the task migration unit 112 inquires of the distributed infrastructure 240, which is a candidate destination for the migration target task of the distributed infrastructure 220 and is indicated by the candidate distributed infrastructure information included in the pressure situation information received by the receiving unit 108 from the distributed infrastructure 220 in S212, whether the migration target task of the distributed infrastructure 220 can be migrated. In S216, the task processing function 209 of the distributed infrastructure 240 responds to the inquiry from the management infrastructure 100 in S214. Here, the explanation will continue assuming that the task processing function 209 responds that the migration target task of the distributed infrastructure 220 can be migrated.

[0149] In S218, the task migration unit 112 instructs the distributed infrastructure 220 to migrate the migration target task, thereby migrating the migration target task of the distributed infrastructure 220 from the distributed infrastructure 220 to the distributed infrastructure 240. In S220, the task processing function 209 of the distributed infrastructure 220 migrates the migration target task from the distributed infrastructure 220 to the distributed infrastructure 240 in accordance with the instruction received by the acquisition unit 204 from the management infrastructure 100 in S218.

[0150] 14 schematically illustrates an example of the hardware configuration of a computer 1200 that functions as the management infrastructure 100 or the distribution infrastructure 200. A program installed on the computer 1200 can cause the computer 1200 to function as one or more "parts" of the apparatus according to the above-described embodiments, or can cause the computer 1200 to execute operations associated with the apparatus according to the above-described embodiments or one or more "parts," and / or can cause the computer 1200 to execute a process or steps of the process according to the above-described embodiments. Such a program can be executed by the CPU 1212 to cause the computer 1200 to perform specific operations associated with some or all of the blocks in the flowcharts and block diagrams described herein.

[0151] The computer 1200 according to this embodiment includes a CPU 1212, a RAM 1214, and a graphics controller 1216, which are interconnected by a host controller 1210. The computer 1200 also includes input / output units such as a communication interface 1222, a storage device 1224, a DVD drive 1226, and an IC card drive, which are connected to the host controller 1210 via an input / output controller 1220. The DVD drive 1226 may be a DVD-ROM drive, a DVD-RAM drive, or the like. The storage device 1224 may be a hard disk drive, a solid-state drive, or the like. The computer 1200 also includes legacy input / output units such as a ROM 1230 and a keyboard 1242, which are connected to the input / output controller 1220 via an input / output chip 1240.

[0152] The CPU 1212 operates according to programs stored in the ROM 1230 and the RAM 1214, thereby controlling each unit. The graphics controller 1216 acquires image data generated by the CPU 1212 into a frame buffer or the like provided in the RAM 1214 or into the graphics controller 1216 itself, and causes the image data to be displayed on the display device 1218.

[0153] The communication interface 1222 communicates with other electronic devices via a network. The storage device 1224 stores programs and data used by the CPU 1212 in the computer 1200. The DVD drive 1226 reads programs or data from a DVD-ROM 1227 or the like and provides them to the storage device 1224. The IC card drive reads programs and data from an IC card and / or writes programs and data to an IC card.

[0154] The ROM 1230 stores therein a boot program or the like that is executed by the computer 1200 upon activation, and / or programs that depend on the hardware of the computer 1200. The input / output chip 1240 may also connect various input / output units to the input / output controller 1220 via a USB port, a parallel port, a serial port, a keyboard port, a mouse port, etc.

[0155] The programs are provided by a computer-readable storage medium such as a DVD-ROM 1227 or an IC card. The programs are read from the computer-readable storage medium, installed in the storage device 1224, RAM 1214, or ROM 1230, which are also examples of computer-readable storage media, and executed by the CPU 1212. Information processing described in these programs is read by the computer 1200, and brings about cooperation between the programs and the various types of hardware resources described above. An apparatus or a method may be configured by implementing operations or processing of information in accordance with the use of the computer 1200.

[0156] For example, when communication is performed between computer 1200 and an external device, CPU 1212 may execute a communication program loaded into RAM 1214 and instruct communication interface 1222 to perform communication processing based on the processing described in the communication program. Under the control of CPU 1212, communication interface 1222 reads transmission data stored in a transmission buffer area provided in RAM 1214, storage device 1224, DVD-ROM 1227, or a recording medium such as an IC card, and transmits the read transmission data to a network, or writes received data received from the network to a reception buffer area or the like provided on the recording medium.

[0157] Furthermore, the CPU 1212 may cause all or a necessary portion of a file or database stored in an external recording medium such as the storage device 1224, the DVD drive 1226 (DVD-ROM 1227), an IC card, etc. to be read into the RAM 1214, and may perform various types of processing on the data on the RAM 1214. The CPU 1212 may then write back the processed data to the external recording medium.

[0158] Various types of information, such as various types of programs, data, tables, and databases, may be stored on the recording medium and may undergo information processing. The CPU 1212 may perform various types of processing on data read from the RAM 1214, including various types of operations, information processing, conditional judgment, conditional branching, unconditional branching, information search / replacement, etc., as described throughout this disclosure and specified by the instruction sequences of the programs, and write the results back to the RAM 1214. The CPU 1212 may also search for information in a file, database, etc. on the recording medium. For example, if multiple entries, each having an attribute value of a first attribute associated with an attribute value of a second attribute, are stored on the recording medium, the CPU 1212 may search for an entry whose attribute value of the first attribute matches a specified condition from among the multiple entries, read the attribute value of the second attribute stored in the entry, and thereby obtain the attribute value of the second attribute associated with the first attribute that satisfies a predetermined condition.

[0159] The above-described programs or software modules may be stored in a computer-readable storage medium on or near the computer 1200. A recording medium such as a hard disk or RAM provided in a server system connected to a dedicated communication network or the Internet can also be used as a computer-readable storage medium, thereby providing the programs to the computer 1200 via the network.

[0160] The blocks in the flowcharts and block diagrams in the present embodiments may represent stages of a process in which an operation is performed or "parts" of a device responsible for performing the operation. Particular stages and "parts" may be implemented by dedicated circuitry, programmable circuitry provided with computer-readable instructions stored on a computer-readable storage medium, and / or a processor provided with computer-readable instructions stored on a computer-readable storage medium. The dedicated circuitry may include digital and / or analog hardware circuits, and may include integrated circuits (ICs) and / or discrete circuits. The programmable circuitry may include reconfigurable hardware circuits, such as field programmable gate arrays (FPGAs) and programmable logic arrays (PLAs), including AND, OR, XOR, NAND, NOR, and other logical operations, flip-flops, registers, and memory elements.

[0161] A computer-readable storage medium may include any tangible device capable of storing instructions that are executed by an appropriate device, such that a computer-readable storage medium having instructions stored thereon comprises an article of manufacture, including instructions that can be executed to create means for performing the operations specified in the flowcharts or block diagrams. Examples of computer-readable storage media may include electronic, magnetic, optical, electromagnetic, and semiconductor storage media. More specific examples of computer-readable storage media may include floppy disks, diskettes, hard disks, random access memories (RAMs), read-only memories (ROMs), erasable programmable read-only memories (EPROMs or flash memories), electrically erasable programmable read-only memories (EEPROMs), static random access memories (SRAMs), compact disc read-only memories (CD-ROMs), digital versatile discs (DVDs), Blu-ray discs, memory sticks, integrated circuit cards, and the like.

[0162] The computer readable instructions may include either assembler instructions, instruction set architecture (ISA) instructions, machine instructions, machine-dependent instructions, microcode, firmware instructions, state-setting data, or source or object code written in any combination of one or more programming languages, including object-oriented programming languages ​​such as Smalltalk®, JAVA®, C++, etc., and conventional procedural programming languages ​​such as the “C” programming language or similar programming languages.

[0163] Computer-readable instructions may be provided locally or over a local area network (LAN), a wide area network (WAN) such as the Internet, to a processor of a general purpose computer, special purpose computer, or other programmable data processing apparatus, or programmable circuitry, such that the processor or programmable circuitry executes the computer-readable instructions to generate means for performing the operations specified in the flowcharts or block diagrams. Examples of processors include computer processors, processing units, microprocessors, digital signal processors, controllers, microcontrollers, etc.

[0164] Although the present invention has been described above using embodiments, the technical scope of the present invention is not limited to the scope described in the above embodiments. It will be apparent to those skilled in the art that various modifications and improvements can be made to the above embodiments. It is clear from the claims that such modifications and improvements can also be included within the technical scope of the present invention.

[0165] It should be noted that the execution order of each process, such as operations, procedures, steps, and stages, in the devices, systems, programs, and methods shown in the claims, specifications, and drawings is not specifically stated as "before," "prior to," etc., and that the processes can be performed in any order unless the output of a previous process is used in a subsequent process. Even if the operational flow in the claims, specifications, and drawings is described using "first," "next," etc. for convenience, this does not mean that the processes must be performed in this order.

[0166] 10 System, 30 Wireless base station, 50 Communication terminal, 100 Management infrastructure, 102 Storage unit, 104 Task allocation unit, 106 Transmission unit, 108 Reception unit, 110 Determination unit, 112 Task migration unit, 114 Selection unit, 116 Offload unit, 118 Integration unit, 200 Distribution infrastructure, 202 Storage unit, 204 Acquisition unit, 206 Execution unit, 207 RAN control function, 209 Task processing function, 210 Transmission unit, 212 Determination unit, 300 RAN, 1200 Computer, 1210 Host controller, 1212 CPU, 1214 RAM, 1216 Graphics controller, 1218 Display device, 1220 Input / output controller, 1222 Communication interface, 1224 Storage device, 1226 DVD drive, 1227 DVD-ROM, 1230 ROM, 1240 I / O chip, 1242 keyboard

Claims

1. A system comprising: a plurality of distributed infrastructures that cooperatively process a single simulation process including a plurality of tasks; and a management infrastructure that manages the plurality of distributed infrastructures, wherein each of the plurality of distributed infrastructures has an execution unit that includes a RAN control function that controls the functions of a RAN (Radio Access Network) and a task processing function that processes tasks included in the single simulation process; an acquisition unit that acquires usage status information that indicates the usage status of the execution unit; and a transmission unit that transmits the usage status information, wherein the management infrastructure has: a task allocation unit that assigns the tasks to each of the distributed infrastructures; a reception unit that receives the usage status information from each of the distributed infrastructures; and a determination unit that determines whether the usage status of the execution unit of each of the distributed infrastructures is in a constrained state or not based on the usage status information of each of the distributed infrastructures. a task migration unit that, when the determination unit determines that the usage status of the execution unit of one of the plurality of distributed infrastructures is under pressure, migrates tasks to be migrated, which are at least some of the tasks assigned to the one distributed infrastructure, from the one distributed infrastructure to another distributed infrastructure for which the determination unit determines that the usage status of the execution unit of the one distributed infrastructure is not under pressure.

2. The system described in claim 1, wherein the task migration unit migrates the task to be migrated from the one distributed infrastructure to the other distributed infrastructure by live migrating a virtual machine used by the one distributed infrastructure to execute the task to be migrated from the one distributed infrastructure to the other distributed infrastructure.

3. The system described in claim 1 or 2, wherein the multiple distributed platforms cooperatively process the one simulation process, which is a spatial simulation process that generates a virtual space corresponding to a real space including multiple partitions, each of the multiple segments included in the virtual space corresponds to each of the multiple partitions, the task allocation unit assigns the task of generating at least two of the multiple segments to each of the distributed platforms based on the location of each of the distributed platforms and the location of each of the partitions, and the task migration unit migrates the migration target task, which is the task of generating at least one segment of the tasks assigned to the one distributed platform, from the one distributed platform to the other distributed platform.

4. The system described in claim 3, wherein the management infrastructure further has a selection unit that, when the determination unit determines that the usage status of the execution unit of the one distributed infrastructure is in a tight state, preferentially selects, as the migration target task, from among the tasks assigned to the one distributed infrastructure, a task that generates at least one segment adjacent to the segment that is the generation target of the task assigned to the other distributed infrastructure, and the task migration unit migrates the migration target task selected by the selection unit from the one distributed infrastructure to the other distributed infrastructure.

5. The system described in claim 3, wherein the task allocation unit allocates the tasks to each of the distributed infrastructures based further on the coverage area of ​​the RAN controlled by each of the distributed infrastructures so that at least two partitions corresponding to the at least two segments for which the tasks to be allocated to each of the distributed infrastructures are generated more closely match the coverage area of ​​the RAN controlled by each of the distributed infrastructures.

6. The system described in claim 5, wherein the management infrastructure further has a selection unit that, when the determination unit determines that the usage status of the execution unit of the one distributed infrastructure is in a tight state, preferentially selects, as the migration target task, a task that generates at least one segment corresponding to the overlapping area among the tasks assigned to the one distributed infrastructure when the cover area of ​​the RAN controlled by the one distributed infrastructure includes an overlapping area that overlaps with the cover area of ​​the RAN controlled by the other distributed infrastructure; and the task migration unit migrates the migration target task selected by the selection unit from the one distributed infrastructure to the other distributed infrastructure.

7. The system described in claim 3, wherein the multiple distributed platforms cooperatively process the spatial simulation process that simulates the communication environment of the RAN that is the control target of each of the distributed platforms, and the RAN control function of each of the distributed platforms controls the function of the RAN based on the task processing result obtained by the task processing function processing the task.

8. The system described in claim 1 or 2, wherein the management infrastructure further has a selection unit that, when the determination unit determines that the usage status of the execution unit of the one distributed infrastructure is in a tight state, and when there are multiple other distributed infrastructures, preferentially selects, as the migration destination of the migration target task, one of the multiple other distributed infrastructures that is located at a shorter distance from the location of the one distributed infrastructure, and the task migration unit migrates the migration target task from the one distributed infrastructure to the other distributed infrastructure selected by the selection unit.

9. The system described in claim 1 or 2, wherein the management infrastructure further has a selection unit that, when the determination unit determines that the usage status of the execution unit of the one distributed infrastructure is under pressure, and when there are multiple other distributed infrastructures, preferentially selects one of the multiple other distributed infrastructures that has a greater amount of free resources in its execution unit as the migration destination of the migration target task, and the task migration unit migrates the migration target task from the one distributed infrastructure to the other distributed infrastructure selected by the selection unit.

10. The system described in claim 1 or 2, wherein the management infrastructure further has an offload unit that, when the determination unit determines that the usage status of the execution unit of one of the distributed infrastructures is under pressure, offloads at least a portion of the processing load of the RAN control function of the one of the distributed infrastructures from the one of the distributed infrastructures to another of the plurality of distributed infrastructures for which the determination unit determines that the usage status of the execution unit is not under pressure.

11. A management platform for managing a plurality of distributed platforms that cooperatively process a single simulation process including a plurality of tasks, each of which has an execution unit including a RAN control function that controls RAN functions and a task processing function that processes tasks included in the single simulation process, an acquisition unit that acquires usage status information that indicates the usage status of the execution unit, and a transmission unit that transmits the usage status information, the management platform comprising: a task allocation unit that assigns the tasks to each of the distributed platforms; a reception unit that receives the usage status information from each of the distributed platforms; and a determination unit that determines whether the usage status of the execution unit of each of the distributed platforms is in a tight state or not based on the usage status information of each of the distributed platforms. a task migration unit that, when the determination unit determines that the usage status of the execution unit of one of the plurality of distributed infrastructures is under pressure, migrates tasks to be migrated, which are at least some of the tasks assigned to the one distributed infrastructure, from the one distributed infrastructure to another distributed infrastructure for which the determination unit determines that the usage status of the execution unit of the one distributed infrastructure is not under pressure.

12. A program that, when executed by a computer, causes the computer to function as the management infrastructure according to claim 11.

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