61 results about "Live migration" patented technology

The invention relates to the technical field of virtual machines, in particular to a virtual machine live migration protocol authentication and data protection method which comprises a migration end configuration process, a migrated end configuration process and a migration process. The migration end carries out a migration end configuration process to obtain strategy configuration data of the migration end; the migrated end carries out a migrated end configuration process to obtain strategy configuration data of the migrated end; based on the strategy configuration data of the migration end and the strategy configuration data of the migrated end, the migration end and the migrated end enter a migration process so as to carry out double-end protocol authentication of the migration end and the migrated end, and after the double-end protocol authentication is passed, the migration data is migrated from the migration end to the migrated end, so that the safety protection of the migration data is realized. And the data migration performance is improved.

Embodiments of the invention disclose a virtual machine live migration management method and apparatus, an electronic device and a storage medium. The method comprises the steps of obtaining historical operation data of each virtual machine in a cloud platform environment; constructing a learning task framework composed of a state space, an action space and a reward function; training a state value function, a guide strategy and an execution strategy in the learning task framework based on the historical operation data; the state value function is used for evaluating a state long-term value, the guide strategy is used for planning a target state, and the execution strategy is used for generating a specific migration action; integrating the trained state value function, the guidance strategy and the execution strategy to obtain a migration strategy generation model; and generating a live migration strategy of the virtual machine based on the migration strategy generation model. A migration strategy generation model is obtained through training, and a complex migration strategy can be learned from historical operation data, so that a live migration strategy is dynamically generated, and intelligence and flexibility of migration decision making are remarkably improved.

The present disclosure relates to a device and a method for implementing live migration, where an on-chip system of the present disclosure is comprised in an integrated circuit apparatus, which comprises a general interconnection interface and other processing apparatuses. The computation apparatus interacts with other processing apparatuses to jointly complete computing operations specified by users. The integrated circuit apparatus also comprises a storage apparatus. The storage apparatus is respectively connected to the computation apparatus and other processing apparatuses and is used for storing data of the computation apparatus and other processing apparatuses.

The invention discloses a container real-time migration method and system and a medium. The method comprises the steps that a deduplication method based on content definition partitioning is introduced into container real-time migration, highly redundant memory pages are effectively detected and removed, and an optimal data reduction algorithm is dynamically selected to improve migration performance by means of an adaptive data reduction technology. Experimental results show that the total migration time can be reduced by 75%, and stable performance can be kept under different working load and bandwidth conditions.

The application provides a container virtual machine management method and system, comprising: deploying a Kubevirt project in a Kubernetes cluster, enabling an EKS cloud platform to run a virtual machine in a container mode; and determining a cloud management interface graphical interface configuration, a customized image, real-time migration, CPU performance optimization and virtual machine internal performance index monitoring of the EKS cloud platform. The application manages and schedules virtual machine resources and container resources by the Kubernetes, provides a unified development platform for developers, realizes the expansion of cloud platform resources, directly places virtualization workloads in a development workflow, supports internal interaction access between a virtual machine application and a containerized application, and enables the decomposition of the application while still using the remaining virtualization components on demand.

Embodiments of the present application provide a virtual machine live migration method, device, system and storage medium. An optimization scheme is proposed for a traditional live migration architecture. By configuring an acceleration device for a source host, the live migration work of the control plane and the data plane can be completely sunk to the acceleration device for execution on the source host side. The live migration work can be completed by cooperation of the destination host and the acceleration device, which realizes zero dependence of the live migration work on the source host resources. Even in the case that the computing resources of the source host are fully occupied, the performance of the live migration is not affected, and the live migration function achieves zero jitter for a virtual machine running on the source host.

A cluster distributed resource scheduling method, apparatus and device, and a storage medium. The method includes: respectively acquiring host CPU utilization rates and vCPU utilization rates; respectively performing a quantization operation on the host CPU utilization rates and the vCPU utilization rates, to obtain host quantized pressure values and virtual machine quantized pressure values; acquiring historical host pressure values and historical virtual machine pressure values; according to the host quantified pressure values and historical host pressure values respectively corresponding to hosts, and virtual machine quantified pressure values and historical virtual machine pressure values respectively corresponding to virtual machines in the hosts, calculating target CPU pressure values respectively corresponding to the hosts; and performing a live migration operation on the virtual machines in the hosts according to the target CPU pressure values.

The present application relates to the technical field of cloud computing and virtualization, and particularly to a cloud service resource scheduling system based on virtual machines; comprising benchmark construction, parallel differential analysis, feature matching and scheduling execution modules; the system collects real-time indexes to generate ideal values without interference, and calculates real deviation and theoretical deviation based on interference models; the core is to calculate the similarity of the two types of deviation in the feature space, and accordingly to distinguish resource contention and business increment, to perform cross-machine live migration when the similarity meets the standard, and otherwise to perform in-place expansion; the present application converts abnormal diagnosis into a pattern matching problem, accurately identifies the root cause of performance degradation, and effectively avoids misjudgment and invalid operation of traditional schemes.

Adaptive live migration running on a hypervisor and a destination network device performs the migration of a virtual machine for a source storage device in a source network device and a destination storage device in the destination network device without stopping the virtual machine for the source storage device.

A system or method for maintaining high availability of containerized workloads in a cloud environment utilizing spot instances. The system provisions multiple spot instances based on corresponding node templates and instantiates production workloads on these spot instances. For each node template, a mirrored standby node template is generated, and on-demand instances are provisioned as standby nodes accordingly. Dummy workloads are instantiated on the on-demand instances, each pre-pulling a container image and reserving compute resources for a corresponding production workload. The system continuously monitors for interruptions of spot instances running production workloads. In response to detecting such an interruption, the system maps the affected production workload to a corresponding dummy workload on a standby node and migrates the production workload to the standby node.

The application relates to the technical field of database migration, and discloses a method for migrating a database without stopping, and the specific steps comprise the following steps: S40, establishing data bidirectional synchronization of new and old databases; S41, detecting the data synchronization speed and quality of the new and old databases, if the detection is passed, the next step is performed, and if the detection is not passed, the migration is stopped, and the operation is ended. The method for migrating a database without stopping, through which data migration is performed, strictly follows an industry database master-slave synchronization scheme in data synchronization, the correctness and integrity of the data are guaranteed, bidirectional synchronization also provides a convenient channel for subsequent rollback; with the aid of a MySQL Binlog characteristic, a high-efficiency method for inquiring data synchronization progress is derived, millisecond-level switching of a new database is supported, the influence on the running business is very small or even zero, and the user is not aware, so that data can be migrated without stopping.

A method of “warm” migrating a virtual machine (VM) on a source host to a target virtual machine on a destination host. The method begins by mirroring contents of disk onto a target disk associated with the target VM. Transfer of the RAM contents is then initiated. Unlike live migration strategies where data transfer occurs at a high rate, the RAM contents are transferred at a low transfer rate. While the contents of the RAM are being transferred, a shutdown of the virtual machine is initiated. This operation flushes to disk all of the remaining RAM contents. Before the shutdown completes, those remaining contents, now on disk, are mirrored to the target disk. Once that mirroring is finished, the shutdown of the virtual machine is completed, and this shutdown is mirrored at the destination host. To complete the warm migration, the target virtual machine is then booted from the target disk.

Provided are systems, methods, and apparatuses for systems and methods for live migration with assigned devices. In one or more examples, the systems, devices, and methods include receiving, at a destination memory, first data from a source; indicating in a mapping table that second data from the source memory is unavailable; sending, to the memory manager, a first message requesting to access on the memory of the destination device one or more memory pages associated with the second data; sending, to a migration manager, a second message requesting the one or more memory pages associated with the second data; receiving, from the memory manager, a third message indicating the one or more memory pages are transferred; and accessing the one or more memory pages on the memory of the destination device.

The invention discloses a virtual machine live migration method and device, electronic equipment and a storage medium, and relates to the technical field of computers.The method comprises the steps that after a source virtual machine receives a data migration request, data in a processing unit is synchronized to a video memory, and resource calling on the processing unit is stopped; wherein the source virtual machine can directly access the processing unit; and the source virtual machine obtains video memory allocation information of the video memory, transmits effective migration data in the video memory to the target virtual machine according to the video memory allocation information, and sends an end message to the target virtual machine to instruct the target virtual machine to recover resource calling of the processing unit under the condition of determining that migration data transmission is finished. According to the embodiment of the invention, a user does not need to manually bind and unbind the processing unit and the virtual machine, full automation of live migration of the virtual machine is realized, the implementation of the live migration process does not need to modify a system kernel code, a kernel is not invaded, and the stability and continuity of services in the live migration process of the virtual machine are ensured.

The technology provides for live migration from a first cluster to a second cluster. For instance, when requests to one or more cluster control planes are received, a predetermined fraction of the received requests may be allocated to a control plane of the second cluster, while a remaining fraction of the received requests may be allocated to a control plane of the first cluster. The predetermined fraction of requests are handled using the control plane of the second cluster. While handling the predetermined fraction of requests, it is detected whether there are failures in the second cluster. Based on not detecting failures in the second cluster, the predetermined fraction of requests allocated to the control plane of the second cluster may be increased in predetermined stages until all requests are allocated to the control plane of the second cluster.

The invention discloses a method for supporting simultaneous live migration of multiple virtual machines without packet loss by combining software and hardware in the field of virtual machine migration. The method comprises the following steps: creating virtual machine live migration auxiliary equipment D1 and a hardware dirty page reporting queue; creating a dirty page processing thread to record dirty page information; according to the live migration request, the vDPA driver registers to-be-migrated virtual machine information to the auxiliary device D1, and the auxiliary device D1 starts dirty page capturing and reporting; and after migration is finished, the vDPA driver cancels migrated virtual machine information and releases resources. According to the method, dirty page capturing and reporting are achieved through hardware, and performance loss of a pure software scheme is avoided; hardware only needs to configure a report queue, so that the hardware design complexity is reduced; independent management of dirty pages of multiple virtual machines is realized through a mapping table, and simultaneous thermal migration of the multiple virtual machines is supported; meanwhile, an exception handling mechanism is introduced, and reliability is improved. According to the method, the thermal migration performance, the hardware complexity and the resource consumption are considered, and the method is suitable for various vDPA virtual machine migration scenes.

The invention discloses a data redistribution method, device and equipment for a distributed memory database and a medium, and belongs to the field of data migration. The method comprises the steps that expansion nodes are added to the distributed memory database, and data balance processing is conducted on the distributed memory database; screening target migration data from the to-be-migrated data according to the transmission time consumption calculated in real time; and performing dynamic migration processing according to the target migration data. According to the method, the data volume of each migration is determined through the predetermined acceptable service pause duration, the data can be divided into smaller data which can be flexibly split for transmission, and the granularity of the data is refined; dynamic adjustment is carried out according to the real-time migration state, resource competition with foreground transactions is reduced, resource waste is avoided, and the resource utilization rate is increased.

The invention discloses a virtual machine live migration method and device and electronic equipment. The method comprises the steps that load data of a physical host is obtained, and the physical host is used for bearing a to-be-migrated virtual machine; a prediction model is adopted to predict the load data, a prediction result is obtained, the prediction model is obtained based on historical load data training, and the prediction result is used for quantitatively representing the load fluctuation trend of the physical host and the to-be-migrated virtual machine in the future time period; adjusting a migration triggering threshold according to the prediction result to obtain a target migration triggering threshold which is at least used for judging whether to migrate the virtual machine to be migrated or not; and determining a target physical host from the physical hosts according to the target migration trigger threshold, and thermally migrating the virtual machine to be migrated to the target physical host. The technical problems that the resource utilization rate is low and load balancing cannot be achieved due to the fact that the thermal migration technology adopted in the related technology depends on a static threshold value are solved.

The invention provides a containerized edge service real-time migration method, device and system, and the method comprises the steps: issuing a file migration request when detecting that a user is leaving a communication range of a source node, so as to obtain a to-be-migrated hierarchical file in the source node, a hierarchical file in a warehouse of a target server, and a hierarchical file in a target node; a file migration strategy is generated through file comparison, so that the source server completes file and data migration to the target server, and the target server completes file and data migration to the target node; the source node is controlled to send container related data to the target node, so that the target node completes the Docker daemon process reloading and migration container recovery process according to the container related data and migrated files and data; the migration efficiency is improved by minimizing the container FS data volume needing to be transmitted, and the dynamic and delay-sensitive edge network requirements are met.

The invention provides a virtual machine live migration method, electronic equipment, a storage medium and a program product, and the method comprises the steps: in response to a live migration request for a virtual machine, determining a minimum dirty page generation interval corresponding to the transmission speed of live migration; in each round of synchronous operation implemented according to the live migration request, a write memory management strategy is adopted to manage the write memory operation of the round, so that the dirty page generation interval corresponding to the write memory operation of the first part is allowed to be smaller than the minimum dirty page generation interval; the dirty page generation interval corresponding to the memory writing operation of the second part is limited to be not smaller than the minimum dirty page generation interval; and gradually strengthening the limitation of the write memory management strategy on dirty pages so as to gradually reduce the dirty pages generated by each round at the interval smaller than the minimum dirty page generation interval.

Provided herein are various enhancements for low downtime migration of virtualized software services across different instantiations, which may include real-time migration over different cloud / server providers and platforms, physical locations, network locations, and across different network elements. Examples herein include handling of migration of data and state for virtualized software services, migration of ingress and egress traffic for the software services, and migration of other various operations aspects applicable to virtualized software services. In many instances, a client node retains the same network addressing used to reach the virtualized software services even as the virtualized software services move to different network locations and physical locations.

The present application relates to the technical field of computer resource management, in particular to a device dynamic running state analysis method and system for multi-task scenarios, comprising: capturing fine-grained resource fluctuation data under multi-task concurrency through a hardware abstraction layer, and constructing a hardware resource monitoring matrix accordingly; inputting the hardware resource monitoring matrix into a preset dynamic weight distribution model to evaluate hardware real-time loss and performance redundancy, and generating a hardware health degree image; dynamically adjusting resource allocation parameters of the current environment according to the image, wherein the parameters include cache mapping strategies and memory bandwidth allocation ratios; determining whether the load data in the hardware resource monitoring matrix reaches a preset bottleneck threshold, and if so, triggering a cross-core resource live migration strategy based on the adjusted parameters to realize smooth migration of task flows among heterogeneous computing cores. The present application realizes hardware state perception and resource parameter closed-loop adjustment, effectively solves multi-task conflicts, and improves execution efficiency.

A smart memory module includes at least one memory device connected to at least one channel, a controller configured to control the at least one memory device, and a host interface circuit configured to perform peer-to-peer (P2P) communication with an external device, and to receive, from a host device, a live migration request. The controller is configured to perform, in response to the live migration request, a migration operation of transmitting buffer data to a target device through the P2P communication under a buffer-full condition.

The invention provides an accelerator resource scheduling method, device and equipment and a readable storage medium, and the method comprises the steps: dividing a server equipped with a first type of instance into a first type of server and a second type of server; the first class instance is an instance obtained based on virtualization of a target class physical accelerator of the server; only first-class instances supporting thermal migration are deployed on the first-class servers; first-class instances which do not support thermal migration are deployed on the second-class servers; executing a live migration operation of the first type of instances for at least one server in the first type of servers and at least one server in the second type of servers; the thermal migration operation comprises the step of thermally migrating all the first-class instances deployed on one server in the first-class servers to one server in the second-class servers. According to the scheme, the problem that a large amount of invalid power consumption exists in the use scheme of the virtual accelerator in the prior art is solved.

The invention relates to the technical field of cloud computing containers, and provides a container thermal migration method based on memory snapshot difference compression, which comprises the following steps: in a normal operation stage of a container, initiating pre-migration preparation through a CRIU framework, continuously capturing dirty pages marked by a copy-on-write mechanism in a fixed period to form a difference page set, and storing the difference page set in a database; calculating the access popularity of each dirty page; dividing dirty pages of the difference page set into hot pages, warm pages and cold pages according to access popularity, and compressing the hot pages, the warm pages and the cold pages by adopting a self-adaptive compression strategy; constructing a three-level priority sending queue at a source node, and entering a network stack according to a priority sequence of a hot page, a warm page and a cold page; and when a convergence condition is met, suspending the container, only transmitting the last group of hot pages and necessary warm pages, and decompressing and rearranging memory pages at a target node according to a serial number to complete container recovery. According to the method, online container migration with high compression ratio, low CPU overhead, short downtime and high migration success rate is realized.

The invention discloses a cloud computing platform data storage method based on big data analysis, and relates to the technical field of cloud computing data storage. The technical problems that according to a traditional cloud computing storage system, resource configuration is homogenized, hot data access delay is too high, cost is wasted due to the fact that cold data occupies high-performance resources, a data popularity dynamic sensing and self-adaptive scheduling mechanism is lacked, and load distribution of storage nodes is unbalanced are solved. Compared with a traditional cloud computing unified storage mode, the method has the advantages that a whole-process technical system of storage resource hierarchical division, big data access frequency analysis, dynamic hierarchical storage, real-time migration scheduling and load balancing calibration is constructed; low-time-delay high-speed access of high-frequency hot spot data, performance and cost balance of medium-frequency temperature spot data and low-cost storage of low-frequency cold spot data are achieved, and storage resources are always accurately matched with data popularity through big data real-time analysis and a self-adaptive scheduling mechanism.

The present invention relates to a multi-level resource pool intelligent scheduling method for an urban rail cloud platform, and a device, which are applied to a rail transit service system. The method comprises: on the basis of a CPU overcommit ratio, a memory overcommit ratio, and whether KSM is disabled, automatically defining resource pools of different levels by using an application system operating behavior model and an application health status analysis model; on the basis of the importance and characteristics of each service module, a virtual machine live migration capability, and a current time period, using the application health status analysis model and an application peak operation time analysis model to respectively schedule the service modules to resource pools of different levels; and receiving system operation condition feedback data, and, on the basis of the feedback data, optimizing the application system operating behavior model and the application health status analysis model. Compared with the prior art, the present invention reduces memory resource requirements and improves effective memory utilization while ensuring that allocated virtual machines can meet actual system operation requirements.