53 results about "Static dispatch" patented technology

The invention relates to the technical field of dispatching automation, and discloses a dispatching automation system application state management method which comprises the following steps: dynamic task state management: monitoring dynamic state indexes of various computing tasks in real time; according to different characteristics of task types, making differentiated priority management strategies; the task priority is dynamically adjusted, and it is ensured that key tasks are preferentially and efficiently executed; dynamic resource state management: continuously monitoring dynamic state indexes of various computing resources, wherein the dynamic state indexes comprise utilization rates and load conditions; dynamically adjusting a resource allocation scheme according to the resource state; dynamically optimizing resource allocation to ensure that the overall resource utilization rate of the system is continuously improved; and optimizing a self-adaptive scheduling strategy: introducing a self-adaptive scheduling algorithm based on reinforcement learning. According to the application state management method of the dispatching automation system, dynamic state management is adopted, a traditional static dispatching mode is abandoned, and the method can better adapt to a complex and changeable computing environment.

The invention relates to the technical field of simulation scheduling combining static scheduling and centralized scheduling, and discloses a simulation scheduling method and system combining static scheduling and centralized scheduling. According to the simulation scheduling method and system combining the static scheduling and the centralized scheduling, pre-allocation and resource planning of tasks are carried out through the static scheduling, and the execution efficiency of periodic tasks is ensured. In combination with centralized scheduling, resource allocation is adjusted in real time in the simulation operation process, the phenomena of resource idleness and overload are reduced to the maximum extent, and dynamic optimization of resources is achieved. The execution sequence of key tasks is locked in advance by static scheduling, and the time constraint of deterministic tasks is ensured. The centralized scheduling can perform global coordination on burst tasks, adjust task priorities in real time and ensure timely response of the burst tasks, so that the real-time response capability of the simulation system is improved.

The invention relates to the technical field of industrial control, in particular to a TSN-based industrial equipment cooperative control method and system and a readable storage medium. The method comprises the following steps that: a switch acquires the flow of a TSN network from a preset detection starting moment t1 to a current moment tK; constructing an optimization objective function of the static scheduling strategy; obtaining a flow priority, a distribution time slot and a bandwidth resource which enable the optimization objective function to reach the minimum; and constructing a dynamic scheduling model based on an intelligent scheduling algorithm of an ant colony optimization algorithm so as to obtain adjusted flow priority, allocation time slot and bandwidth resources. According to the invention, a static traffic scheduling strategy is adopted to ensure that key control traffic can be transmitted preferentially; the network state is analyzed in real time by adopting an intelligent flow dynamic scheduling algorithm in combination with an ant colony optimization algorithm, and network resource allocation is optimized; the problem that traditional flow scheduling cannot adapt to network changes in real time is effectively solved.

The invention relates to the technical field of construction resource scheduling, in particular to a water conservancy construction equipment scheduling method and system, and the method comprises the following steps: obtaining on-site point cloud and soil data to construct an environmental resistance field; calculating a dynamic work efficiency matrix by combining the equipment power parameters and the resistance field; generating an initial time sequence chain based on the work efficiency matrix, and calculating an overlapping volume of a three-dimensional space envelope body of the equipment; if there is overlap, the job time is adjusted according to the priority to generate a conflict-free scheduling instruction set. According to the method, the rated work efficiency parameters of different machine types in a specific operation area are corrected in real time by constructing the equipment passing resistance model fusing the terrain gradient and the soil moisture content, the problem that static scheduling cannot adapt to environmental changes is solved, and meanwhile space-time conflict detection logic based on the three-dimensional operation envelope surface is introduced; and when it is recognized that the multi-machine moving tracks are overlapped, avoiding or peak shifting instructions with priorities are automatically generated, and conflict-free collaborative operation of the equipment cluster in a complex water conservancy scene is achieved.

The invention relates to the technical field of industrial control, and discloses an industrial control system task scheduling method and system based on dynamic priority. The method comprises the following steps: acquiring equipment inclination angle data and performing data cleaning; analyzing a state change trend according to the cleaned data, extracting dynamic features, and mapping the feature values into risk levels by applying a risk assessment rule base; if the risk level exceeds a threshold value, determining a task emergency degree in combination with the risk level and equipment importance, and generating a task redistribution instruction; a task queue is adjusted according to the instruction and the emergency degree, and an adjusted task scheduling sequence is obtained after it is verified that resources are sufficient; and the queue state is continuously monitored to realize closed-loop adjustment. According to the method, by establishing closed-loop association of physical risk perception and task scheduling, the problem that a traditional static scheduling strategy cannot cope with dynamic changes of equipment is solved, and the safety and the operation efficiency of the industrial control system are remarkably improved.

The embodiment of the invention provides an embedded operation method and system based on preemptive multi-task scheduling, and belongs to the technical field of multi-task scheduling. The method comprises the following steps: initializing a global task priority group, a start-stop bit field group and an execution quality feedback table, and configuring parameters of a time base interrupt source; loading task parameters, and generating a task configuration table; driving each task cycle counter to accumulate through the time base interrupt source, and when the current accumulated value of the cycle counter is matched with the cycle parameter in the task configuration table and the start-stop bit field group is started, generating a ready mark graph; updating the global task priority group, determining a to-be-executed task, and completing task scheduling; and executing the to-be-executed task, calculating a task priority compensation value, and adjusting the priority value of the corresponding task in the global task priority group in the next period based on the task priority compensation value. According to the method, the defect of static scheduling accumulative errors is overcome through a dynamic priority compensation mechanism.

The invention provides an http request task queue concurrent processing method based on a UE engine, and relates to the technical field of network communication methods, and the method comprises the steps of request receiving, data acquisition, model construction, load prediction, request enqueue, task scheduling, task distribution, request response and the like. According to the method, the system load change can be accurately predicted, so that the processing of the request can be dynamically adjusted according to the actual state of the system load, and the instability caused by static scheduling in a traditional method is reduced.

The invention relates to a context delay switching method and system based on an embedded operating system, and belongs to the technical field of embedded operating systems. According to the method, a dependency graph is constructed, a dependency state is analyzed, judgment and adjustment are carried out, conflict-free tasks are screened, sorting is carried out, and switching is executed; according to the method, the limitation that traditional static scheduling cannot adapt to task dependency relationship changes during operation is solved by constructing the dependency relationship graph and collecting and analyzing the dependency strength and the execution state between the tasks in real time, and in a complex embedded scene, the correlation degree between the tasks is quantified through a dependency strength formula, and the real-time state analysis is combined, so that the real-time state analysis is realized. The task switching sequence can be dynamically adjusted, it is ensured that key tasks are executed according to the dependency sequence, execution blocking or data errors caused by the fact that front tasks are not completed are avoided, switching of the tasks which do not meet dependency can be flexibly suspended, conflict-free tasks are executed, and therefore the real-time response capacity and the operation stability are improved.

The invention belongs to the technical field of task scheduling of a storage system, and discloses a user-mode-oriented storage task self-adaptive scheduling method and system, and a more efficient task processing framework is realized by replacing an original kernel thread-based storage task scheduling scheme with a user-mode coroutine scheduling mechanism. The multi-level priority queues are directly managed in task scheduling, and CPU core binding configuration is carried out, so that the switching delay of a user mode / kernel mode is reduced, and the task execution controllability is improved. A dual-threshold self-adaptive scheduling strategy switching technology is introduced, and a greedy scheduler and a reinforcement learning scheduler are combined, so that the problem of adaptability of a static scheduling strategy in a dynamic load environment is relieved, performance loss caused by scheduling strategy solidification is avoided, and the self-adaptive capability and service quality guarantee of a system under a complex load are improved. Compared with an existing task scheduling method based on a kernel thread, the task scheduling method has the advantages that the overall performance and the resource utilization rate of a storage system can be remarkably improved while the task execution efficiency and the SLA requirement are guaranteed.

The invention discloses a resource scheduling system of a prefabricated data center, which relates to the related field of control and regulation systems, and comprises the following steps: acquiring configuration topology information of a plurality of prefabricated units by interacting a target scene; initial static scheduling decision making is carried out according to real-time task requirements, and an initial resource scheduling strategy set is generated; and analyzing the configuration topology information, obtaining connectivity characteristics of the plurality of prefabricated units, and obtaining real-time resource state information. And carrying out iterative decision optimization on the initial resource scheduling strategy set to obtain an optimized scheduling strategy set. And selecting the optimal first N optimal scheduling strategies from the optimal scheduling strategy set, outputting the optimal first N optimal scheduling strategies as a resource scheduling plan set, and performing resource scheduling control of the target prefabricated data center according to the resource scheduling plan set. The technical problems that in the prior art, resource scheduling of a prefabricated data center is poor in scheduling accuracy, an optimal resource scheduling strategy is difficult to obtain in a changeable environment, and consequently the resource utilization rate and the task execution efficiency are difficult to improve are solved.

This application provides a HARQ-ACK information feedback method and apparatus. The DCI sent by the network device to the terminal device activates semi-static scheduling and also dynamically schedules downlink data. The timing offset value from the PDSCH to the HARQ feedback indicated by the DCI can simultaneously indicate the time-domain position of the PUCCH carrying the HARQ-ACK information corresponding to the semi-static scheduled data, as well as the time-domain position of the PUCCH carrying the HARQ-ACK information corresponding to the aforementioned downlink data. Through this scheme, the time-domain position of the PUCCH carrying the HARQ-ACK information corresponding to the semi-static scheduled data determined by the terminal device is valid, thereby ensuring timely feedback of the HARQ-ACK information corresponding to the semi-static scheduled data and guaranteeing the transmission performance of the semi-static scheduled data.

The application provides a container pipeline scheduling management method and system based on an ARM+DSP heterogeneous multi-core processor and a medium, and the method comprises the following steps: configuring scheduling related attributes of a container, wherein the scheduling related attributes of the container comprise a container duration time DT and a container interval time IT, and the container comprises an ARM container and a DSP container; according to the scheduling related attributes of the container and a pre-established container linked list, a next container to be run is selected according to a time window static scheduling strategy, and the container pipeline is controlled to run. Compared with the prior art, the application realizes independent running of various containers under the premise that the containers are sequentially arranged, do not affect each other and can interact with each other under the condition of sharing physical resources.

This invention discloses a production data-driven intelligent scheduling method and system for mechanical equipment, relating to the technical field of equipment scheduling. The method includes: constructing a set of equipment operating characteristics; comprehensively evaluating the current load rate, processing capacity, and failure risk of each piece of mechanical equipment; constructing a scheduling objective function using equipment survivability scores as scheduling decision weight parameters; performing task allocation and processing path optimization calculations to generate an intelligent scheduling scheme for the mechanical equipment; and monitoring the scheduling execution process in real time to adaptively adjust the production scheduling scheme. This invention solves the technical problems in existing technologies where static scheduling cannot adapt to real-time changes in equipment status and lacks a dynamic risk feedback mechanism, leading to equipment overload, unplanned downtime, and cascading production delays during scheduling scheme execution. It achieves the technical effects of improving the production scheduling system's adaptability to dynamic equipment operating conditions, reducing the risk of unplanned downtime, and optimizing equipment utilization and production delivery reliability.

The embodiment of the invention discloses an independent task dynamic scheduling method based on cloud computing. The independent task dynamic scheduling method comprises the steps that a user submits a task to a cloud computing system according to a standard; reading the task by using a sorter; sequencing and updating the read tasks in the sequencer, and updating to obtain a task list; obtaining the first m tasks in the task list to a scheduler, and reordering the first m tasks; and establishing a host list, obtaining a local task sub-list and the host column and table through the scheduler, and allocating tasks of the local task sub-list. By adopting the method, the important problem that the real-time performance of task scheduling is ignored due to the fact that excessive energy is put on execution efficiency and load balance in a static scheduling algorithm can be corrected, and the characteristics of each independent task and the working state of a host processor are also fully considered.

This invention relates to the field of construction resource scheduling technology, specifically to a method and system for scheduling water conservancy construction equipment. The method includes the following steps: acquiring site point cloud and soil data to construct an environmental resistance field; calculating a dynamic efficiency matrix by combining equipment dynamic parameters and the resistance field; generating an initial time sequence chain based on the efficiency matrix and calculating the overlapping volume of the equipment's three-dimensional spatial envelope; if overlap exists, adjusting the operation time according to priority to generate a conflict-free scheduling instruction set. In this invention, by constructing an equipment passage resistance model that integrates terrain slope and soil moisture content, the rated efficiency parameters of different machine models in specific operating areas are corrected in real time, solving the problem that static scheduling cannot adapt to environmental changes. Simultaneously, a spatiotemporal conflict detection logic based on the three-dimensional operating envelope surface is introduced, automatically generating priority avoidance or staggered operation instructions when overlapping of multiple machine operating trajectories is detected, thus realizing conflict-free collaborative operation of equipment clusters in complex water conservancy scenarios.

The present invention relates to the field of industrial control technology, and in particular to a TSN-based industrial equipment collaborative control method, system, and readable storage medium. The method comprises the following steps: a switch obtains the TSN network from a preset start detection time t1 to the current time t K The present invention adopts a static traffic scheduling strategy to ensure that critical control traffic is transmitted first; it uses an intelligent traffic dynamic scheduling algorithm, combined with the ant colony optimization algorithm, to analyze network status in real time and optimize network resource allocation. This effectively solves the problem that traditional traffic scheduling cannot adapt to network changes in real time.

The application relates to the technical field of simulation scheduling combining static scheduling and centralized scheduling, and discloses a simulation scheduling method and system combining static scheduling and centralized scheduling, which comprises the following steps: the simulation scheduling method and system provided by the application perform pre-allocation of tasks and resource planning through static scheduling, so that the execution efficiency of periodic tasks is ensured; in combination with centralized scheduling, resource allocation is adjusted in real time during simulation operation, the phenomena of resource idling and overloading are minimized, and dynamic optimization of resources is realized; the static scheduling locks the execution sequence of key tasks in advance, so that the time constraint of deterministic tasks is ensured; the centralized scheduling can globally coordinate burst tasks, adjust the task priority in real time, ensure timely response of emergency tasks, and thus the real-time reaction capability of the simulation system is improved.

The embodiment of the invention provides a dynamic resource scheduling method, electronic equipment and a storage medium, and relates to the field of resource scheduling. The method comprises the following steps: an upper computer obtains a source event triggering condition, and determines a triggering source and a source event priority in combination with a preset event priority table; when the trigger source is a lower computer, a starting signal is received, and whether the source event is executed or not is judged according to current task state information, the priority of the source event and a preset table; if execution is determined, sending a starting feedback signal to obtain a lower computer state message, converting the lower computer state message, and inputting the converted lower computer state message into the large language model agent to obtain a first instruction and an auditing result; if the verification is passed, the instruction is converted into a message to be issued, and after the lower computer permission decision is passed and executed, a first completion signal is received. The method is used for improving real-time performance, adaptability and reliability of resource scheduling, and avoiding insufficient system stability caused by the fact that static scheduling cannot respond to sudden demands or resource distribution is unbalanced.

The present application belongs to the field of industrial automation control and intelligent manufacturing technology, and relates to a manufacturing execution dynamic scheduling method and system based on multi-agent cooperation. The present application solves the problems that the traditional centralized static scheduling cannot adapt to the dynamic changes of the workshop, the decoupling of processing and logistics, the slow response of equipment failure, etc. The present application analyzes the production task into manufacturing intent nodes with front and rear dependencies. The device agent generates a bidding certificate based on the transient physical data of the underlying programmable logic controller and numerical control system. The order agent filters the optimal device to establish a point-to-point execution contract accordingly. During the processing, the physical completion timestamp of the workpiece is dynamically deduced, and the pre-logistics generates a carrying path with a time window, realizing the space-time synchronization of processing and logistics. When the equipment fails, the system locks the processing completion degree, initiates a relay processing request between adjacent devices and synchronously changes the logistics path, generating a local physical self-healing state, and improving the production robustness.

The invention relates to the technical field of wireless communication, and discloses a semi-persistent scheduling method, base station equipment and user equipment.The semi-persistent scheduling method comprises the steps that configuration information of semi-persistent scheduling parameters is sent to user equipment UE, so that the UE conducts semi-persistent scheduling data transmission based on the configuration information; and performing semi-static scheduling data transmission based on the configuration information of the semi-static scheduling parameters. According to the method provided by the embodiment of the invention, the low-delay requirement of URLLC can be met, so that the existing semi-static scheduling transmission mechanism can support higher low-delay requirements, multiple semi-static scheduling configurations are introduced at the same time, and different time-frequency resources are allocated for each semi-static scheduling configuration, so that multiple services can be supported at the same time.

The invention relates to the technical field of information, in particular to a distributed workflow load parallel scheduling method and device based on Monte Carlo. The method comprises the following steps: sampling execution time by using a Monte Carlo method; multiple scheduling schemes are generated based on static scheduling CPOP, after a critical path is obtained by using a CPOP algorithm, the search time is shortened by using a Monte Carlo search tree, and the scheduling schemes with long time are screened out; and sampling the execution time, calculating the minimum scheduling time obtained according to different scheduling schemes, and selecting the scheduling scheme with the minimum average value of the minimum scheduling time. The invention aims to break through the limitation of the traditional static scheduling method in dealing with the uncertainty of the task execution time, and more accurately grasp the randomness characteristic of the task execution time by means of analogue simulation and sampling analysis so as to realize a better scheduling strategy and overall performance optimization in a decision making process.

The present disclosure relates to a transmission method, a transmission device and a storage medium. The transmission method includes: in response to the period of the scheduled transmission block TB being a non-integer multiple of the semi-static scheduling period, determining the symbol position of the TB transmission. The present disclosure solves the problem that when the semi-static scheduling under a non-integer multiple period determines the symbol position of the scheduled TB, the starting symbol of the transmission TB does not match the starting symbol of the non-integer multiple of the semi-static scheduling period, thereby meeting the low latency requirement of data transmission.

The present application discloses a semi-static scheduling method and device, which is used to solve the problem in the related art that the semi-static scheduling period does not match the actual data transmission demand, resulting in waste of wireless resources. The method includes: the network device determines the configuration of the semi-static scheduling to be activated from multiple semi-static scheduling configurations pre-allocated to the terminal according to the time interval of at least two requests, wherein the configuration of the semi-static scheduling to be activated is different from the configuration of the semi-static scheduling currently adopted by the network device and the terminal; multiple requests are used to instruct the network device to update the data to be sent or multiple requests are used to instruct the network device to allocate time-frequency resources; the time interval is the time interval between any two requests that are adjacent in the time domain among the multiple requests, and the time interval between any two requests that are adjacent in the time domain among the multiple requests is the same; the network device instructs the terminal to activate the configuration of the semi-static scheduling to be activated.

The invention provides an A664 terminal message delay upper bound analysis method based on static scheduling, and the method comprises the steps: an analysis end system data transmission stage 1: obtaining the maximum delay of a message in a sending end system traffic shaping stage; in the second data transmission stage of the analysis end system, the maximum delay of VL multiplexing scheduling of the message in the sending end system is obtained; the maximum delay of a data frame of the sending end system is obtained by combining the maximum delay of the flow shaping stage of the sending end system and the maximum delay of VL multiplexing scheduling of the sending end system; according to the method, the physical architecture of the A664 terminal system is analyzed, and the frame delay generated by traffic shaping of the A664 terminal system and the jitter upper bound generated by static scheduling of an output port are theoretically calculated, so that the accuracy of the network message delay upper bound in the terminal system calculated by the algorithm is ensured.

Computer-implemented method for generating a parallelized program for a multiprocessor system mounted in a vehicle on-board device (400), comprising: Dividing a sequential program into multiple macro-tasks according to a predetermined procedure using a parallelization compiler running on a computer, which controls an embedded system, wherein the sequential program is executed by a single-processor system; Generating, using the compiler, a macroflow graph based on an analysis of control dependencies and data dependencies between the macro tasks; Specify, by means of the compiler, based on the control dependency specified in the macroflow graph, at least one pair consisting of a start-end task and a finish-end task, wherein the start-end task is a macro task having a conditional branch, and the finish-end task is a macro task that is the first macro task executed common to all of several series of macro tasks executed sequentially from the start-end task as a starting point, wherein the specification includes: analyzing all possible execution paths from the start-end task and identifying the first macro task executed common to all of the series of macro tasks as the finish-end task; Merge, using the compiler, (i) the initiating end task, (ii) the termination end task, and (iii) all macro tasks that are executed after the start-up end-task and before the finish-up end-task into a block task to hide the conditional branch of the start-up end-task in the block task, wherein the block task is designed such that, from the perspective of tasks outside the block task, the conditional branch in the start-up end-task is hidden from tasks outside the block task, and the merging is performed in such a way as to eliminate control dependencies between block tasks, thereby enabling static scheduling; Extracting, by means of the compiler, based on the data dependencies between the macro-tasks, including the block-tasks after fusion, from parallel-executable macro-tasks that can be executed in parallel by multiple processor units included in the multiprocessor system mounted in the vehicle on-board device (400), wherein the block-tasks have no control dependencies among themselves after fusion and the extraction is performed based on data dependencies between the block-tasks and remaining macro-tasks, so that static scheduling between the block-tasks is possible; Execution, using the compiler, a static schedule that assigns the parallel-executable macro tasks to the processor units, thereby executing the parallel-executable macro tasks in parallel by the multiple processor units; and Generating, by means of the compiler, a parallelized program to be executed by the multiprocessor system mounted in the vehicle on-board device (400), based on a result of the static scheduling.

The invention discloses a Pod migration method under a Kubernetes cluster architecture system, which comprises the following steps of: 1, continuously monitoring the resource imbalance degree of a cluster, judging whether the resource imbalance degree exceeds a threshold value or not, and if so, executing a step 2; if not, continuing monitoring; 2, finding out nodes with serious resource imbalance, finding out Pod with the maximum influence on the resource imbalance in the nodes, and determining that the Pod is the Pod to be migrated; 3, state information of all nodes in the current cluster is collected, a Pod migration program is called for the to-be-migrated Pod, and finally a new target node is obtained; and 4, firstly creating the Pod on the new target node, and then deleting the original Pod until the Pod is successfully migrated to the new target node and runs. According to the invention, the limitation problem of Kubernetes static scheduling is solved, and the load balance of cluster resources and the reliability of services are ensured.

The present invention provides a static scheduling method, device, equipment and medium for inter-city multiple round-trip vehicles integrating private car service and carpooling service, and relates to the technical field of inter-city static carpooling scheduling. The method comprises: S1, obtaining passengers' scheduled travel data and vehicle set. S2, based on the scheduled travel data and vehicle set, constructing a static scheduling model with maximizing the profit of ordinary carpooling and maximizing the profit of private car service as the optimization goal. S3, according to the static scheduling model, using a sequential line construction algorithm to generate an initial feasible solution. S4, according to the static scheduling model, setting a neighborhood operator based on a one-way trip to perform disturbance. S5, according to the static scheduling model, setting a local search operator based on private car service passengers to improve disturbance. S6, using a variable neighborhood search algorithm to solve according to the static scheduling model, the initial feasible solution, the neighborhood operator and the local search operator to obtain the optimal solution. Among them, the optimal solution is a static scheduling plan.

The invention provides a key service scheduling method and system for a service oriented architecture (SOA), and relates to the technical field of automobile SOA service, and the method comprises the steps: introducing unified AP / CP cross-platform priority mapping, special resource allocation and an elastic resource pool mechanism, and combining the real-time monitoring of a high-key service execution state and dynamic resource preemption. The problems that in traditional static scheduling, high-key services are prone to being blocked by low-key services, the resource utilization rate is low, and cross-platform scheduling is inconsistent are effectively solved. According to the method, idle computing resources are fully utilized to process QM-level low-key services while ensuring that ASIL-B and above-level safety key services always meet strict real-time requirements, and the resources are quickly recycled at key moments to guarantee high-quality tasks; therefore, collaborative optimization of scheduling flexibility, system reliability and hardware resource efficiency is realized under the function security constraint.

The application discloses an OpenMP static scheduling method for random loop load balancing. After the configuration of OMPi compiler in the linux environment, the random loop part in the calculation program is isolated. Then the execution time in each loop iteration is obtained by using the idea of iterative compilation, and the execution time is used to represent the load contained in the random loop. Then according to the obtained load information and the actual running thread number required, the load of each iteration in the random loop, the total load and the average load are obtained, the start and end indexes of each thread distribution to the iteration block are calculated, and the start and end index values are respectively stored in the corresponding pointers. Finally, the code about OpenMP scheduling in the compiler is changed to realize the scheduling strategy. The application overcomes the shortcoming of additional time overhead caused by pre-running, has no scheduling overhead, realizes the load balancing and speeds up the execution efficiency of the program.

Methods, apparatuses, and systems are disclosed for tracking an actual number of semi-persistent scheduling (SPS) transmissions performed to reduce signaling overhead. In one example aspect, a method of wireless communication includes transmitting, by a base station, a configuration of SPS transmissions to a mobile device. The method also includes transmitting, by the base station, an indication of actual SPS transmissions performed based on the configuration to the mobile device.