324 results about "Lower priority" patented technology

The invention discloses a high-efficiency computer software system resource scheduling method, system and device and a medium, and the method comprises the steps: deploying a hardware counter in an operating system, and monitoring the CPU utilization rate, memory occupation, disk I / O, network bandwidth, the use condition of data aggregation system resources and the resource demand of each process or thread in real time; based on monitoring data, analyzing a current resource supply and demand state by adopting an advanced algorithm, and predicting a future resource demand trend; according to an analysis result, a resource allocation strategy is dynamically adjusted, it is ensured that a high-priority task obtains needed resources in time, and meanwhile fairness of a low-priority task is considered; data feedback after scheduling execution is collected, a scheduling algorithm is continuously optimized, and the scheduling efficiency is improved; the system, the equipment and the medium are used for realizing the high-efficiency computer software system resource scheduling method. The problems that an existing computer system is low in resource utilization rate, poor in key task stability and high in operation and maintenance cost are solved.

The invention relates to the technical field of electric power data analysis, and discloses a concentrator collection data analysis method and system based on big data, and the method comprises the steps: capturing a high-priority task in real time, and generating a concentrator collection task flow sequence arranged according to an initial scheduling sequence; performing cross-task dependency chain logic association tracking on the concentrator collection task flow sequence, and constructing a multi-dimensional scheduling feature vector reflecting the importance gradient of the task; based on the multi-dimensional scheduling feature vector, a hierarchical priority aggregation algorithm is utilized to extract a preemption evolution track of a high-priority task to the bandwidth and the acquisition time slot, and potential scheduling error sequence candidate tasks are detected; performing priority grading delimitation on the scheduling error sequence candidate tasks and the associated low-priority task interval, and constructing a local task logic graph with a priority weight gradient; and performing dynamic intervention judgment on the scheduling evolution path based on the local task logic graph. The method has the advantage of improving the overall scheduling efficiency.

A system comprising security devices and a computing device. The security devices may each be configured to detect an event in response to video frames and audio and communicate the video frames, the audio and a notification of the event. The computing device may be configured to execute one or more steps, the steps comprising performing a classification of the notifications of the events into a plurality of event levels and displaying a list of the notifications of the events according to the classification. Each of the plurality of event levels determined to be high priority events are added to a top of the list as the high priority events are detected. Each of the plurality of event levels determined to be a lower priority than the high priority events are added to the list below the high priority events as the events with the lower priority are detected.

The invention discloses a bidirectional feedback-driven large-model dynamic memory regulation and control system and method, and the system comprises a router, a generator, an actuator and a memory system, and is optimized through four core mechanisms: 1) a dynamic grading mechanism: dividing memory grades based on timeliness, accuracy, repeatability and context consistency by using fuzzy comprehensive evaluation; 2) a forgetting mechanism: performing knowledge distillation compression on the low-priority memory by adopting TinyBERT, and clearing redundant data; 3) an enhancement mechanism: combining similar task memories through LLM to generate an optimized narrative text; and 4) extracting a mechanism, and accurately retrieving knowledge in combination with a potential semantic index and retrieval enhancement generation technology, realizing closed-loop regulation and control of task allocation, generation, execution and memory enhancement through bidirectional interaction of actuator feedback and a memory system, remarkably improving storage efficiency, task solving speed and long-term self-adaptive ability, and greatly improving the system performance. The method is suitable for complex scene optimization of a large language model.

The invention discloses a server fault processing method and device and a medium, and relates to the technical field of computers. And the server fault analysis problem is converted to obtain vector information, and the vector information is input to the pre-training model for reasoning analysis, so that accurate fault positioning is realized, and the search accuracy of fault analysis is improved. The fault analysis problem comprises a potential fault analysis problem, so that unknown faults are predicted and reasoned, and the fault processing delay is reduced. In inference analysis of a pre-training model, corresponding target inference strategies are matched based on priorities of different fault modes and association degrees of multiple faults instead of being directly processed one by one according to the priorities of the faults, and the association degrees of the multiple faults and whether the corresponding inference strategies are conflicted or not are concerned firstly; according to the method, the situation that secondary faults are caused by contradictory occurrence of heavy faults under the condition that the faults with low priorities are processed in a delayed mode is avoided, the fault maintenance progress is further accelerated, and the reliability of the server is improved.

The invention discloses a priority scheduling method and system for an on-orbit data processing task. The method comprises the following steps: constructing a DAG model, decomposing a macroscopic task into subtasks, defining a subtask dependency relationship, and endowing a subtask node with a priority attribute; setting or dynamically adjusting the priorities of the sub-tasks according to task service types, processing delay requirements or external instructions; maintaining a schedulable queue containing subtasks which have completed precursor tasks and meet scheduling conditions; calculating task scheduling priority indexes based on the queue, sorting, and selecting optimal calculation resource allocation; the priority is dynamically adjusted according to task waiting time or an external instruction during execution, and hunger of low-priority tasks is avoided; the multiple processing units execute the high-priority tasks in parallel according to needs; and after the task is completed, updating a subsequent node dependency state, and adding a new schedulable task cycle. According to the method, high-priority task resource allocation can be guaranteed preferentially, low-priority task hunger is avoided, and the overall throughput rate of the system and the self-adaptive capacity to on-orbit diversified tasks are remarkably improved.

A user equipment maps a high priority hybrid automatic repeat request-acknowledgment / negative acknowledgment (HARQ-ACK / NACK) information to one or more resource elements (REs), and maps one or more of a low priority HARQ-ACK / NACK information, channel state information (CSI), or uplink-shared channel (UL-SCH) data to REs while rate matching around the mapped high priority HARQ-ACK / NACK REs. A network entity receives an uplink transmission, including high and low priority HARQ-ACK / NACK information, CSI, and UL-SCH data mapped to high and low priority HARQ-ACK / NACK REs, CSI REs, and UL-SCH REs, respectively. The low priority HARQ-ACK / NACK REs, the CSI REs, and the UL-SCH REs are rate matched around the high priority HARQ-ACK / N ACK REs. The network entity demaps and decodes the REs of the high and low priority HARQ-ACK / NACK, the CSI, and UL-SCH to obtain the high and low priority HARQ-ACK / NACK information, CSI, and UL-SCH data.

The invention discloses a CAN message priority dynamic arbitration method and system based on event triggering, and the method comprises the steps: obtaining a discrete sampling signal of a CAN node of an engineering vehicle and a state register value of a CAN controller, converting the discrete sampling signal into a working condition data sequence, and obtaining a bus load rate through the state register value; obtaining an event state sequence according to the working condition data sequence; all CAN messages to be sent are constructed into a message data record, and the message data record with event semantics and dynamic priority labels is obtained according to the protocol data unit and the event state sequence; and according to the bus load rate and the event state sequence, sending a message data record with event semantics and dynamic priority annotations by adopting a token bucket mechanism through a three-level priority queue linked with a three-state state machine. According to the invention, the security key message in the system can still be transmitted in time under high load, and the bandwidth occupation and delay jitter caused by the low-priority message are avoided at the same time.

The invention provides a multi-factor collaborative dynamic priority task scheduling method based on waiting time feedback, which is characterized by comprising the following steps of: initializing waiting time, task criticality and weight values of queue length, initializing a mixed task set and a task waiting queue, and initializing the task waiting queue into an empty set; entering a task waiting queue; updating the priorities of all tasks in the task waiting queue; sorting the tasks in the task waiting queue according to the priority; monitoring whether a new task arrives in real time; judging whether the newly arrived task meets a preemption condition or not; updating the historical average waiting time of the task; updating weight values of task waiting time and queue length; and judging whether all tasks in the mixed task set are scheduled. According to the method, long-term hunger of low-priority tasks is avoided, and the average waiting time of the tasks is shortened; the preemption threshold value is dynamically adjusted, and the context switching overhead is reduced; a dynamic weight mechanism is designed, and the self-adaptive capacity of the system is improved.

The invention discloses a coroutine scheduling method, device, system and equipment, a storage medium and a product, and relates to the technical field of task scheduling, a multi-priority queue group is used for storing a first coroutine task to be executed in a corresponding scheduling domain, and a storage module is used for storing a second coroutine task periodically executed in a corresponding scheduling domain; the execution cycle of the first coroutine task is smaller than that of the second coroutine task. And when the expired second coroutine task exists in the storage module, mounting the expired second coroutine task to the multi-priority queue group. The situation that the first coroutine task with the low priority cannot be executed due to the fact that the second coroutine task does not reach the execution time is effectively avoided. And the coroutine tasks are obtained and executed from the multi-priority queue group according to the priority sequence, so that the tasks with high priorities are ensured to preferentially obtain execution resources. According to the running state and the load state of each scheduling domain, task migration of each scheduling domain is carried out, and the resource utilization rate is optimized.

The invention is suitable for the field of business data scheduling, and provides a data-in-channel scheduling method and system adaptive to multiple business scenarios, and the method comprises the steps: collecting business feature data in real time, abstracting business departments participating in scheduling as game roles, and distributing resource demand attributes and game chip attributes for the game roles. And based on the task urgency degree coefficient, the resource utilization efficiency and the scene adaptation weight, constructing a bid calculation model to generate automatic bids, allocating exclusive resources to high-priority roles in combination with a resource allocation thermodynamic diagram, and scheduling low-priority roles as required through an elastic resource pool. The system dynamically monitors resource utilization rate and task indexes, evaluates bidding rationality and adjusts chip attributes. According to the method, roles are stimulated to compete efficiently through a game mechanism, resource allocation is optimized in combination with dynamic feedback, the problems that a traditional method is poor in adaptability and not public in allocation are solved, and the resource utilization efficiency and service continuity in a multi-service scene are remarkably improved.

Systems and methods for enhanced Physical Uplink Control Channel (PUCCH) power control when missing Uplink Control Information (UCI) of different priorities are provided. In some embodiments, a method performed by a User Equipment (UE) for determining a power adjustment includes determining a PUCCH power adjustment with respect to a PUCCH format and / or Transport Format (TF); wherein determining the PUCCH power adjustment is based on one or more out of: a UCI consists of UCI with same priority index or different priority indices; a number of high-priority and / or low-priority UCI bits; and a minimum of high-priority and low-priority UCI bits. In this way, PUCCH power is able to be properly adjusted when UCI consists of UCI with different priority index.

A system may receive a request to generate an object. A system may generate, based on the request, a first portion of a prompt associated with a first layer of a hierarchy and a second portion of the prompt associated with a second layer of the hierarchy, where the second layer has a lower priority than the first layer. A system may generate the object based in part on providing the portions of the prompt as input to a machine learning model, where the object is formatted according to an object format and is internally consistent. To generate the object the machine learning model does not violate instructions associated with a layer of the hierarchy based on instructions associated with a layer of the hierarchy having a relatively lower priority.

The invention discloses an access sequence determination method and device, a data reading method and device, equipment and a storage medium, and relates to the technical field of communication, and the method comprises the steps: caching a plurality of access requests when the access requests sent by a plurality of hosts for accessing the same slave are received; identifying the request type of each access request; selecting at least one target arbitration process from a plurality of arbitration processes according to the request type; executing at least one target arbitration process, arbitrating the hosts corresponding to the plurality of access requests, and determining an access sequence of each host to the slave; and sequentially sending the access requests to the slaves according to the access sequence. The request type of each access request is identified, multiple arbitration processes are provided, it is ensured that high-priority requests can be processed in time, meanwhile, it is prevented that low-priority requests cannot be responded for a long time, and the fairness of the system is improved. And the limitations of the traditional methods, such as priority starvation and non-uniform resource allocation, are overcome.

The invention provides a multi-task automatic mutual exclusion lock management middleware which realizes full-automatic lock management through intelligent resource classification, dynamic lock strategy matching and priority sensitive scheduling. The middleware is internally provided with a resource feature analysis algorithm, read-write features of resources such as hardware equipment and memory queues can be automatically recognized, and optimal lock mechanisms are allocated to different scenes in combination with a preset lock strategy library; a priority preemptive scheduling algorithm is originally created, high-priority tasks are allowed to break through the limitation of a lock waiting queue, and the real-time task response capability is guaranteed; and meanwhile, an annular deadlock detection module is integrated, and a low-priority lock occupation task is relieved through transaction rollback, so that circular waiting is relieved. A developer only needs to label task priority labels, zero manual lock coding can be achieved, and the lock conflict risk is reduced. The modules cooperate to achieve full-automatic lock management, lock conflict and deadlock risks are remarkably reduced on the premise that lock logic does not need to be coded manually, and the real-time performance and reliability of a multi-task system are remarkably improved.

Embodiments of the present application relate to a task scheduling method and apparatus, an electronic device and a storage medium, applied to a resource pool having multiple tenants, where a task queue corresponding to each tenant is configured with a minimum resource limit and a maximum resource limit, a difference between the maximum resource limit and the minimum resource limit is an elastic resource limit of the task queue, and the maximum resource limit is an elastic resource limit of the task queue. Comprising the steps that priority information of a next to-be-executed task in a target task queue and current available resource information of the target task queue are obtained, the priority information comprises a high priority or a low priority, and the current available resource information comprises available resources in a minimum resource limit and available resources in an elastic resource limit; or no available resource exists in the maximum resource limit; and based on the priority information of the next to-be-executed task and the current available resource information of the target task queue, performing resource elastic scheduling on the next to-be-executed task. The task throughput and the resource utilization rate of the scheduling system can be improved in an elastic scheduling mode.

The invention belongs to the technical field of computers and artificial intelligence, and discloses a priority differential cache-based MoE batch reasoning method and system, and the method comprises the steps: recognizing global hot experts with higher activation frequency in each layer, enabling the global hot experts to remain in a high-priority cache during initialization, and building a priority list of the experts in each layer; in the reasoning stage, selecting an expert set needing to be activated in the current layer; the expert priority score is dynamically updated according to the activation and reuse behaviors of the experts, and the experts are migrated and replaced among the high-level cache, the middle-level cache and the low-level cache according to the priority score and a cache threshold value; according to a current layer gating result and a historical activation track, predicting an expert set which may be activated in a next layer, and asynchronously loading the expert set to a low-priority cache during current layer calculation so as to realize time overlapping of calculation and communication. According to the method, the expert migration frequency can be reduced, the cache hit rate and the throughput rate are improved, the video memory utilization rate is remarkably optimized, and good expansibility and universality are achieved.

The invention provides a self-adaptive data packet scheduling method based on approximate quantiles and multiple queues on a programmable data plane, and aims to solve the problem that the scheduling performance and the resource efficiency are difficult to balance in the prior art. According to the method, lightweight ranking scoring, dynamic queue mapping and a cascade enqueue strategy are combined. A relative priority score of the data packet is efficiently calculated through a minimum-maximum normalization mechanism; adaptively mapping the data packets to one of a plurality of FIFO queues according to the scores and real-time congestion conditions of the queues, and providing a fast channel for extremely high priority traffic; and when the target queue is full, trying to store the data packet into a queue with a lower priority in a cascading manner so as to avoid unnecessary discarding. According to the method, resource consumption and implementation complexity are remarkably reduced while the approximate ideal PIFO scheduling performance is achieved, and the method is particularly suitable for resource-limited environments such as a software-defined network and edge computing.

An intra-user equipment (UE) multiplexing method is executed in a UE. The UE obtains respective timeline conditions for multiplexing uplink transmission with high priority and uplink transmission with low priority when detecting collision in time between the uplink transmissions with different priorities. The UE performs multiplexing of the uplink transmissions with different priorities when the respective timeline conditions are satisfied.

To extremely restrain variation in time until a low-priority cyclic task starts to be executed even if an interruption task is executed when a high-priority cyclic task and a low-priority cyclic task are executed as cyclic tasks at each control period.SOLUTION: In a control period in which an interrupt task is executed and execution of at least one portion of a high-priority cyclic task is disabled, the start timing of a low-priority cyclic task is corrected at timing earlier than timing when it is assumed that the high-priority cyclic task is entirely completed. For this reason, even if an interrupt task is executed, an influence of time required for the interrupt task on the start timing of a low-priority cyclic task can be reduced. As a result, even if an interrupt task is executed, variation in time until low-priority processing starts to be executed after a control period is started can be restrained as much as possible.SELECTED DRAWING: Figure 2

The invention provides a priority dynamic allocation method and system of an embedded operating system, and belongs to the technical field of embedded operating systems. The method comprises the following steps: initializing a core data structure of the embedded operating system, and starting a time base manager; performing task registration and static parameter setting, integrating dynamic priority factors, and calculating effective priorities of tasks to dynamically configure task parameters; using the time base manager to drive a multi-layer scheduling mechanism to perform multi-level task scheduling; dynamically adjusting the effective priority to realize the priority dynamic distribution of the embedded operating system; and monitoring the running state of the embedded operating system, and performing dynamic cutting according to the running state so as to optimize the running of the embedded operating system. According to the invention, the peripheral interruption directly triggers the dependent task priority transition; the priority can be dynamically adjusted, and priority overturning and low-priority task starvation are prevented; the function modules can be automatically degraded according to hardware resources, and the purpose of good hardware adaptability is achieved.

A transmission method and a terminal device are provided. The transmission method includes: when configuring a configured grant retransmission timer, a terminal device determining a hybrid automatic repeat request process and / or the state of the timer on the basis of a satisfied condition. By means of the embodiments of the present application, the transmission delay of a resource, especially a low-priority resource, can be reduced.

The invention discloses an Internet of Things charging station intelligent power distribution control method fused with panoramic image comparison. The method comprises the following steps: deploying a sensing unit through an electric-red Internet of Things system to collect multiple pieces of panoramic sensing information; generating an initial sub-image, fusing the environment parameters to mark an abnormal region, and splicing to form a target panoramic image of the charging station; calling a preset panoramic image as a reference; comparing the target panoramic image with a preset panoramic image, and outputting an abnormal event when the difference exceeds a set range; calculating a priority score for the abnormal event, and generating an instruction execution sequence; cooperative instructions are generated according to a sequence, and conflicts are solved. During target conflicts, high-priority instructions cover low-priority instructions, compensation instructions are generated, and optimal redistribution is carried out according to efficiency during resource conflicts. And the target equipment issues a control instruction to realize dynamic adjustment of the power distribution parameters. Through power distribution parameter dynamic adjustment and instruction control, line loss and energy waste are reduced, and high-concurrency charging requirements are met.

The invention belongs to the technical field of automotive electronics AUTOSAR, and discloses an AUTOSAR multi-task-oriented nested lock management and real-time priority scheduling control system, a detection and prevention module establishes a dynamic resource allocation diagram by taking tasks and locks as nodes, real-time traversal is performed in combination with a depth-first search algorithm, and a task-lock-task circulation path is accurately identified; when a potential deadlock is detected, preferentially releasing a low optimal lock occupied by a low-priority task through priority arbitration, and triggering an overtime release mechanism when the priorities are the same; a scene of accessing multiple layers of shared resources by multi-task nesting under an AutoSar framework is adapted, so that the system is ensured to stably run in a complex concurrent scene, and function failure caused by deadlock is avoided; the priority scheduling module establishes a scheduling rule in combination with dual priorities of tasks and locks, optimizes a nested priority inheritance mechanism, temporarily improves the priority when a low-optimal task occupies a lock required by a high-optimal task, and configures a preemption right for the high-optimal lock.

This disclosure provides systems, methods and apparatuses for a high priority route selection descriptor (RSD) selection timer. A protocol data unit (PDU) session may be established for an application associated with a user equipment (UE). If the PDU session is associated with a lower RSD priority than the highest RSD priority for the application, the UE may initiate an RSD selection timer. After expiration of the RSD selection timer, the UE may try to establish another PDU session for the application with the highest RSD priority for the application. If another PDU session with the highest RSD priority is accepted, the UE may release the initial PDU session with the lower RSD priority and establish a new PDU session with the highest RSD priority. Such implementations may increase data rates, quality of service, and reliability for the application, decrease latency of the application, or decrease power consumption of the UE.

The invention discloses a WebWorker cooperative interrupt scheduling processing method and device for high-frequency time sequence monitoring data. The method comprises the following steps: splitting original high-frequency time sequence monitoring data into a plurality of tasks according to a statistical dimension in a main thread, and endowing the tasks with priorities; utilizing the minimum heap maintenance task queue to split each task into fragmentation units which can be independently executed; dynamically creating a Web Worker pool according to the core number of the central processing unit, and executing a current fragmentation unit in any Worker in the Web Worker pool through a scheduling controller; if the task of which the priority is higher than that of the current fragmentation unit is detected, interrupting the current fragmentation unit, storing the execution state of the current fragmentation unit, and preempting the fragmentation unit for executing the high-priority task by the thread; and increasing the weight of the low-priority task along with time through a starvation detection mechanism until the low-priority task is executed, and transmitting a task processing result to the main thread for visual rendering.

The invention provides a resource scheduling method which can be applied to the fields of cloud computing and artificial intelligence. The resource scheduling method is applied to a service processing system containing heterogeneous computing resources and comprises the steps that service request load prediction information in a preset time period is obtained, the batch processing scale of each priority is determined by combining service priorities and a response time limit threshold value, and the batch processing scale of the high priority is smaller than the batch processing scale of the low priority; based on the batch processing scale and the memory consumption characteristic parameters, calculating the memory capacity required by the task, and screening candidate computing resources with sufficient available memories; according to the batch processing scale, the calculation feature parameters and the candidate resource performance parameters, calculation execution time delay and combination of queuing time delay, determining predicted completion time; and in the candidate resources meeting the response time limit threshold, selecting the resource with the smallest number of calculation units to execute the task. The invention further provides a resource scheduling device and equipment, a medium and a program product.

In various embodiments, a live event caching application caches segments that are associated with live events. At a first point-in-time, the live event caching application stores a segment of a downloadable that is associated with a live event in a high priority list. At a second point-in-time, the live event caching application determines that the segment is at a tail of the high priority list, where the second point-in-time is subsequent to the first point-in-time. Upon determining that the segment is at the tail of the high priority list, further determining that an age of the segment is greater than a cutoff threshold. In response to determining that the age of the segment is greater than the cutoff threshold, moving the segment from the high priority list to a low priority list.

The invention discloses a front-end resource management method and device, equipment and a medium, and relates to the technical field of computers, and the method comprises the steps: determining a to-be-loaded page resource based on current behavior data; reading and loading a first to-be-loaded page sub-resource corresponding to the to-be-loaded page resource from a pre-loading resource list in the cache; the preloaded resource list comprises page sub-resources meeting priority conditions in different page resources; the priority condition is that the priority of the page sub-resources is within a target priority range; the target priority range is a plurality of priorities screened from all priorities according to a high-to-low screening sequence of the priorities; and after the first to-be-loaded page sub-resource is loaded, calling a rear-end interface to load a second to-be-loaded page sub-resource corresponding to the to-be-loaded page resource, and adding the second to-be-loaded page sub-resource which does not exist in the pre-loaded resource list in the cache and meets the cache requirement into the pre-loaded resource list in the cache. The page loading efficiency can be improved.

A processing system including processing cores, a shared memory, a shift table that stores a maximum number of reservations to locations in the memory, and an exclusive monitor that uses the shift table and an eviction policy to enforce core synchronization. The eviction policy is based on priority, age of valid reservations, shift table fullness state, and reservation memory conflict. The shift table may include a memory address and a size value indicative of a flexible amount of reserved memory at the memory address. The exclusive monitor evicts an oldest reservation in the shift table having a same or lower priority level as the new reservation. The exclusive monitor rejects the new reservation when the shift table is full of higher priority reservations. Reservations are shifted to maintain age status. Stale reservations may be invalidated or have their priority lowered. Conflicting reservations may be made with the same priority level.