群智感知计算下多终端引擎任务有效分配方法  

Effective allocation method of multi-terminal engine tasks under group intelligence perception computing

作　　者：张洋[1] 郑云鹏 ZHANG Yang;ZHENG Yun-peng(School of College of Humanities&Information Changchun University of Technology,Jilin Changchun 130000,China)

机构地区：[1]长春工业大学人文信息学院,吉林长春130000

出　　处：《计算机仿真》2023年第6期491-494,517,共5页Computer Simulation

摘　　要：目前多终端引擎任务分配方法忽略了对多终端引擎状态数据的行采集,存在分配时间长、分配效能低和负载均衡度差的问题。为此提出基于群智感知计算的多终端引擎任务分配方法。优先划分时空域,在感知期间构建系统模型,引入感知覆盖概念,利用群智感知计算方法对多终端引擎任务状态数据进行采集。根据采集数据建立多终端引擎分配器模型,根据据引擎在执行过程中的用户状态及负载运行情况,采用任务分配算法将任务分配给最佳用户,实现多终端引擎任务分配方法。实验结果表明,通过对所提方法的分配时间、分配效能和负载均衡度指标的对比测试,验证了上述方法的有效性强、准确度高。The multi-terminal engine task allocation method has long allocation time,low allocation efficiency and load balance,because of ignoring the row collection of multi-terminal engine status data.Consequently,the task allocation method of multi terminal engine based on swarm intelligence perception computing is studied in this paper.During perception,the space-time domain was divided and the system model was constructed.Based on the concept of perceptual coverage,swarm intelligence perceptual computing method was used to collect the data of multi terminal engine task status.According to the collected data results,the multi-terminal engine distributor model was established.Based on the user status and load operation of the engine during the execution process,the task allocation algorithm was introduced to allocate the task to the best user,thus achieving the task allocation method of multi termi-nal engine.The experimental results show that this method has short allocation time,high allocation efficiency and outstanding load balancing.

关 键 词：群智感知计算 多终端引擎任务 任务分配 任务分配算法 

分 类 号：F046.3[经济管理—政治经济学]