物联网环境下多并发任务分簇调度方法仿真

Simulation of Clustering Scheduling Method for Multi-Concurrent Tasks in Internet of Things

为全面缓解由网络任务拥堵造成的调度均衡失控问题,提出物联网环境下的多并发任务分簇调度方法。在多并发网络处理架构中,设置具有关联能力的智能任务检测电表,并以电表中的显示数值为依据设计无线任务传输模块,完成多并发任务处理的物联网环境构建。在此基础上,确定任务目标参量,通过提取TDS分簇算子的方式,扩展多并发调度系数,实现物联网环境下多并发任务分簇调度方法的顺利应用。仿真结果显示,应用QoS、DoS、AoS方法后,网络任务的拥堵现状均不能得到有效缓解,且调度均衡参数的最大值与预期标准数值也始终存在较大物理误差,而随着多并发任务分簇调度方法的应用,网络任务拥堵量不断下降,调度均衡参数的实际值也开始出现大幅回升,固有调度均衡失控问题得到有效解决。

In order to comprehensively alleviate the problem of incontrollable scheduling caused by network task congestion,a clustering and scheduling method for multi-concurrent tasks in Internet of Things(IoT)environment was presented.In the multi-concurrent network architecture,an intelligent electricity meter to detect tasks with associated ability was established.The wireless task transmission module was designed based on the displayed value in electricity meter,and thus to complete the construction of IoT environment for processing multi-concurrent tasks.On this basis,the target parameters of tasks were determined,and the multi-concurrent scheduling coefficients were extended by extracting TDS clustering operator.Finally,the clustering and scheduling method for multi-concurrent tasks could be applied in IoT environment.Simulation results show that,after QoS,DoS and AoS are adopted,the congestion of network tasks cannot be effectively alleviated,and there are large physical errors between the maximum value of scheduling equalization parameters and the expected standard values.With the application of clustering and scheduling method of multi-concurrent tasks,the network task congestion is reduced,and the actual value of scheduling equalization parameters also increases sharply,so that the inherent problem of scheduling imbalance is effectively solved.