物联网中共享资源数据调度方法的研究  

Study of the Shared Resource Data Scheduling Method of the Internet of Things

作　　者：顾炜江[1] 

机构地区：[1]南京林业大学信息中心,江苏南京210037

出　　处：《计算机仿真》2017年第1期268-271,共4页Computer Simulation

摘　　要：对物联网共享资源数据进行合理调度,可以减少冗余数据,提高物联网络性能。在进行共享资源数据调度时,需要构建数据约束函数,对共享资源数据进行上下界的约束,而传统的共享队列算法是将数据资源请求提交到某个线程队列中进行调度,没有设定数据资源上下界约束条件,导致某个队列中出现数据拥塞,而另一队列没有数据的情况,降低了数据调的有效性。提出TD算法的物联网中共享资源数据进行调度,其中提出调度共享资源的上下界约束条件对将共享资源数据划分为不同的状态,在此基础上建立物联网中共享资源数据调度模型,将模型中的执行节点按计算能力进行划分,利用向上排序值计算方法将各个共享资源调度任务进行排序,选取具有调度任务完成时间的最小值作为当前任务分配的节点,有效的完成了物联网中共享资源数据调度。仿真结果证明,TD算法在物联网共享资源数据调度中能够大幅度的提升物联网络中共享资源数据调度的公平性与合理性。It can reduce redundant data and improve the Internet of things performance to schedule shared resource data reasonably. We need to build constraint function of data and restrain shared resource data with upper and lower bound during scheduling shared resource data. Traditional shared queue algorithm schedules data via referring data resource request to some linear queue. It doesnot Set upper and lower bound constraints. So it results in jamming in one queue and no data in another. The algorithm reduces effectiveness of data scheduling. In this paper, we propose a TD algorithm to schedule shared resource data. The shared resource data are divided into different status by scheduling upper and lower bound constraint. Then we build shared resource data scheduling model. We divide execution nodes of model based on computing power. Each shared resource scheduling task is ranked via upward ranking value computing way. Finally we select the minimum finished time as current task node to complete shared resource data scheduling effectively. The simulation showed that the TD algorithm can significantly elevate equity and rationality of shared resource data during data scheduling in the Internet of things.

关 键 词：资源调度 物联网 向上排序值 

分 类 号：TP302[自动化与计算机技术—计算机系统结构]