摘要
针对物联网智能感知节点的软硬件划分问题,提出了基于π网的物联网智能感知节点的软硬件划分模型,并对模型进行了实验与仿真.首先对物联网智能感知节点进行带约束定义,得到了智能感知节点的约束模型;然后利用π网理论,建立了基于π网的物联网智能感知节点软硬件划分模型,并对模型进行了演化分析;最后,利用先进Pareto优化算法对划分模型进行了优化,同时与TS禁忌搜索算法和GA遗传算法等进行了对比实验.通过分析与实验仿真,建立的模型,在适应度和划分执行时间等方面具有一定的优越性和实用性.
Aiming at the problem of hardware and software partition of intelligent sensing nodes in Internet of Things, a hardware and software partition model of intellisence nodes based on π network was proposed, experimented and simulated. Firstly, the constrained model of the intellisense node was obtained by defining intellisense nodes of the internet of things with constraints. Then, the hardware and software partition model of intelligent sensing nodes based on π network was established by using the π network theory, and the model was analyzed by evolution analysis method. Finally, the partition model was optimized by the advanced Pareto optimization algorithm, and compared with TS tabu search algorithm and GA genetic algorithm in experiments. Through the analysis and experimental simulation,the model established has certain superiority and practicability in the aspects of adaptability and division of execution time.
出处
《西南民族大学学报（自然科学版）》
CAS
2018年第1期56-63,共8页
Journal of Southwest Minzu University(Natural Science Edition)
基金
国家科技计划支撑基金项目(2012BAH76F01)
四川省水利厅2017年科研计划项目(SL2017-01)
关键词
物联网
智能感知节点
π网
软硬件划分
internet of things
intelligent sensing node
π-net
hardware/software partitioning
