An MDP-based application oriented optimal policy for wireless sensor networks

Arslan Munir, A. Gordon-Ross
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引用次数: 39

Abstract

Technological advancements due to Moore's law have led to the proliferation of complex wireless sensor network (WSN) domains. One commonality across all WSN domains is the need to meet application requirements (i.e. lifetime, responsiveness, etc.) through domain specific sensor node design. Techniques such as sensor node parameter tuning enable WSN designers to specialize tunable parameters (i.e. processor voltage and frequency, sensing frequency, etc.) to meet these application requirements. However, given WSN domain diversity, varying environmental situations (stimuli), and sensor node complexity, sensor node parameter tuning is a very challenging task. In this paper, we propose an automated Markov Decision Process (MDP)-based methodology to prescribe optimal sensor node operation (selection of values for tunable parameters such as processor voltage, processor frequency, and sensing frequency) to meet application requirements and adapt to changing environmental stimuli. Numerical results confirm the optimality of our proposed methodology and reveal that our methodology more closely meets application requirements compared to other feasible policies.
一种基于mdp的面向应用的无线传感器网络优化策略
由于摩尔定律的技术进步导致了复杂无线传感器网络(WSN)域的扩散。所有WSN域的一个共同点是需要通过特定于域的传感器节点设计来满足应用需求(即生命周期、响应性等)。传感器节点参数调优等技术使WSN设计人员能够专门设计可调参数(即处理器电压和频率,传感频率等)以满足这些应用需求。然而,考虑到WSN域的多样性、不同的环境情况(刺激)和传感器节点的复杂性,传感器节点参数的调优是一项非常具有挑战性的任务。在本文中,我们提出了一种基于自动化马尔可夫决策过程(MDP)的方法来规定最佳传感器节点操作(选择可调参数的值,如处理器电压,处理器频率和传感频率),以满足应用需求并适应不断变化的环境刺激。数值结果证实了我们提出的方法的最优性,并表明与其他可行的策略相比,我们的方法更接近于应用需求。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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