Autonomous Resource Management and Control Algorithms for Distributed Wireless Sensor Networks

被引:0
|
作者
Talukder, Ashit [1 ]
Bhatt, Rajan [1 ]
Chandramouli, L. [1 ]
Ali, Syed Muhammad [1 ]
Pidva, Rishi [1 ]
Monacos, S. [1 ]
机构
[1] Univ So Calif, CHLA, Jet Prop Lab, NASA, Los Angeles, CA 90089 USA
关键词
Evolutionary algorithm; control; distributed sensing; machine learning; sensor networks; pattern recognition; resource management; mathematical optimization; wireless communication;
D O I
暂无
中图分类号
TP301 [理论、方法];
学科分类号
081202 ;
摘要
We discuss a novel framework for integrated sensing and resource management in a distributed intelligent sensor network with sensor nodes whose useful active lifetime is significantly shorter than the required lifetime of the sensor system. Past sensor network research has focused on security and communication, but largely ignored the overall dynamic resource management issue of such distributed systems. Our contribution is in integrated control optimization and resource management algorithms to ensure proper functioning of distributed sensors in extremely limited bandwidth, power, and storage. In this paper, we present a novel genetic algorithm for real-time system control and resource management that handles multiple conflicting objectives and constraints in the distributed system. Our framework is suitable for dynamic environments where the desired system performance and resource usage changes dynamically while being constrained by limited amount of resources.
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页数:8
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