Energy efficient routing algorithm for patient monitoring in body sensor networks

R. Rajagopalan
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引用次数: 10

Abstract

Wireless body sensor networks are widely used for monitoring individuals in assisted living facilities and has emerged as a promising technology in e-healthcare. Such networks consist of sensors on the body or clothing of an individual for measuring vital signals such as heart beat, body temperature, and electrocardiogram. This enables patients to experience greater physical mobility and independence eliminating the need to stay in the hospital. Efficient and reliable transmission of data from on body sensors to medical personnel via multi-hop routing is critical for continuous health monitoring. In this paper, we propose a new routing algorithm for energy efficient routing in body sensor networks for reliable health monitoring. We model the routing problem as a constrained multi-objective optimization problem maximizing the throughput while minimizing the energy consumption subject to a constraint on end to end latency. We have designed a new constrained multi-objective genetic algorithm (CMOGA) for obtaining energy efficient routes. Simulation results show that CMOGA demonstrates the advantages of multi-objective optimization and outperforms a widely used and well known multi-objective evolutionary algorithm.
身体传感器网络中病人监测的高效路由算法
无线身体传感器网络广泛用于辅助生活设施中的个人监测,并已成为电子医疗领域的一项有前途的技术。这种网络由个人身上或衣服上的传感器组成,用于测量诸如心跳、体温和心电图等重要信号。这使患者能够体验到更大的身体活动能力和独立性,无需留在医院。通过多跳路由将身体传感器的数据高效可靠地传输给医务人员对于持续健康监测至关重要。在本文中,我们提出了一种新的路由算法,用于身体传感器网络中的节能路由,以实现可靠的健康监测。我们将路由问题建模为一个受约束的多目标优化问题,在端到端延迟约束下,使吞吐量最大化,同时使能耗最小化。设计了一种求解节能路径的约束多目标遗传算法(CMOGA)。仿真结果表明,CMOGA具有多目标优化的优点,优于一种广泛使用的多目标进化算法。
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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