A Multi-Objective Optimization Framework for Cluster-Based Wireless Sensor Networks

Chi-Tsun Cheng, H. Leung
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引用次数: 9

Abstract

Wireless sensor nodes are battery-powered communication devices. Their limited capabilities have imposed various constraints to the system design of wireless sensor networks (WSNs). These constraints are interrelated, and are usually in conflict with each other. Clustering is often used to reduce energy consumption in WSNs. However, an arbitrary selection of clustering parameters may lead to severe degradation in other aspects, such as extra delays in data collection processes (DCPs). In this paper, a multi-objective optimization (MOO) framework for cluster-based WSNs is proposed. The proposed framework considers both the energy consumption and the duration of a DCP as its objective functions. Simulation results show that networks optimized using the proposed framework can obtain reasonable trade-offs between the two objectives. Nevertheless, the networks optimized using the proposed framework can obtain non-dominated solutions that cannot be achieved by using energy-aware clustering algorithms.
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基于集群的无线传感器网络多目标优化框架
无线传感器节点是由电池供电的通信设备。它们有限的性能给无线传感器网络(WSNs)的系统设计带来了各种限制。这些约束是相互关联的,并且通常彼此冲突。在无线传感器网络中,聚类通常用于降低能耗。但是,任意选择聚类参数可能会导致其他方面的严重退化,例如数据收集过程(dcp)的额外延迟。提出了一种基于聚类的无线传感器网络多目标优化框架。提出的框架将能量消耗和DCP持续时间作为其目标函数。仿真结果表明,使用该框架优化的网络可以在两个目标之间获得合理的权衡。然而,使用该框架优化的网络可以获得非支配解,这是使用能量感知聚类算法无法实现的。
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