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

机译:基于集群的无线传感器网络的多目标优化框架

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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.
机译:无线传感器节点是电池供电的通信设备。它们有限的功能给无线传感器网络(WSN)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。群集通常用于减少WSN中的能耗。但是,聚类参数的任意选择可能导致其他方面的严重降低,例如数据收集过程(DCP)的额外延迟。本文提出了一种基于集群的无线传感器网络的多目标优化框架。提议的框架将能耗和DCP的持续时间都视为其目标功能。仿真结果表明,使用所提出的框架进行优化的网络可以在两个目标之间取得合理的权衡。尽管如此,使用所提出的框架进行优化的网络仍可以获得非支配的解决方案,而这些解决方案无法通过使用能量感知的聚类算法来实现。

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