基于混合模糊和改进骑手优化算法的物联网无线体域网络节能聚类和路由

D. A, Rangaraj J
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引用次数: 1

摘要

无线传感器网络广泛应用于各种物联网应用,包括医疗保健、水下传感器网络、体域网络和多个办公室。无线体域网络(WBAN)简化了医疗部门的工作,提供了一种减少医疗诊断过程中错误可能性的解决方案。这种网络对实时应用日益增长的需求将刺激重要的研究活动。由于网络拓扑的动态变化、严格的功率约束和有限的计算能力,在保持能源效率的同时设计此类关键事件的场景是很困难的。路由协议的设计对无线局域网的通信栈和网络性能有着重要的影响。WBAN中节点的高移动性导致拓扑变化快,影响网络的可扩展性。节点集群是wban中用于解决此问题的许多其他机制之一。我们考虑了物联网设备的距离、延迟和功耗等优化因素,以实现所需的CH选择。本文提出了一种采用混合模糊和改进的骑手优化算法(MROA)的高级CH选择和路由方法。本研究工作是利用MATLAB软件实现的。模拟是在一系列条件下进行的。在能耗和网络寿命方面,所提出的方案优于当前最先进的技术,如低能量自适应聚类层次(LEACH)、能量控制路由算法(ECCRA)、节能路由协议(EERP)和简化能量平衡替代感知路由算法(SEAR)。
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Energy Efficient Clustering and Routing Using Hybrid Fuzzy with Modified Rider Optimization Algorithm in IoT - Enabled Wireless Body Area Network
Wireless sensor networks are widely used in various Internet of Things applications, including healthcare, underwater sensor networks, body area networks, and multiple offices. Wireless Body Area Network (WBAN) simplifies medical department tasks and provides a solution that reduces the possibility of errors in the medical diagnostic process. The growing demand for real-time applications in such networks will stimulate significant research activity. Designing scenarios for such critical events while maintaining energy efficiency is difficult due to dynamic changes in network topology, strict power constraints, and limited computing power. The routing protocol design becomes crucial to WBAN and significantly impacts the communication stack and network performance. High node mobility in WBAN results in quick topology changes, affecting network scalability. Node clustering is one of many other mechanisms used in WBANs to address this issue. We consider optimization factors like distance, latency, and power consumption of IoT devices to achieve the desired CH selection. This paper proposes a high-level CH selection and routing approach using a hybrid fuzzy with a modified Rider Optimization Algorithm (MROA). This research work is implemented using MATLAB software. The simulations are carried out under a range of conditions. In terms of energy consumption and network life time, the proposed scheme outperforms current state-of-the-art techniques like Low Energy Adaptive Clustering Hierarchy (LEACH), Energy Control Routing Algorithm (ECCRA), Energy Efficient Routing Protocol (EERP), and Simplified Energy Balancing Alternative Aware Routing Algorithm (SEAR).
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