基于混合最优父代选择的低功耗有损网络(RPL)节能路由协议

IF 7.5 1区 计算机科学 Q1 COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE
Prabhavathi Cheppali, Meera Selvakumar
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引用次数: 0

摘要

在低功耗损耗网络路由协议(RPL)中,研究人员提出了一种基于多目标优化技术的单复合度量方法来选择父节点。但是选择错误的父节点会导致丢包、网络节点拥塞、能耗增加、收敛时间延长等问题。为了克服这些问题,本文提出了一种具有混合最优亲本选择模型的节能RPL路由。首先,基于信任、延迟、能量、链路质量(LQ)和距离等多目标进行最优亲本选择阶段。针对这种最优亲本选择,提出了一种新的混合优化方法——矮猫鼬辅助Shuffle - Shepherd优化(DM-SSO)。然后,提出了一种改进的基于覆盖的动态细流技术,用于高效的目标导向无环图(DODAG)构造。然后,考虑源和目的之间距离最短的路径进行路由。最后,在现有模型的基础上对所提出的DM-SSO模型进行了性能评价。所提出的DM-SSO模型能量最高,为1.16,而传统方法能量最低,分别为FF = 0.74、MFO-RPL = 0.79、ACOR = 0.84、BMO = 0.76、SSA = 0.82、SMA = 0.85、MRFO = 0.73。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Hybrid optimal parent selection based energy efficient routing protocol for Low-Power and lossy networks (RPL) routing
A single-composite measure with a multi-objective optimization technique for parent selection is provided by the researchers in Routing protocol for low-power and lossy networks (RPL). However, selecting the wrong parent causes packet losses, congestion on network nodes, higher energy consumption, and longer convergence times. To overcome these issues, this paper proposes an energy-efficient RPL routing with a hybrid optimal parent selection model. Initially, the optimal parent selection stage is performed based on multi-objectives like trust, delay, energy, link quality (LQ), and distance. For this optimal parent selection, a novel hybrid optimization method called Dwarf Mongoose aided Shuffle Shepherd Optimization (DM-SSO) is proposed. Then, an improved coverage-based dynamic trickle technique is developed for energy-efficient Destination Oriented Directed Acyclic Graph (DODAG) construction. Then, the path with the shortest distance between the source and destination is considered for routing. Finally, the performance of the proposed DM-SSO model is evaluated over existing models. The proposed DM-SSO model acquired the highest energy of 1.16, while the conventional techniques acquired the lowest energy such as FF = 0.74, MFO-RPL = 0.79, ACOR = 0.84, BMO = 0.76, SSA = 0.82, SMA = 0.85 and MRFO = 0.73, respectively.
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来源期刊
Expert Systems with Applications
Expert Systems with Applications 工程技术-工程:电子与电气
CiteScore
13.80
自引率
10.60%
发文量
2045
审稿时长
8.7 months
期刊介绍: Expert Systems With Applications is an international journal dedicated to the exchange of information on expert and intelligent systems used globally in industry, government, and universities. The journal emphasizes original papers covering the design, development, testing, implementation, and management of these systems, offering practical guidelines. It spans various sectors such as finance, engineering, marketing, law, project management, information management, medicine, and more. The journal also welcomes papers on multi-agent systems, knowledge management, neural networks, knowledge discovery, data mining, and other related areas, excluding applications to military/defense systems.
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