Ant Colony Optimization Based Routing Strategies for Internet of Things

Q2 Environmental Science

Evergreen Pub Date : 2023-06-01 DOI:10.5109/6793654

Anukriti Sharma, Sharad Sharma, Dushyant Gupta

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引用次数: 0

Abstract

: In this paper, two meta-heuristic approaches have been optimized using SI (Swarm Intelligence) optimization technique. The method comprises computation of shortest path of both, static and dynamic IoT (Internet of Things) network using “widely used algorithms” among researchers, namely, ‘Breadth first search’ and ‘Dijkstra algorithm.’ Further, the determined route has been optimized using ant colony optimization. The issue of route selection to reach the destination, as well as parameters such as network energy, departed node count, residual energy of IoT nodes, and critical points of IoT nodes have been explored using proposed smart routing techniques. The two unique routing approaches have been simulated with rigorous iteration run, i=2000. The proposed methods, ‘Ant colony optimization-Breadth first computation-Minkowski-Static’ (ABMS) technique and ‘Ant colony optimization-Breadth first computation-Minkowski-Dynamic’ (ABMD) technique have been simulated. After comparing efficiency between both techniques, ABMS method outperforms the ABMD routing technique for IoT network. A significant energy savings has been reported, extending network lifetime of a static IoT network scenario. With the implementation of both techniques, the comparison between dynamic and static results closely.

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基于蚁群优化的物联网路由策略

在本文中，使用SI（Swarm Intelligence）优化技术对两种元启发式方法进行了优化。该方法包括使用研究人员中“广泛使用的算法”，即“广度优先搜索”和“Dijkstra算法”，计算静态和动态物联网网络的最短路径此外，已经使用蚁群优化对所确定的路线进行了优化。使用所提出的智能路由技术，探讨了到达目的地的路由选择问题，以及网络能量、离开节点数、物联网节点的剩余能量和物联网节点关键点等参数。这两种独特的路由方法已经通过严格的迭代运行（i=2000）进行了模拟。对所提出的“蚁群优化广度优先计算Minkowski静态”（ABMS）技术和“蚁群优化宽度优先计算Minkawski动态”（ABMD）技术进行了仿真。在比较了两种技术的效率后，ABMS方法在物联网网络中的性能优于ABMD路由技术。据报道，在静态物联网网络场景中，显著节省了能源，延长了网络寿命。随着这两种技术的实现，动态与静态结果的比较越来越紧密。

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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来源期刊

Evergreen Environmental Science-Management, Monitoring, Policy and Law

CiteScore

4.30

自引率

0.00%

发文量

期刊介绍： “Evergreen - Joint Journal of Novel Carbon Resource Sciences & Green Asia Strategy” is a refereed international open access online journal, serving researchers in academic and research organizations and all practitioners in the science and technology to contribute to the realization of Green Asia where ecology and economic growth coexist. The scope of the journal involves the aspects of science, technology, economic and social science. Namely, Novel Carbon Resource Sciences, Green Asia Strategy, and other fields related to Asian environment should be included in this journal. The journal aims to contribute to resolve or mitigate the global and local problems in Asia by bringing together new ideas and developments. The editors welcome good quality contributions from all over the Asia.