Merged Path: Distributed Data Dissemination in Mobile Sinks Sensor Networks

IF 3 3区 计算机科学 Q2 COMPUTER SCIENCE, HARDWARE & ARCHITECTURE IEEE Transactions on Sustainable Computing Pub Date : 2024-06-06 DOI:10.1109/TSUSC.2024.3410247
Xingfu Wang;Ammar Hawbani;Liang Zhao;Saeed Hamood Alsamhi;Wajdy Othman;Mohammed A.A. Al-qaness;Alexey V. Shvetsov
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Abstract

This paper studies distributed data dissemination in multiple mobile sinks wireless sensor networks. Previous studies employed separated paths to disseminate data packets from a given source to a given set of mobile sinks independently, which exhausts the constrained resources of the network. In this paper, we explore how the merged paths mechanism could rationalize utilizing network resources. To do so, we propose a protocol named Merged Path, which is implemented in four steps in a distributed manner. First, the bifurcation points (i.e., where the path is branched into multiple sub-branches) are discovered. Second, we developed a Discrete Cumulative Clustering algorithm (DCC) to divide the sinks into disjoint clusters at each bifurcation point. Third, we propose a Diagonal Virtual Line (DVL) structure to delegate the communication between the high-tier and low-tier nodes. Last, on top of DVL and DCC, we propose an opportunistic metric that captures multiple network-layer attributes to disseminate the data packet to the sinks through multiple branches. The simulation results showed that about 50% of the network energy could be saved by merging the paths versus the separate paths, considering an area of interest application with 20 mobile nodes each carrying a sink.
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本文研究多移动汇无线传感器网络中的分布式数据传播。以往的研究采用分离路径将数据包从一个给定的源独立传播到一组给定的移动汇,这耗尽了有限的网络资源。本文探讨了合并路径机制如何合理利用网络资源。为此,我们提出了一个名为 "合并路径 "的协议,该协议以分布式方式分四步实现。首先,发现分叉点(即路径分支成多个子分支的地方)。其次,我们开发了一种离散累积聚类算法(DCC),在每个分叉点将汇分成互不相关的簇。第三,我们提出了对角线虚拟线(DVL)结构,以委托高层和低层节点之间的通信。最后,在 DVL 和 DCC 的基础上,我们提出了一种机会主义度量方法,它能捕捉多个网络层属性,通过多个分支将数据包传播到汇。仿真结果表明,考虑到一个有 20 个移动节点、每个节点携带一个汇节点的兴趣区应用,合并路径与单独路径相比可节省约 50% 的网络能源。
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来源期刊
IEEE Transactions on Sustainable Computing
IEEE Transactions on Sustainable Computing Mathematics-Control and Optimization
CiteScore
7.70
自引率
2.60%
发文量
54
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