LooP: A Low-Overhead Path Reconstruction for Large-Scale IoTs

IF 6.7 2区计算机科学 Q1 ENGINEERING, MULTIDISCIPLINARY

IEEE Transactions on Network Science and Engineering Pub Date : 2025-02-13 DOI:10.1109/TNSE.2025.3535806

Luwei Fu;Zhiwei Zhao;Zhuoliu Liu;Geyong Min

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引用次数: 0

Abstract

Internet of Things (IoT) plays a vital role in various smart applications due to its cost-efficiency and good scalability. For safety and management of a large-scale IoT with many gateways, packet-level path reconstruction which exactly reveals the transmission path of each packet is desired. However, the existing path reconstruction schemes rely on correlation between diverse packets, which results in either considerable overhead or poor accuracy. It is particularly difficult to reconstruct the paths by affordable overhead under the intensive deployment, constrained resource, and weak correlation of IoT devices. To this end, we propose a Low-overhead Path reconstruction (LooP) for large-scale IoT. The proposed scheme exploits the nature of incremental update that each node only identifies the changes of its one-hop topology for diverse gateways. The gateway nodes then iteratively recover the complete path of each received packet according to the reported changes and historical information. It removes much redundant overhead (e.g., the common paths information) while guaranteeing the accurate reconstruction in a large scale and dynamic topology network. We analyze the information entropy of LooP and several existing schemes to theoretically prove the superiority of our proposal. The experimental results also demonstrate LooP can achieve 98% reconstruction accuracy on average and at least 3x gain-cost-ratio of the sub-optimal rival.

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环路：用于大规模物联网的低开销路径重建

物联网（Internet of Things, IoT）以其成本效益和良好的可扩展性在各种智能应用中发挥着至关重要的作用。为了保证具有多个网关的大规模物联网的安全和管理，需要进行数据包级路径重构，以准确显示每个数据包的传输路径。然而，现有的路径重建方案依赖于不同数据包之间的相关性，这导致了相当大的开销或准确性差。在物联网设备密集部署、资源约束和弱相关性的情况下，以负担得起的开销重建路径尤为困难。为此，我们提出了一种用于大规模物联网的低开销路径重建（LooP）。该方案利用了增量更新的特性，即每个节点只识别不同网关的单跳拓扑的变化。然后，网关节点根据报告的更改和历史信息迭代地恢复每个接收到的数据包的完整路径。在保证大规模动态拓扑网络重构的准确性的同时，消除了公共路径信息等冗余开销。我们分析了环路的信息熵和现有的几种方案，从理论上证明了我们的方案的优越性。实验结果还表明，环路的平均重建精度为98%，增益成本比至少为次优竞争对手的3倍。

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

IEEE Transactions on Network Science and Engineering Engineering-Control and Systems Engineering

CiteScore

12.60

自引率

9.10%

发文量

393

期刊介绍： The proposed journal, called the IEEE Transactions on Network Science and Engineering (TNSE), is committed to timely publishing of peer-reviewed technical articles that deal with the theory and applications of network science and the interconnections among the elements in a system that form a network. In particular, the IEEE Transactions on Network Science and Engineering publishes articles on understanding, prediction, and control of structures and behaviors of networks at the fundamental level. The types of networks covered include physical or engineered networks, information networks, biological networks, semantic networks, economic networks, social networks, and ecological networks. Aimed at discovering common principles that govern network structures, network functionalities and behaviors of networks, the journal seeks articles on understanding, prediction, and control of structures and behaviors of networks. Another trans-disciplinary focus of the IEEE Transactions on Network Science and Engineering is the interactions between and co-evolution of different genres of networks.