FlexRout: Dynamic Routing in Blockchain Networks

IF 7.9 2区计算机科学 Q1 ENGINEERING, MULTIDISCIPLINARY IEEE Transactions on Network Science and Engineering Pub Date : 2024-12-25 DOI:10.1109/TNSE.2024.3519802

Souradeep Das;Riya Tapwal;Sudip Misra

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Abstract

Blockchain is highly dependent on network topology and routing paths for efficient operation. The speed and effectiveness of mining are impacted by network topology, as a well-defined routing path improves the speed of mining by the faster exchange of data for verification. However, high traffic on the path, caused by the exchange of messages among the miners leads to delays in the routing path and lengthens the time needed for mining data. Moreover, the dynamic addition and termination of miners from the network affect the topology, further contributing to delays in the mining process and transactions. To address these challenges, we present a novel system called FlexRout that dynamically predicts the optimal routing path to increase the speed of the mining process. It firstly predicts miners (nodes) who can leave mining by checking their resource availability. Simultaneously, it also grants a reward or a penalty depending upon the right or wrong prediction made respectively. Experimental results demonstrate that FlexRout can significantly reduce traffic by almost 49% and latency by 50%.

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flexroute：区块链网络中的动态路由

区块链高度依赖于网络拓扑和路由路径，以实现高效运行。挖掘的速度和有效性受到网络拓扑结构的影响，因为定义良好的路由路径通过更快地交换用于验证的数据来提高挖掘的速度。然而，由于矿工之间的消息交换导致路径上的高流量导致路由路径延迟，并延长了挖掘数据所需的时间。此外，网络中矿工的动态加入和终止会影响拓扑结构，进一步导致挖掘过程和交易的延迟。为了应对这些挑战，我们提出了一个名为flexroute的新系统，该系统可以动态预测最佳路由路径，以提高挖矿过程的速度。它首先通过检查资源可用性来预测哪些矿工（节点）可以离开挖矿。同时，它还根据预测的正确或错误分别给予奖励或惩罚。实验结果表明，flexroute可以显著减少49%的流量和50%的延迟。

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.