数据融合及群迁移对MRHOF和OF0载荷分布的影响

IF 1.2 Q4 COMPUTER SCIENCE, INFORMATION SYSTEMS
Raad S. Al-Qassas, Malik Qasaimeh
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引用次数: 0

摘要

针对物联网提出的许多路由算法都是基于对RPL目标函数和涓流算法的修改。然而,缺乏深入研究移动性对基于MRHOF和OF0算法的路由协议的影响。本文研究了群体移动性对这些算法的影响,并通过使用著名的Cooja模拟器进行模拟,研究了它们在分配负载和不同流量影响方面的能力。对于低流量率和低移动速度的各种指标,这两种算法表现出相似的性能。但是,当业务量较大时,OF0的性能优势就显现出来了,表现在吞吐量、报文负载偏差、功率偏差、CPU功率偏差等方面。更高速度的移动性有助于MRHOF提高其吞吐量和负载偏差。可移动性允许MRHOF展示更好的数据包负载偏差。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Data Fusion and the Impact of Group Mobility on Load Distribution on MRHOF and OF0
Abstract Many routing algorithms proposed for IoT are based on modifications on RPL objective functions and trickle algorithms. However, there is a lack of an in-depth study to examine the impact of mobility on routing protocols based on MRHOF and OF0 algorithms. This paper examines the impact of group mobility on these algorithms, also examines their ability in distributing the load and the impact of varying traffic with the aid of simulations using the well-known Cooja simulator. The two algorithms exhibit similar performance for various metrics for low traffic rates and low mobility speed. However, when the traffic rate becomes relatively high, OF0 performance merits appear, in terms of throughput, packet load deviation, power deviation, and CPU power deviation. The mobility with higher speeds helps MRHOF to enhance its throughput and load deviation. The mobility allowed MRHOF to demonstrate better packets load deviation.
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来源期刊
Cybernetics and Information Technologies
Cybernetics and Information Technologies COMPUTER SCIENCE, INFORMATION SYSTEMS-
CiteScore
3.20
自引率
25.00%
发文量
35
审稿时长
12 weeks
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