Bio-inspired Seamless Vertical Handover Algorithm for Vehicular Ad Hoc Networks

Mohanad M. Abdulwahhab, M. Rasid, F. Hashim
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引用次数: 2

Abstract

One of the most important factors to implement VANET is by considering the variety of wireless networks available around the city as well as the vehicles traffic scenarios. However, by providing a diverse range of wireless access technologies, it is necessary to provide continuous network connectivity as well as selecting the most suitable network technology and performance. Many researchers have worked on building algorithms for selecting the best network to improve the handover process. However, with high-speed vehicles mobility, the vertical handover process became the most challenging task in order to achieve realtime network selection. This paper proposes a bio-inspired network selection algorithm influenced by insect's behaviour which combines Artificial Bee Colony (ABC) and Particle Swarm Optimization (PSO). The proposed algorithm is applied to process multi-criteria parameters to evaluate the best available network and then execute the handover process seamlessly. The results demonstrate the benefits of the proposed Multi-Criteria ABC-PSO method by reducing the handover decision delays by 25%. It gives the optimum performance in terms of network selections and reduces the handover latency by 14.5%. The proposed algorithm also reduces the number of unnecessary handovers by 48% for three different mobility scenarios based on traffic environments (highway, urban and traffic jam).
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基于仿生的车载Ad Hoc网络无缝垂直切换算法
实现VANET最重要的因素之一是考虑城市周围可用的各种无线网络以及车辆交通场景。然而,通过提供多样化的无线接入技术,有必要提供连续的网络连接以及选择最合适的网络技术和性能。许多研究人员致力于构建算法来选择最佳网络以改善切换过程。然而,随着车辆的高速移动,为了实现实时网络选择,垂直切换过程成为最具挑战性的任务。结合人工蜂群算法和粒子群算法,提出了一种受昆虫行为影响的仿生网络选择算法。该算法用于处理多准则参数,以评估最佳可用网络,然后无缝地执行切换过程。结果表明,多准则ABC-PSO方法可将切换决策延迟降低25%。它在网络选择方面提供了最佳性能,并将切换延迟降低了14.5%。在基于交通环境(高速公路、城市和交通堵塞)的三种不同移动场景中,该算法还将不必要的换车次数减少了48%。
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