Optimal Route Selection Using Hill Climbing Based Red Deer Algorithm in Vehicular Ad-Hoc Networks to Improve Energy Efficiency

K. Giridhar, C. Anbuananth, N. Krishnaraj
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Abstract

– One of the effective technologies that have been found useful in a number of real-time applications to increase the safety of roadways is called a vehicular ad hoc network, or VANET for short. In spite of the many advantages of the VANET, one of the most difficult aspects of this network is still the creation of an efficient routing protocol. The fact that VANET involves dynamic factors in its routing process makes it a difficult task to do successfully. It is possible to build a wide variety of route selection strategies in order to make efficient use of the available networking resources and to improve the efficacy of the routing. To achieve a higher level of resource utilization within VANET, the development of an efficient routing protocol is an absolute necessity. As a result of this impetus, the purpose of this research is to present an energy efficient hill climbing based red deer algorithm known as EEHC-RDA for use as an optimal route selection technique in VANET. In order to increase both the system's lifetime and its energy efficiency, the EEHC-RDA technique that has been presented prioritizes the selection of the most effective routes to the final destination. In addition, the EEHC-RDA method improves the convergence rate since it combines the mating behaviour of red deer with the hill climbing (HC) ideas. In addition to this, the EEHC-RDA method computes a fitness function for selecting the best possible routes, which takes into account a variety of input factors. In order to show that the EEHC-RDA approach offers a higher level of performance, a broad range of simulations are carried out. The outcomes of these simulations show that the suggested model has an enhanced performance in contrast to the existing methods in terms of a wide variety of different metrics, which demonstrates that the present state of approaches is not optimal.
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基于爬山马鹿算法的车辆自组织网络优化路径选择提高能源效率
在许多实时应用中,人们发现一种有效的技术可以提高道路的安全性,这种技术被称为车辆自组织网络,简称VANET。尽管VANET有许多优点,但该网络最困难的方面之一仍然是创建有效的路由协议。VANET在其路由过程中涉及到动态因素,这使得它很难成功完成。为了有效地利用现有的网络资源,提高路由的有效性,可以建立多种路由选择策略。为了在VANET中实现更高水平的资源利用率,开发有效的路由协议是绝对必要的。基于这种动力,本研究的目的是提出一种高效的基于马鹿的爬坡算法,称为EEHC-RDA,用于VANET的最优路线选择技术。为了提高系统的使用寿命和能源效率,EEHC-RDA技术优先选择通往最终目的地的最有效路线。此外,EEHC-RDA方法结合了马鹿的交配行为和爬山思想,提高了收敛速度。除此之外,EEHC-RDA方法还计算了一个适应度函数,用于选择考虑各种输入因素的最佳可能路径。为了证明EEHC-RDA方法提供了更高水平的性能,进行了广泛的仿真。这些模拟结果表明,与现有方法相比,所建议的模型在各种不同的指标方面具有增强的性能,这表明目前的方法状态不是最优的。
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来源期刊
International Journal of Computer Networks and Applications
International Journal of Computer Networks and Applications Computer Science-Computer Science Applications
CiteScore
2.30
自引率
0.00%
发文量
40
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