基于遗传算法的机动网络能量和机动性感知路径优化技术

Q4 Business, Management and Accounting
G. Mathiyalagan, A. Wahi
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引用次数: 3

摘要

由于在移动自组织网络(manet)中,节点高度移动并且依赖电池容量运行,因此电池消耗和节点的移动性构成了主要问题。为了解决这个问题,每个节点消耗的能量应该平均分配,从而使总传输功率最小化。为了实现这一目标,本文提出了一种基于遗传算法的能量和机动性感知路径优化技术。在这种方法中,网络估计估计的几何距离(EGD)度量。在这里,薄弱环节被排除在网络之外。然后,对最小-最大电池容量和节点连通性指标进行估计。基于这些指标,应用遗传算法选择具有最佳适应度函数的路线。仿真结果表明,该方法降低了时延和开销,提高了分组传输率和剩余能量。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Energy and mobility aware route optimisation technique based on genetic algorithm in MANETs
Due to the fact that in mobile ad hoc networks (MANETs), nodes being highly mobile and operate on battery capacity, battery consumption and mobility of the nodes pose as major issues. To resolve this issue, the energy consumed by each node should be distributed equally thereby minimising the overall transmission power. In order to achieve this, an energy and mobility aware route optimisation technique based on genetic algorithm has been proposed in this paper. In this approach, the network estimates the estimated geometrical distance (EGD) metric. Here, the weak links are excluded from the network. Then, an estimation of min-max battery capacity and node connectivity index is done. Genetic algorithm is applied for selecting the routes with a best fitness function based on these metrics. Based on the simulation results, we gather that the proposed technique reduces delay and overhead along with the increased packet delivery ratio and residual energy.
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来源期刊
International Journal of Mobile Network Design and Innovation
International Journal of Mobile Network Design and Innovation Business, Management and Accounting-Management Information Systems
CiteScore
0.30
自引率
0.00%
发文量
0
期刊介绍: The IJMNDI addresses the state-of-the-art in computerisation for the deployment and operation of current and future wireless networks. Following the trend in many other engineering disciplines, intelligent and automatic computer software has become the critical factor for obtaining high performance network solutions that meet the objectives of both the network subscriber and operator. Characteristically, high performance and innovative techniques are required to address computationally intensive radio engineering planning problems while providing optimised solutions and knowledge which will enhance the deployment and operation of expensive wireless resources.
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