PDAU:一种新的自组网路由策略

Q4 Business, Management and Accounting
Sandeep Raskar, K. Iyer
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引用次数: 1

摘要

一般来说,路由是为一个网络或多个网络中的流量选择路径的过程。路由策略通常与最短路径路由(SPR)问题有关。许多路由模型已经在进行中,但是在一些实际应用中仍然存在挑战。这种路由策略给人的印象是通过考虑延迟、能量和总适应度来解决这些问题。本文提出了一种新的路由算法来解决路由建立和路由恢复所面临的问题。本文还利用神经网络模型对自组织网络中的节点运动进行预测。更重要的是,本文通过引入一种新的混合算法来解决主要的最优路径选择问题。提出了一种基于概率的基于人工蜂群(ABC)更新的蜻蜓(DA)模型,该模型在延迟、能量和总适应度方面与其他传统方法进行了比较。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
PDAU: a new exploitation of routing strategy in adhoc network
Generally, routing is the process of selecting a path for traffic in a network, or across multiple networks. The routing strategy usually struck with the issue of shortest path routing (SPR). A number of routing models is already in progress but, still the challenges rise with some real-world applications. This routing strategy impresses to focus on solving these issues by considering delay, energy and total fitness. This paper introduces a new routing algorithm for solving the issues faced in route establishment and route recovery as well. This paper also uses neural network (NN) model to predict the node movements in adhoc network. More importantly, the major optimal route selection problem is solved here by introducing a new hybrid algorithm. The proposed model, probability-based dragonfly (DA) with artificial bee colony (ABC) update (PDAU) compares its performance over other conventional methods in terms of delay, energy and total fitness.
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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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