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Multi-constraint QoS Unicast Routing Using Genetic Algorithm (MURUGA)

机译:使用遗传算法(MURUGA)的多约束QoS单播路由

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摘要

The current Internet architecture supports best-effort data delivery by default, which has provided satisfactory services for various applications, such as the email and file transfer, to a great extent. On the other hand, the increase in real-time multimedia applications such as voice over IP, audio, and video streaming in the public Internet demand for a Quality of Service (QoS) routing that satisfies multiple constraints such as bandwidth, delay, delay jitter, packet loss, and cost. To find a feasible path satisfying multiple constraints is NP-complete. Hence the recent researches on QoS based routing have triggered the proposition of many heuristic QoS routing algorithms. Most of these heuristics find a path subject to relaxed constraints, which may result in some feasible paths being not retrieved. To search all feasible paths in less time, many researchers have used the concept of Genetic Algorithm (GA), which is a new computational strategy inspired by natural processes. The aim of these routing algorithms is to aid the fast selection of a route, which should be adaptive, flexible, and intelligent for efficient network management. But in all these algorithms only one constraint or single mixed constraint has been considered. The focus of this paper is to develop a GA based routing algorithm that satisfies multiple constraints of the multimedia applications. Hence, in this paper a heuristic called Multi-constraint QoS Unicast RoutingUsing Genetic Algorithm (MURUGA), which incorporates multiple constraints required by multimedia applications to find the feasible path satisfying the constraint requirement has been proposed, designed, and simulated. The performance analysis of MURUGA has also been carried out and compared with the existing algorithms. The results confirm that MURUGA performs better in terms of time taken to return feasible paths.
机译:当前的Internet体系结构默认情况下支持尽力而为的数据传递,它在很大程度上为各种应用程序提供了令人满意的服务,例如电子邮件和文件传输。另一方面,诸如公共IP上的IP语音,音频和视频流之类的实时多媒体应用的增加,也需要满足带宽,延迟,延迟抖动等多种约束的服务质量(QoS)路由。 ,封包丢失和成本。寻找一个满足多重约束的可行路径是NP完成的。因此,基于QoS路由的最新研究触发了许多启发式QoS路由算法的提出。这些启发式方法中的大多数都找到了受宽松约束约束的路径,这可能会导致无法检索到某些可行的路径。为了在更短的时间内搜索所有可行的路径,许多研究人员使用了遗传算法(GA)的概念,这是一种受自然过程启发的新计算策略。这些路由算法的目的是帮助快速选择路由,路由应具有自适应性,灵活性和智能性,以进行有效的网络管理。但是在所有这些算法中,仅考虑了一个约束或单个混合约束。本文的重点是开发一种基于GA的路由算法,该算法可满足多媒体应用程序的多个约束。因此,本文提出,设计和仿真了一种启发式算法,称为多约束QoS单播路由使用遗传算法(MURUGA),该算法结合了多媒体应用程序所需的多个约束条件,以找到满足约束条件要求的可行路径。还对MURUGA进行了性能分析,并与现有算法进行了比较。结果证实,MURUGA在返回可行路径所花费的时间方面表现更好。

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