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首页> 外文期刊>Simulation modelling practice and theory: International journal of the Federation of European Simulation Societies >An ant based multi constraints QoS aware service selection algorithm in Wireless Mesh Networks
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An ant based multi constraints QoS aware service selection algorithm in Wireless Mesh Networks

机译:无线网状网络中基于蚁群的多约束QoS感知服务选择算法

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摘要

Over the years, multihop Wireless Mesh Networks (WMNs) are providing cost effective services to the end users such as Video on demand (VoD), Voice over IP (VoIP), and Video conferencing in an efficient manner. Most of these services require an efficient service selection mechanism that can provide Quality of Service (QoS) in presence of various constraints such as delay, jitter, and service availability. In presence of these constraints, multi-constraint QoS aware service selection in WMNs is an NP-hard problem. In this paper, we propose an ant colony based multi constraints QoS aware service selection (QSS) algorithm. In the proposed algorithm, ants are launched from source node. The best path is chosen based upon the defined cost effective (CE) metric in presence of constraints. The constraints are chosen both from network and user perspectives. The goodness of the chosen path is determined by the CE metric. Moreover, ants are not launched randomly from the source node. They are launched based upon the guided search evaluation (GSE) criterion. This criterion is also used if the two paths have the same CE metric. The simulation results show that the proposed algorithm is more effective than the earlier improved ant colony QoS routing algorithm (IAQR) algorithm with respect to convergence, end-to-end delay (jitter), and service availability. Specifically, the service availability increases by 35-50% in the proposed QoS aware scheme compared to IAQR algorithm.
机译:多年来,多跳无线网状网络(WMN)以有效的方式为最终用户提供了经济高效的服务,例如视频点播(VoD),IP语音(VoIP)和视频会议。这些服务中的大多数都需要有效的服务选择机制,该机制可以在各种约束(例如延迟,抖动和服务可用性)存在的情况下提供服务质量(QoS)。在存在这些约束的情况下,WMN中的多约束QoS感知服务选择是一个NP难题。在本文中,我们提出了一种基于蚁群的多约束QoS感知服务选择(QSS)算法。在提出的算法中,蚂蚁是从源节点启动的。在存在约束的情况下,基于定义的成本效益(CE)指标选择最佳路径。从网络和用户的角度选择约束。所选路径的优劣由CE指标决定。而且,不会从源节点随机启动蚂蚁。它们是根据引导搜索评估(GSE)标准启动的。如果两条路径具有相同的CE指标,也将使用此标准。仿真结果表明,该算法在收敛性,端到端时延(抖动)和服务可用性方面比早期的改进蚁群QoS路由算法(IAQR)更有效。具体而言,与IAQR算法相比,在提出的QoS感知方案中,服务可用性提高了35-50%。

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