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An efficient QoS routing algorithm for solving MCP in ad hoc networks

机译:一种解决ad hoc网络中MCP的高效QoS路由算法

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摘要

Providing guaranteed quality of service (QoS) in wireless networks is a key issue for deploying multimedia applications. To support such a QoS, an arduous problem concerning how to find a feasible end to end path to satisfy multiple QoS constraints should be studied. In general, multi-constrained path selection, with or without optimization, is an NP-complete problem that cannot be exactly solved in polynomial time. Approximation algorithms and heuristics with polynomial and pseudo-polynomial time complexities are often used to deal with this problem. However, existing solutions suffer either from excessive computational complexities that cannot be used for multimedia applications in ad hoc networks characterized by mobility and performance constraints (e.g., limited energy, wireless medium, etc.). Recently a promising heuristic algorithm H_MCOP using a non linear Lagrange relaxation path functions has demonstrated an improvement in its success rate and in finding feasible paths. However, the H_MCOP is not suitable for ad hoc networks and has not exploited the full capability that a Lagrange relaxation could offer. In this paper, we propose an efficient multi-constrained path heuristic called E_MCP, which exploits efficiently the Lagrange relaxation and enhances the path search process to be adequate to mobile ad hoc networks. Using extensive simulations on random mobile network with correlated and uncorrelated link weights, we show that the same level of computational complexity, E_MCP can achieve a higher success ratio of finding feasible paths.
机译:在无线网络中提供有保证的服务质量(QoS)是部署多媒体应用程序的关键问题。为了支持这样的QoS,应该研究关于如何找到满足多个QoS约束的可行的端到端路径的艰巨问题。通常,有或没有优化的多约束路径选择是一个NP完全问题,无法在多项式时间内精确解决。通常使用具有多项式和伪多项式时间复杂度的近似算法和启发式方法来处理此问题。然而,现有解决方案遭受过大的计算复杂性的困扰,而这些计算复杂性不能用于以移动性和性能约束(例如,有限的能量,无线介质等)为特征的自组织网络中的多媒体应用。最近,使用非线性拉格朗日松弛路径函数的有希望的启发式算法H_MCOP已证明其成功率和寻找可行路径的改进。但是,H_MCOP不适合用于ad hoc网络,还没有利用Lagrange松弛可以提供的全部功能。在本文中,我们提出了一种有效的多约束路径启发式方法,称为E_MCP,该方法有效地利用了Lagrange松弛并增强了路径搜索过程以适合移动自组织网络。通过在具有相关和不相关链路权重的随机移动网络上进行广泛的仿真,我们表明,在相同的计算复杂度下,E_MCP可以找到找到可行路径的更高成功率。

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