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Maximal throughput scheduling based on the physical interference model using learning automata

机译:使用学习自动机基于物理干扰模型的最大吞吐量调度

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摘要

Wireless link scheduling is one of the major challenging issues in multi-hop wireless networks when they need to be designed in distributed fashion. This paper improves the general randomized scheduling method by using learning automata based framework that allows throughput optimal scheduling algorithms to be developed in a distributed fashion. A distributed scheduling algorithm that operates on more realistic conflict graph was proposed based on the physical interference model. This model uses a combination of a distributed learning automata based on the pick algorithm and an algorithm that compares successive scheduling solutions. Comparison was made by creating spanning tree on the conflict graph of the two consecutive schedules. Briefly, a distributed scheduling schemes was proposed, that: (i) is throughput optimal, (ii) intelligently choose links for new schedule, and (iii) message and time complexity is in O(n(3)). (C) 2016 Elsevier B.V. All rights reserved.
机译:当需要以分布式方式设计多跳无线网络时,无线链路调度是主要的挑战性问题之一。本文通过使用基于学习自动机的框架改进了通用随机调度方法,该框架允许以分布式方式开发吞吐量优化调度算法。基于物理干扰模型,提出了一种在更现实的冲突图上运行的分布式调度算法。该模型结合了基于挑选算法的分布式学习自动机和比较连续调度解决方案的算法。通过在两个连续计划的冲突图上创建生成树进行比较。简要地,提出了一种分布式调度方案,该方案是:(i)吞吐量最佳,(ii)为新调度智能地选择链路,(iii)消息和时间复杂度在O(n(3))中。 (C)2016 Elsevier B.V.保留所有权利。

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