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Distributed multi-objective cross-layer optimization with joint hyperlink and transmission mode scheduling in network coding-based wireless networks

机译:基于网络编码的无线网络中具有联合超链接和传输模式调度的分布式多目标跨层优化

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In this work, we address a cross-layer multi-objective optimization problem of maximizing network lifetime and optimizing aggregate system utility with intra-flow network coding, solved in a distributed manner. Based on the network utility maximization (NUM) framework, we resolve this problem to accommodate routing, scheduling, and stream control from different layers in the coded networks. Specially, we consider that there are two scheduling primitives, namely hyperlink and transmission mode, to be concurrently activated for the multi-objective optimization. Given the constraints with respect to these primitives, the optimization problem is specifically formulated as a quadratically constrained quadratic programming (QCQP) problem that is NP-hard in general, and its scheduling subproblem even when reduced to account for only one of these primitives is a maximum weighted independent set (MWIS) problem that is NP-hard already. To alleviate this complex problem in a distributed manner, we resort to alternate convex search (ACS) and primal decomposition (PD) to approximate the optimal results by using biconvex programming model and subgradient-based algorithm that can iteratively approach to the optimal solution. For the wireless multihop networks, wherein an optimal solution could be practically approximated as its validity would be out-of-date soon in the error-prone wireless environment, our simulation results show that the distributed method can fulfill our requirements, and can make a good trade-off on the heterogeneous objectives with well computational efficiency. (C) 2015 Elsevier B.V. All rights reserved.
机译:在这项工作中,我们解决了一个跨层多目标优化问题,该问题以流内网络编码最大化网络寿命并优化聚合系统效用,以分布式方式解决。基于网络实用程序最大化(NUM)框架,我们解决了此问题,以适应来自编码网络不同层的路由,调度和流控制。特别地,我们认为有两个调度原语,即超链接和传输模式,要同时激活以进行多目标优化。给定相对于这些原语的约束,优化问题专门公式化为通常是NP-hard的二次约束二次规划(QCQP)问题,即使仅考虑其中一个原语,其调度子问题也是最大加权独立集(MWIS)问题已经是NP问题了。为了以分布式方式缓解此复杂问题,我们采用双凸规划模型和基于次梯度的算法来迭代地求最佳解,从而求助于交替凸搜索(ACS)和原始分解(PD)来逼近最优结果。对于无线多跳网络,在易出错的无线环境中,最佳解决方案的有效性很快就会过时,因此可以实际估算出最佳解决方案,我们的仿真结果表明,该分布式方法可以满足我们的要求,并且可以使在异构目标上进行良好的权衡,并具有良好的计算效率。 (C)2015 Elsevier B.V.保留所有权利。

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