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

被引:1
作者
Liu, Jain-Shing [1 ]
Tsai, Jichiang [2 ,3 ]
机构
[1] Providence Univ, Dept Comp Sci & Informat Engn, Taichung, Taiwan
[2] Natl Chung Hsing Univ, Dept Elect Engn, Taichung 40227, Taiwan
[3] Natl Chung Hsing Univ, Grad Inst Commun Engn, Taichung 40227, Taiwan
关键词
Multi-objective; Cross-layer optimization; Distributed algorithm; Joint scheduling; Network coding; MAXIMUM THROUGHPUT; TRADE-OFF; MULTICAST; DESIGN; DECOMPOSITION; ALGORITHM; TUTORIAL;
D O I
10.1016/j.adhoc.2015.09.007
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
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the wireless multihop networks, wherein an optimal solution could be practically approximated as its validity would be out-of-date soon in the error-prone wireless environment, our simulation results show that the distributed method can fulfill our requirements, and can make a good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.
引用
收藏
页码:460 / 474
页数:15
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