دانلود مقاله ISI انگلیسی شماره 70257
ترجمه فارسی عنوان مقاله

بهینه سازی متقابل لایه چند هدفه توزیع شده با لینک مشترک و برنامه ریزی حالت انتقال در شبکه های بی سیم مبتنی بر برنامه نویسی شبکه ☆

عنوان انگلیسی
Distributed multi-objective cross-layer optimization with joint hyperlink and transmission mode scheduling in network coding-based wireless networks ☆
کد مقاله سال انتشار تعداد صفحات مقاله انگلیسی
70257 2016 15 صفحه PDF
منبع

Publisher : Elsevier - Science Direct (الزویر - ساینس دایرکت)

Journal : Ad Hoc Networks, Volume 37, Part 2, February 2016, Pages 460–474

ترجمه کلمات کلیدی
چند هدفه؛ بهینه سازی متقابل لایه؛ الگوریتم توزیع شده؛ برنامه ریزی مشترک؛ برنامه نویسی شبکه
کلمات کلیدی انگلیسی
Multi-objective; Cross-layer optimization; Distributed algorithm; Joint scheduling; Network coding
پیش نمایش مقاله
پیش نمایش مقاله   بهینه سازی متقابل لایه چند هدفه توزیع شده با لینک مشترک و برنامه ریزی حالت انتقال در  شبکه های بی سیم مبتنی بر برنامه نویسی شبکه ☆

چکیده انگلیسی

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the wireless multihop networks, wherein an optimal solution could be practically approximated as its validity would be out-of-date soon in the error-prone wireless environment, our simulation results show that the distributed method can fulfill our requirements, and can make a good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.