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An improved approximation algorithm for the shortest link scheduling in wireless networks under SINR and hypergraph models
Authors:Cui Wang  Jiguo Yu  Dongxiao Yu  Baogui Huang  Shanshan Yu
Institution:1.School of Information Science and Engineering,Qufu Normal University,Rizhao,China;2.Department of Computer Science,The University of Hong Kong,Pokfulam,China;3.School of Information Science and Engineering,Shandong University,Jinan,China
Abstract:Link scheduling is a fundamental problem in wireless ad hoc and sensor networks. In this paper, we focus on the shortest link scheduling (SLS) under Signal-to-Interference-plus-Noise-Ratio and hypergraph models, and propose an approximation algorithm \(SLS_{pc}\) (A link scheduling algorithm with oblivious power assignment for the shortest link scheduling) with oblivious power assignment for better performance than GOW* proposed by Blough et al. IEEE/ACM Trans Netw 18(6):1701–1712, 2010]. For the average scheduling length of \(SLS_{pc}\) is 1 / m of GOW*, where \(m=\lfloor \varDelta _{max}\cdot p \rfloor \) is the expected number of the links in the set V returned by the algorithm HyperMaxLS (Maximal links schedule under hypergraph model) and \(0<p<1\) is the constant. In the worst, ideal and average cases, the ratios of time complexity of our algorithm \(SLS_{pc}\) to that of GOW* are \(O(\varDelta _{max}/\overline{k})\), \(O(1/(\overline{k}\cdot \varDelta _{max}))\) and \(O(\varDelta _{max}/(\overline{k}\cdot m))\), respectively. Where \(\overline{k}\) (\(1<\overline{k}<\varDelta _{max}\)) is a constant called the SNR diversity of an instance G.
Keywords:
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