2014 IEEE 34th International Conference on Distributed Computing Systems最新文献

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Adaptive Partitioning for Large-Scale Dynamic Graphs 大规模动态图的自适应分区

2014 IEEE 34th International Conference on Distributed Computing Systems Pub Date : 2013-09-04 DOI: 10.1145/2523616.2525943

Luis M. Vaquero, F. Cuadrado, Dionysios Logothetis, Claudio Martella

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引用次数: 65

Almost Optimal Channel Access in Multi-Hop Networks with Unknown Channel Variables 信道变量未知的多跳网络中的几乎最优信道接入

2014 IEEE 34th International Conference on Distributed Computing Systems Pub Date : 2013-08-21 DOI: 10.1109/ICDCS.2014.54

Yaqin Zhou, Xiangyang Li, Fan Li, Min Liu, Zhongcheng Li, Zhiyuan Yin

{"title":"Almost Optimal Channel Access in Multi-Hop Networks with Unknown Channel Variables","authors":"Yaqin Zhou, Xiangyang Li, Fan Li, Min Liu, Zhongcheng Li, Zhiyuan Yin","doi":"10.1109/ICDCS.2014.54","DOIUrl":"https://doi.org/10.1109/ICDCS.2014.54","url":null,"abstract":"We consider the problem of online dynamic channel accessing in multi-hop cognitive radio networks. Previous works on online dynamic channel accessing mainly focus on single-hop networks that assume complete conflicts among all secondary users. In the multi-hop multi-channel network settings studied here, there is more general competition among different communication pairs. A simple application of models for single-hop case to multi-hop case with N nodes and M channels leads to exponential time/space complexity O (MN), and poor theoretical guarantee on throughput performance. We thus novelly formulate the problem as a linearly combinatorial multi-armed bandits (MAB) problem that involves a maximum weighted independent set (MWIS) problem with unknown weights. To efficiently address the problem, we propose a distributed channel access algorithm that can achieve 1/ρ of the optimum averaged throughput where each node has communication complexity O (r2+D) and space complexity O (m) in the learning process, and time complexity O (D mρr) in strategy decision process for an arbitrary wireless network. Here ρ = 1 + ε is the approximation ratio to MWIS for a local r-hop network with m <; N nodes, and D is the number of mini-rounds inside each round of strategy decision.","PeriodicalId":170186,"journal":{"name":"2014 IEEE 34th International Conference on Distributed Computing Systems","volume":"14 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-08-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127072189","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 15

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