计算机科学 ›› 2018, Vol. 45 ›› Issue (6): 105-110.doi: 10.11896/j.issn.1002-137X.2018.06.018
侯林清, 蔡英, 范艳芳, 夏红科
HOU Lin-qing, CAI Ying, FAN Yan-fang, XIA Hong-ke
摘要: 节点对路由消息的存储-携带-转发是移动社交网中的一种短距离通讯方式,传输性能是影响用户交互体验的关键因素,如果用户能够根据彼此间的兴趣或社区来进行消息传输,则可提高传输性能。目前,针对移动社交网中的短距离通讯,已有的研究主要是基于兴趣或者基于社区的传输方式。为了使用户得到更好的交互体验,将用户兴趣与社区相结合,提出基于兴趣社区的消息传输方案InComT(Interest Community based Transmission)。对移动社交网中单个节点的兴趣进行度量,根据得出的节点兴趣值进行社区划分,从而确定社区整体的兴趣值,并根据兴趣值来选择中继社区和中继节点,实现消息的传输。仿真结果表明,该策略在传输负载率和平均延时较低的情况下能够拥有较高的传输成功率。
中图分类号:
[1]Index,Cisco Visual Networking.Global Mobile Data Traffic Forecast Update 2015-2020 White Paper[OL].https://www.cisco.com/go/offices. [2]HU X,CHU T H S,LEUNG V C M,et al.A survey on mobile social networks:Applications,platforms,system architectures,and future research directions [J].IEEE Communications Surveys & Tutorials,2015:1557-1581. [3]VASTARDIS N,YANG K.Mobile social networks:Architectures,Social properties,and Key Research Challenges[J].IEEE Communications Surveys & Tutorials,2013,15(3):1355-1371. [4]ZHU Y,XU B,SHI X,et al.A survey of social based routing in delay tolerant networks:Positive and negative social effects[J].IEEE Communications Surveys & Tutorials,2013,15(1):387-401. [5]NEWMAN M E J.Fast algorithm for detecting community structure in networks[J].Physical Review E,2003,69(6 Pt 2):066133. [6]HUI P,YONEKI E,CHAN S Y,et al.Distributed community detection in delay tolerant networks[C]//Workshops -2nd ACM International Workshop on Mobility in the Evolving Internet Architecture.2007:1-8. [7]NGUYEN N P,DINH T N,TOKALA S,et al.Over-lapping communities in dynamic networks:their detection and mobile applications[C]//Proceedings of the 17th Annual International Conference on Mobile Computing and Networking.ACM,2011:85-96. [8]FORTUNATO S,CASTELLANO C.Community structure in graphs [M].New York:Springer,2012. [9]MACROPOL K,SINGH A.Scalable discovery of best clusters on largegraphs[C]//Proc.VLDB Endow..2010:693-702. [10]XIE J R,SZYMANSKI B K,LIU X M.Slpa:Uncovering overlapping communities in social networks via a speaker-listenerinteraction dynamic process[C]//Data Mining Workshops (ICDMW).IEEE 11th International Conference,2011:344-349. [11]WILLIAMS M J,WHITAKER R M,ALLEN S M.Decentralised detection of periodic encounter communities in opportu-nistic networks[C]//Ad Hoc Networks.2012:1544-1556. [12]CHEN Q,WU T T,FANG M.Detecting local community structures in complex networks based on local degree central nodes[J].Physica A Statistical Mechanics and Its Applications,2013,392(3):529-537. [13]RHOUMA D,ROMDHANE L B.An efficient algorithm for community mining with overlap in social networks[J].Expert Systems with Applications,2014,41(9):4309-4321. [14]WEI K,LIANG X,XU K.A survey of social-aware routing protocols in delay tolerant networks:applications,taxonomy and design-related issues[J].IEEE Communications Surveys & Tutorials,2014,16(1):556-578. [15]ZHANG X,NEGLIA G,KUROSE J,et al.Performance modeling of epidemic routing[J].Computer Networks,2007, 51(10):2867-2891. [16]LINDGREN A,DORIA A,SCHELEN O.Probabilistic routing in intermittently connected networks [M]//Service assurance with partial and intermittent resources.2004:239-254. [17]SPYROPOULOS T,PSOUNIS K,RAGHAVENDRA C S. Spray and wait:an efficient routing scheme for inter- mittently connected mobile networks [C]//Proceedings of the ACM SIGCOMM Workshop.2005:252-259. [18]DALY E M,HAAHR M.Social network analysis for routing in disconnected delay-tolerant manets [C]//Proceedings of the 8th ACM International Symposium on Mobile Ad hoc Networking and Computing.ACM,2007:32-40. [19]HUI P,CROWCROFT J,YONEKI E.Bubble Rap:Social-based Forwarding in Delay Tolerant Networks[C]//ACM MobiHoc.2008. [20]GAO W,LI Q,ZHAO B,et al.Multicasting in delay tolerant networks:a social network perspective [C]//Tenth ACM International Symposium on Mobile Ad hoc Networking and Computing.ACM,2009:299-308. [21]IOANNIDIS S,CHAINTREAU A,MASSOULIÉ L.Optimal and scalable distribution of content updates over a mobile social network[C]//INFOCOM.2009:1422-1430. [22]MOGHADAM A,SCHULZRINNE H.Interest-aware content distribution protocol for mobile disruption-tolerant networks[C]//IEEE International Symposium.2009:1-7. [23]MTIBAA A,MAY M,DIOT C,et al.Peoplerank:Social opportunistic forwarding[C]//Infocom Proceedings IEEE.2010:1-5. [24]HUI P,CROWCROFT J,YONEKI E.Bubble-rap:Social-based forwarding in delay-tolerant networks [J].IEEE Transactions on Mobile Computing,2011,10(11):1576-1589. [25]GAO W,CAO G.User-centric data dissemination in disruption tolerant networks [C]//INFOCOM IEEE.2011:3119-3127. [26]LIN K C J,CHEN C W,CHOU C F.Preference aware content dissemination in opportunistic mobile social networks[C]//INFOCOM Proceedings IEEE.2012:1960-1968. [27]WU J,WANG Y.Social feature-based multi-path routing in delay tolerant networks[C]//INFOCOM Proceedings IEEE.2012:1368-1376. [28]XU Y,CHEN X.Social-similarity-based multicast algorithm inimpromptu mobile social networks[C]//Global Communications Conference (GLOBECOM).IEEE,2014:346-351. [29]DIDWANIA A,NARMAWALA Z.A comparative study of various community detection algorithms in the mobile social network[C]//Engineering Nui- CONE 5th Nirma University International Conference.IEEE,2015:1-6. [30]MAO Z,JIANG Y,MIN G,et al.Mobile social networks:Design requirements,architecture,and state-of-the-art technology [J].Computer Communications,2016,100:1-19. |
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