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      Challenges on Probabilistic Modeling for Evolving Networks

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          Abstract

          With the emerging of new networks, such as wireless sensor networks, vehicle networks, P2P networks, cloud computing, mobile Internet, or social networks, the network dynamics and complexity expands from system design, hardware, software, protocols, structures, integration, evolution, application, even to business goals. Thus the dynamics and uncertainty are unavoidable characteristics, which come from the regular network evolution and unexpected hardware defects, unavoidable software errors, incomplete management information and dependency relationship between the entities among the emerging complex networks. Due to the complexity of emerging networks, it is not always possible to build precise models in modeling and optimization (local and global) for networks. This paper presents a survey on probabilistic modeling for evolving networks and identifies the new challenges which emerge on the probabilistic models and optimization strategies in the potential application areas of network performance, network management and network security for evolving networks.

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          Author and article information

          Journal
          2013-04-29
          2013-05-04
          Article
          1304.7820
          7c870101-aa61-45e8-b02b-144b11c955ae

          http://arxiv.org/licenses/nonexclusive-distrib/1.0/

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          Custom metadata
          18 pages. Book chapter. arXiv admin note: text overlap with arXiv:1012.0009 by other authors
          cs.SI cs.AI physics.soc-ph

          Social & Information networks,General physics,Artificial intelligence
          Social & Information networks, General physics, Artificial intelligence

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