SoFA: An expert-driven,self-organization peer-to-peer semantic communities for network resource management |
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| Authors: | Li Wang |
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| Affiliation: | 1. Collaborative Autonomic Computing Laboratory, School of Computer Science, University of Electronic Science and Technology of China, China;2. The Israel Electric Corporation, P.O. Box 10, Haifa 31000, Israel;3. University of Massachusetts, Dartmouth, MA 02747, USA;4. Parametric Technology Corporation, Greensburg, PA 15601, USA;1. Dept. of Computer Science and Engineering, Konkuk University, Seoul, Republic of Korea;2. Center for Experimental Research in Computer Systems, Georgia Institute of Technology, Atlanta, GA, USA;1. Department of Computer Science, Yangzhou University, Yangzhou 225009, China;2. State Key Lab of Novel Software Tech., Nanjing University, Nanjing 210093, China;1. School of Geodesy and Geomatics, Wuhan University, Wuhan 430079, China;2. National Astronomical Observatories, Chinese Academy of Sciences, Beijing 100012, China;3. Shanghai Astronomical Observatory, Chinese Academy of Sciences, Shanghai 200030, China;4. GNSS Research Center, Wuhan University, Wuhan 430079, China;5. Institute of Geodesy, University of Stuttgart, Stuttgart 70174, Germany;1. Institute of Systems Engineering, Dalian University of Technology, Dalian, Liaoning 116024, China;2. College of Software, Dalian University of Foreign Languages, Dalian, Liaoning 116044, China |
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| Abstract: | According to the peer-to-peer (P2P) sociality, an expert-driven multi-semantic self-organized P2P semantic community model is built in this paper to resolve the two principle problems of P2P resource management, which are how to possess enormous number of high quality shared resource, how to find the resource quickly and accurately. The main contribution of this paper is: ① the autonomous peer (AP) model and Autonomic Semantic Community (ASC)model are build, ② one local domain-related trust and trusted evaluation is projected that bases on semantic similarity, history evaluation and time effect and it takes the requirement and owned resource two aspects into account to present one AP. ③ an algorithm of fusing APs’local trust degree and self-evaluation is designed.④ a procedure to collaboratively elect expert APe is proposed. ⑤ Self-organized community formation algorithm SoFA and its communication mechanism are built. In SoFA, APs gather its communication information and according to it to evaluate itself and other APs locally, build and dynamically adjust local topology, elect the domain expert APe and then an expert-driven ASC is established. Experiment shows our domain trust evaluation and self-evaluation mechanism and SoFA could not only adaptively optimize network to improve the efficiency of service (resource) discovery but also base on the synthesized trust degree to find the free-riders, malice peers, low quality service peers and to keep them within limits. |
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