SoFA: An expert-driven, self-organization peer-to-peer semantic communities for network resource management

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.