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Fuzzy Inference-based Super Peer Selection for a Practical Double-layered Mobile Peer-to-peer System
Kwang-Jo Lee, Jae-Ho Choi and Sung-Bong Yang

Mobile ad hoc networks have received increasing attention as mobile technology advances and more applications are developed. Mobile peer-to-peer (P2P) systems are becoming useful in mobile network applications where installation of infrastructure may be difficult or even infeasible. To realize a mobile P2P system, the double-layered mobile P2P systems that consider both the mobility and energy status of users were introduced. Although the double-layered systems significantly reduce the network traffic, they cannot adequately handle ever changing mobile environments, since they use a fixed mobility-to-energy ratio for hybridization in periodic reconfigurations of the network. Moreover, to determine the optimal fixed ratio, every possible ratio of the two factors should be examined before the system is implemented. In this paper, we propose a more practical mobile P2P system that utilizes a fuzzy method with both mobility and energy as the fuzzy inputs. During each reconfiguration of the network, the proposed system selects super peers adaptively using the fuzzy method to more effectively reflect the current environment. The performance of the proposed system was compared with those of the previous works on the Network Simulator NS-3. Our proposed fuzzy-based system achieves almost the same performance as the fixed ratio system that delivers the optimal performance. A large number of experiments are required to determine the optimal fixed ratio for every single environment.

Keywords: Peer-to-peer, mobility, energy, fuzzy, super peer, MANET

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