Network selection using fuzzy logic

Abstract

The peer-to-peer technology offers many advantages, but at the same time, it poses many novel challenges for the research community. Modern peer-to-peer systems are characterized by large scale, poor reliability, and extreme dynamism of the participating nodes, with a continuous flow of nodes joining and leaving the systems. Selection of an optimal network requires estimation of its rank using attributes such as storage, average load, cost, reliability etc. There are multiple networks, each vying for users business by providing them novel services. The user in turn has to decide which network best meets its service requirements and accordingly join a network. In this paper, we propose a model with two ranking schemes, one being network-specific and the other user-specific. The schemes use fuzzy logic to rank different networks based on their attributes. The difference between the two ranking schemes lie in the dynamism offered by them. The user-specific ranking criteria is flexible while the network-specific scheme uses a fixed criteria. The network-specific scheme helps in providing a structure to visualize the overall performance index of the networks. The user-specific scheme is adaptive in the sense that it caters to the specific needs of the users. The simulations performed by us show that the two schemes are light-weight, highly accurate and easily implementable