Enhancing Resource Sharing in Mobile Networks Using Social Relations

Abstract

A Mobile Ad hoc Network (MANET) is a dynamic wireless network without fixed infrastructure. Nodes move freely and organize themselves arbitrarily, and they usually have limited resources. Therefore, data sharing through this network requires cooperation among network nodes. Data sharing can be categorized to unicast and multicast. In unicast, data is shared from one source to one destination but, in multicast data is shared from one source to more than one destination. In this work, there are two challenging problems in data sharing, selfishness and data dissemination. Selfishness is a challenging problem in the data delivery process through the network. A selfishness detect-and-motivate (SDM) approach is proposed to detect selfish nodes and motivate them to cooperate in data delivery. The other challenging problem is disseminating data efficiently. We use the influential user’s concept and the social relations of users. The influential user term is described as a user that have an effective activity in the network and influence on the other users. Detecting influential nodes is useful in many applications. The detection process of influential nodes is dramatically affected by the participation behavior of the other nodes. Selfish nodes who selectively disseminate information in the network may reduce the influence of the other nodes. In this thesis, influential nodes detection is proposed taking into consideration the negative effects of different patterns of selfish behavior. A C# based simulator is used to simulate a MANET and implement the proposed approach. Using the simulator, we compare our protocols with others under different scenarios to prove our performance. The proposed protocols achieve up to 40% efficiency in each scenario.