Mobile user-preference-based data dissemination on mobile P2P networks
A considerable number of studies have been performed recently on mobile peer-to-peer networks (MOPNETs), as the number of services based on mobile devices has increased. However, existing studies still reveal numerous shortcomings, such as bandwidth overhead, and redundant transmission in terms of multi-broadcast between peers. Especially, owing to the characteristics of MOPNETs, it is extremely important to determine broadcast size and to disseminate data within the limited environment of the network. The mechanism directly affects how well resource information in a mobile device is discovered and how data are transmitted. In this context, it is vital to efficiently disseminate data to be able to arrange hierarchal sequences of resource information of each mobile device for better search performance. Especially, it is also vital to determine the broadcast size, considering the consumption patterns of mobile users. In this article, we propose an adaptable algorithm that determines weighted values and disseminates data using the high-order Markov chain (HoMC). We apply weighted values in consideration of the MOPNET environment. In addition, the proposed HoMC-based Mobile User-preference-based Data Dissemination algorithm was simulated with a Qualnet simulator. Results show that the proposed algorithm performs 17.3% better, on average, in terms of data dissemination, than the existing dissemination methods.
mobile p2p networks high-order markov chain qualnet rank-based broadcast