Copy limited flooding over opportunistic networks

Abstract

Mobile devices with local wireless interfaces can be organized into opportunistic networks which exploit communication opportunities arising from the movement of their users. For some occasions, such as tracking wild animals and communications at rural areas, opportunistic networks are a practical way to disseminate information. It is important to investigate message dissemination over opportunistic networks to maximize the potential of those networks. Traditional flooding is an optimal mechanism to disseminate messages over opportunistic networks if resource consumption is not considered. To overcome the weakness of traditional flooding, in this paper, we considered k-Copy Limited Flooding (k-CLF) over opportunistic networks where a node can forward no more than k copies of a message to its neighbors. To achieve this goal, we proposed a network model called Markov and Random graph Hierarchic Model (MRHM), where a node transfers among different Main-areas (places frequently visited by nodes according to the Markov rule), and two different nodes in the same Main-area can establish a connection with a certain probability. This model is able to reflect the social characteristics of nodes to some extent. We theoretically analyzed the performance of CLF over MRHM in terms of delivery ratio, buffer and energy consumption. Our extensive simulation results over synthetic and real traces show that if the buffer space and initial energy of nodes are sufficient, the performance of the 3-CLF algorithm is very close to that of traditional flooding, or else the 2-CLF algorithm performs best among all the schemes in terms of delivery ratio and resource consumption.