Abstract
Message transmission in opportunistic networks is accomplished via the encounters of mobile nodes while moving around. The distributing of nodes greatly impacts the performance of message delivery ratio due to their sparse encounter opportunities. Nodes with exhaust energy can’t participate in message transfer process. So it is very meaningful to make nodes energetic and balance the energy consumption between nodes. In this paper, a novel dynamic irregular cellular multiple learning automata (DICMLA) model and the corresponding routing algorithm are proposed to optimize the energy consumption of nodes. The proposed routing algorithm utilizes the characteristics of cellular learning automata to reduce the energy consumption of nodes and improve the delivery ratio of message transmission. The simulation results show that the proposed algorithm can obviously balance energy consumption of nodes and thus prolong the lifetime of the network.
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