An Energy Aware Cellular Learning Automata Based Routing Algorithm for Opportunistic Networks | Zendy

Feng Zhang | Zendy; Xiaoming Wang | Zendy; Peng Li | Zendy; Lichen Zhang | Zendy

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An Energy Aware Cellular Learning Automata Based Routing Algorithm for Opportunistic Networks

Author(s) -

Feng Zhang,

Xiaoming Wang,

Peng Li,

Lichen Zhang

Publication year - 2016

Publication title -

international journal of grid and distributed computing

Language(s) - English

Resource type - Journals

eISSN - 2207-6379

pISSN - 2005-4262

DOI - 10.14257/ijgdc.2016.9.2.22

Subject(s) - computer science , learning automata , routing algorithm , cellular automaton , routing (electronic design automation) , computer network , energy (signal processing) , distributed computing , automaton , algorithm , routing protocol , theoretical computer science , statistics , mathematics

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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