ElePSO: energy aware elephant swarm optimization for Mobile Adhoc Network
The high pace increase in wireless mobile communication based applications have made Mobile Adhoc Network (MANET) an essential communication paradigm to ensure Quality of Service (QoS) provisioning. MANET characterizes itself with its decentralized network establishment nature and architectural dyna...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
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penseejournal.com
2014
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| Subjects: | |
| Online Access: | http://irep.iium.edu.my/36536/ http://irep.iium.edu.my/36536/ http://irep.iium.edu.my/36536/1/ElePSO_Energy_Aware_Elephant_Swarm_Optimization_for_Mobile_Adhoc_Network.pdf |
| Summary: | The high pace increase in wireless mobile communication based applications have made Mobile Adhoc Network (MANET) an essential communication paradigm to ensure Quality of Service (QoS) provisioning. MANET characterizes itself with its decentralized network establishment nature and architectural dynamicity. The predominant QoS parameters in MANETs are end-to-end delay, network throughput, overheads, network life time and others. The mobility and the lack of optimum resource sharing mechanism cause the QoS degradation in MANETs. The lifespan of any node deployed in Adhoc network is in proportion with the associated level of components and functions. Data drop and successive data regeneration also cause the exhaustion of energy in MANETs, resulting into reduced network lifetime. To achieve optimum resource sharing and energy conservation, in this paper a hybrid cross layered MAC optimization scheme has been developed for MANET’s real time applications. Specifically an optimization approach based on Elephant swarm behaviour named ElePSO has been proposed to optimize the node life time and throughput. As, CSMA/CA protocol is not effective for multihop data transmissions, so the proposed ElePSO scheme has been incorporated with TDMA-MAC to ensure energy aware communication. Simulation results show that the proposed ElePSO outperforms other bio-inspired optimization techniques like (Particle Swarm Optimization) PSO and (Ant Colony Optimization) ACO. ElePSO exhibits 73.56% higher active nodes as compared to PSO and while bearing36.6% lower communication overhead.
Keywords: MANETs, Cross layering, PSO, ACO, TDMA-MAC, OLSR
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