Optimal Node Selection in Mobile Cloud off Loading Using Hybrid Swarm Intelligence
S.K. Piramu Preethika1, R. Gobinath2
1S.K. Piramu Preethika, Research Scholar, Department of Computer Science, VISTAS, India.
2R. Gobinath, Assistant Professor, Department of Computer Science, VISTAS, India.
Manuscript received on 25 May 2019 | Revised Manuscript received on 03 June 2019 | Manuscript Published on 22 June 2019 | PP: 73-79 | Volume-8 Issue-3S, February 2019 | Retrieval Number: C10150283S19/19©BEIESP
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)

Abstract: Smart Mobile Devices engage and entertain all age group of the world all time all day long which leads to battery down problem. In order to avoid this issue mobile handshaking with powerful cloud is called as mobile cloud offloading. Earlier our work gave focus to send extracted electrocardiogram data packets from mobile to cloud in which void and energy holes were alleviated by partitioning into concentric circles and sensor node distribution using enhanced behavioural pattern. The research work carried out in this paper broadens its novelty by applying fitness value and selecting the best forwarding nodes using hybrid swarm intelligence. After the selection of strong forwarding nodes, the optimal path is discovered using fuzzy inference system, the energy is efficiently consumed and hence it avoids early energy depletion of sensor nodes closer to base station. Furthermore the optimal node transmitted the extracted Electrocardiogram data packets to healthcare centres.
Keywords: Mobile Cloud off Loading, Fuzzy Inference System, Sensor Nodes, Particle Swarm Optimization.
Scope of the Article: Mobile Computing