Alleviation of void and energy hole in mobile cloud offloading using hybrid behavioral intelligence

In modern internet the usability of smart mobile devices is rapidly increased. It is not only used for commercial and communication purposes, it can be extended in the field like mobile health care, mobile learning, and mobile games. More access of smart mobile devices has a restriction due to resource constraint, this issue overwhelming via cloud computing. Heavy computations from mobile devices are offloaded to cloud and the application got executed. The problem occurs when the Electrogram data is entered into a mobile network in cloud environment which holds void and energy holes occurrences with heavy traffic and unbalanced load distribution.This paper aims to develop hybrid intelligence behavioural patterns for void and energy hole in mobile cloud offloading. The research work carried out in this paper extends its novelty in stage partitioning for concentric circles and sensor node distribution. The network area distribution of partitioning are uniformly distributed among void hole. The simulation results show the proposed approach produces high energy consumption in the mobile cloud paradigm.