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A New Context-Sensitive Decision Making System for Mobile Cloud Offloading
Recently, with the rapid spread use of mobile devices, some problems have begun to emerge. The most important of these are that the mobile devices batteries’ life may be short and that these devices may be in some cases. The complex tasks that must be addressed to solve such problems on mobile devices can be transferred to the cloud environment when appropriate conditions are met. The decision to offload to the cloud environment at this stage is very important. In this thesis, a context-aware decision-making system has been developed for offloading to cloud environments. Unlike similar tasks, the processes determined for transfer to the cloud are not run randomly, but rather according to the mobile user's application usage habits. The developed system was implemented in a real environment for one month. According to the results, it was determined that processes transferred to the cloud were completed in less time and consumed less energy.
Keywords
Mobile Cloud Offloading, Mobile Cloud Computing, Context-Aware System, Forecasting, Dynamic Estimation, Energy-Efficiency.
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