Abstract
In this paper, we are investigating the power consumption of mobile device while performing offloading system. The offloading system is way in which mobile application can be divided into local and remote execution in order to alleviate the CPU energy consumption. However, existing offloading systems do not consider data transfer communication energy while performing mobile offloading system. They have just focused on mobile CPU energy consumption. In this paper, we are investigating the energy consumption mobile CPU and communication energy collaboratively while performing mobile offloading for complex application. To cope up with the above problem, we have proposed Energy Efficient Task Scheduler (EETS) algorithm, whose aim is to determine optimal tasks execution in offloading system in order to minimize mobile CPU and communication energy. Simulation results show that EETS outperforms as compared to baseline approaches.
Highlights
It can be anticipated that more and more applications are to be converted into mobile cloud computing (MCC) [1]
To cope up with the above problem, we have proposed Energy Efficient Task Scheduler (EETS) algorithm, whose aim is to determine optimal tasks execution in offloading system in order to minimize mobile CPU and communication energy
Energy Efficient Task Assignment has three techniques for the application execution in a mobile device; for example full offloading where energy hungry tasks computationally offloaded to the surrogate server it could be local or remote cloud
Summary
It can be anticipated that more and more applications are to be converted into mobile cloud computing (MCC) [1]. We are studying the application partitioning and energy efficient task scheduler in mobile cloud environment. Energy Efficient Task Assignment has three techniques for the application execution in a mobile device; for example full offloading where energy hungry tasks computationally offloaded to the surrogate server it could be local or remote cloud. We have proposed EETA (energy efficient task assignment) algorithm and that is a partial offloading technique so that it minimizes and prolongs the device energy as well as communication energy. Energy efficient application partitioning and task assignment play an important role in performance Proposed scheme such as static analysis could not guarantee the optimal and energy efficient task assignment due to adaptively change in mobile device status and workload.
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