In spite of the dramatic growth in the number of Smartphone in recent years, the challenge of limited energy capacity of these devices has not been solved satisfactorily. However, in the era of cloud computing, the limitation on energy capacity can be eased off in an efficient way by offloading heavy tasks to the cloud. Cloud computation offloading is a promising method that sending heavy computation to resourceful servers on cloud and then receiving the results from them. To maximize efficiency, systems must determine the functionality to offload at runtime, which will require innovation in both automated program transformation and systematic runtime adaptation. We studied the offloading techniques and explored the trade-off between shortening execution time and extending battery life of mobile devices. The comparison will be performed by using HTTP and FTP Internet protocols with 3G and Wi-Fi network interfaces. All the experiments will be conducted on an Android based Smartphone. We are expecting a result which will show that MCC provides the Smartphone with much multimedia functionality and saves Smartphone energy from 30% to 70%.
Onkar Pasfule : Computer Engineering Department, Savitribai Phule Pune University,
Pune, Maharashtra, India
Pravin Rathod : Computer Engineering Department, Savitribai Phule Pune University,
Pune, Maharashtra, India
Harshal Shinde : Computer Engineering Department, Savitribai Phule Pune University,
Pune, Maharashtra, India
Harmeet Khanuja : Computer Engineering Department, Savitribai Phule Pune University,
Pune, Maharashtra, India
Offloading, Energy, Cloud computing
In this paper we are representing a generic mobile cloud system and investing a trade-off between remote and local processing from the view point of energy use, taking into account into energy used for transferring the task from the local system to a remote service. We are aiming to minimize the energy consumption of trans-coding on mobile device and service engine in cloud while achieving low delay.
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