MECCA: mobile, efficient cloud computing workload adoption framework using scheduler customization and workload migration decisions

Authors:
Dharmesh Kakadia;Prasad Saripalli;Vasudeva Varma
Affiliations:
International Institute of Information Technology, Hyderabad, Hyderabad, India;IBM Cloud Center of Excellence, Hyderabad, India;International Institute of Information Technology, Hyderabad, Hyderabad, India
Venue:
Proceedings of the first international workshop on Mobile cloud computing & networking
Year:
2013

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Abstract

The availability of increasingly richer applications is providing surprisingly wide range of functionalities and new use cases on mobile devices. Even tough mobile devices are becoming increasingly more powerful, the resource utilization of richer application can overwhelm resources on these devices. At the same time, ubiquitous connectivity of mobile devices also opens up the possibility of leveraging cloud resources. Seamless and flexible path to mobile cloud computing requires recognizing opportunities where the application execution on cloud instead of mobile device. In this paper we propose a cloud aware scheduler for application offloading from mobile devices to clouds. We used learning based algorithm for predicting the gain attainable using performance monitoring and high level features. We evaluated prototype of our system on various workloads and under various conditions.