Simplifying cyber foraging for mobile devices
Proceedings of the 5th international conference on Mobile systems, applications and services
Practical power modeling of data transmission over 802.11g for wireless applications
Proceedings of the 1st International Conference on Energy-Efficient Computing and Networking
MAUI: making smartphones last longer with code offload
Proceedings of the 8th international conference on Mobile systems, applications, and services
CODES/ISSS '10 Proceedings of the eighth IEEE/ACM/IFIP international conference on Hardware/software codesign and system synthesis
TaintDroid: an information-flow tracking system for realtime privacy monitoring on smartphones
OSDI'10 Proceedings of the 9th USENIX conference on Operating systems design and implementation
CloneCloud: elastic execution between mobile device and cloud
Proceedings of the sixth conference on Computer systems
Where is the energy spent inside my app?: fine grained energy accounting on smartphones with Eprof
Proceedings of the 7th ACM european conference on Computer Systems
Spaceify: a client-edge-server ecosystem for mobile computing in smart spaces
Proceedings of the 19th annual international conference on Mobile computing & networking
Cloud is not a silver bullet: a case study of cloud-based mobile browsing
Proceedings of the 15th Workshop on Mobile Computing Systems and Applications
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Offloading tasks to cloud is one of the proposed solutions for extending battery life of mobile devices. Most prior research focuses on offloading computation, leaving communication-related tasks out of scope. However, most popular applications today involve intensive communication that consumes a significant part of the overall energy. Hence, we currently do not know how feasible it is to use offloading for saving energy in such apps. In this paper, we first show that it is possible to save energy by offloading communication-related tasks of the app to the cloud. We use an open source Twitter client, AndTweet, as a case study. However, using a set of popular open source applications, we also show that existing apps contain constraints that have to be released with code modifications before offloading can be profitable, and that the potential energy savings depend on many communication parameters. We therefore develop two tools: the first to identify the constraints and the other for fine-grained communication energy estimation. We exemplify the tools and explain how they could be used to help offloading parts of popular apps successfully.