An Investigation of Different Computing Sources for Mobile Application Outsourcing on the Road
Mobile applications are growing fast due to pervasive usage of mobile devices. With inherently limited on-device resources, plenty of research has been conducted on job partitioning/outsourcing strategies to execute mobile computing tasks on external sources, such as public clouds or nearby computers. However, little is known about the performance difference to mobile users on these external computing sources.
In this paper, considering the user’s response time and the battery power consumption on mobile devices, we first show that outsourcing mobile applications to public clouds may not outperform outsourcing to nearby residential computers, particularly for delay sensitive applications. To facilitate efficient mobile outsourcing to residential computers, we propose to build a framework RoseMic (ROad-SidE-MobIle- Computing). In RoseMic, a resource overlay network is built with users’ idle residential (home) computers. To encourage the sharing of idle residential computers, RoseMic also includes a credit based incentive mechanism that can be enforced automatically without users’ interferences in order to defeat collusion attacks. To demonstrate the performance of RoseMic, we run several real-world applications. The results show that RoseMic outperforms Amazon EC2 by 3 times and 4 times on average in terms of response time and the battery power consumption, respectively.
KeywordsMobile Device Mobile User Mobile Application Node Failure Public Cloud
Unable to display preview. Download preview PDF.
- 1.Boinc, http://boinc.berkeley.edu/
- 2.Cross Correlation, http://en.wikipedia.org/wiki/Cross-correlation
- 3.Google Geolocation Service, http://code.google.com/p/gears/wiki/GeolocationAPI
- 4.International Data Corporation : Press Release (January 28, and February 4, 2010), http://www.idc.com/
- 6.Seti Home, http://setiathome.berkeley.edu/
- 7.Balan, R., Flinn, J., Satyanarayanan, M., Sinnamohideen, S., Yang, H.-I.: The case of cyber foraging. In: Proceedings of the 10th ACM SIGOPS European Workshop, Saint-Emilion, France (July 2002)Google Scholar
- 8.Balan, R.K., Gergle, D., Satyanarayanan, M., Herbsleb, J.: Simplifying cyber foraging for mobile devices. In: Proceedings of the 5th International Conference on Mobile Systems, Applications, and Services (MobiSys), San Juan, Puerto Rico (June 2007)Google Scholar
- 9.Chun, B.G., Maniatis, P.: Augmented smartphone applications through clone cloud execution. In: Proceedings of the 12th Workshop on Hot Topics in Operating Systems (HotOS), Monte Veritá, Switzerland (May 2009)Google Scholar
- 10.Chun, B.G., Maniatis, P.: Dynamically partitioning applications between weak devices and clouds. In: Proceedings of ACM Workshop on Mobile Cloud Computing & Services (MCS), San Francisco, CA, USA (June 2010)Google Scholar
- 11.Cuervo, E., Balasubramanian, A., Cho, D.K., Wolman, A., Saroiu, S., Chandra, R., Bahl, P.: Maui: Making smartphones last longer with code offload. In: Proceedings of the 8th International Conference on Mobile Systems, Applications, and Services (MobiSys), San Francisco, CA, USA (June 2010)Google Scholar
- 12.Flinn, J., Narayanan, D., Satyanarayanan, M.: Self-tuned re-mote execution for pervasive computing. In: Proceedings of the 8th Workshop on Hot Topics in Operating Systems (HotOS), Schloss Elmau, Germany (May 2001)Google Scholar
- 13.Jain, J.R., Jain, A.K.: Displacement measurement and its application in interframe image coding. IEEE Transactions on Communications 29 (December 1981)Google Scholar
- 14.Ott, J., Kutscher, D.: Drive-thru internet: Ieee 802.11b for “automobile” users. In: Proceedings of IEEE InfoCom, Hong Kong (March 2004)Google Scholar
- 15.Rudenko, A., Reiher, P., Popek, G.J., Kuenning, G.H.: Saving portable computer battery power through remote process execution. In: Proceedings of Mobile Computing and Communication Review, MC2R (1998)Google Scholar
- 16.Satyanarayanan, M., Bahl, P., Caceres, R., Davies, N.: The case for vm-based cloudlets in mobile computing. IEEE Pervasive Computing 8(4) (October 2009)Google Scholar
- 17.Nahrstedt, K., Gu, X., Messer, A., Greenberg, I., Milojicic, D.: Adaptive offloading inference for delivering applications in pervasive computing environments. In: Proceedings of IEEE International Conference on Pervasive Computing and Communications (PerCom), Dallas-Fort Worth, Texas (March 2003)Google Scholar