Call for Paper - February 2021 Edition
IJCA solicits original research papers for the February 2021 Edition. Last date of manuscript submission is January 20, 2021. Read More

Application Method-based Efficient Offloading Scheme in Mobile Cloud Computing

International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Year of Publication: 2015
Ahmed A.A. Gad-ElRab, T.A.A. Alzohairy, Farouk A. Emara

Ahmed A A Gad-ElRab, T A A Alzohairy and Farouk A Emara. Article: Application Method-based Efficient Offloading Scheme in Mobile Cloud Computing. International Journal of Computer Applications 132(3):1-8, December 2015. Published by Foundation of Computer Science (FCS), NY, USA. BibTeX

	author = {Ahmed A.A. Gad-ElRab and T.A.A. Alzohairy and Farouk A. Emara},
	title = {Article: Application Method-based Efficient Offloading Scheme in Mobile Cloud Computing},
	journal = {International Journal of Computer Applications},
	year = {2015},
	volume = {132},
	number = {3},
	pages = {1-8},
	month = {December},
	note = {Published by Foundation of Computer Science (FCS), NY, USA}


Mobile Cloud Computing is a new paradigm that transfers the data storage and the data processing from a mobile device to a power full cloud server which has a big storage. Mobile cloud applications use offloading schemes to move the computing power and data storage away from mobile phones into this cloud server. However, for a code compilation, offloading might consume more energy than the local processing of data when the size of code is small. So, a new offloading schemes are needed to be adaptive with the code size of an application or a service. This paper introduces a new method-based offloading scheme for mobile application. The proposed scheme divides each mobile application into presentation layer, logical layer and data access layer. Also, it considers each service or process in each layer as a set of methods. The methods of presentation layer resides on the mobile device, the methods of data layer is fully deployed on the cloud to minimize the data access, and the methods of logic layer is distributed between the cloud and mobile device by using formulated cost model which takes into account energy, memory, time, and data transfer delay costs. The conducted simulation results show that the offloading performance of the proposed scheme is much better than local processing scheme.


  1. Hoang T Dinh, Chonho Lee, Dusit Niyato, and Ping Wang. A survey of mobile cloud computing: architecture, applications, and approaches. Wireless communications and mobile computing, 13(18):1587–1611, 2013.
  2. Muhammad Shiraz, Abdullah Gani, Rashid Hafeez Khokhar, and Rajkumar Buyya. A review on distributed application processing frameworks in smart mobile devices for mobile cloud computing. Communications Surveys & Tutorials, IEEE, 15(3):1294–1313, 2013.
  3. A Khan, Mazliza Othman, S Madani, and S Khan. A survey of mobile cloud computing application models. 2013.
  4. Byung-Gon Chun, Sunghwan Ihm, Petros Maniatis, Mayur Naik, and Ashwin Patti. Clonecloud: elastic execution between mobile device and cloud. In Proceedings of the sixth conference on Computer systems, pages 301–314. ACM, 2011.
  5. Eduardo Cuervo, Aruna Balasubramanian, Dae-ki Cho, Alec Wolman, Stefan Saroiu, Ranveer Chandra, and Paramvir Bahl. Maui: making smartphones last longer with code offload. In Proceedings of the 8th international conference on Mobile systems, applications, and services, pages 49–62. ACM, 2010.
  6. Ioana Giurgiu, Oriana Riva, Dejan Juric, Ivan Krivulev, and Gustavo Alonso. Calling the cloud: enabling mobile phones as interfaces to cloud applications. In Middleware 2009, pages 83–102. Springer, 2009.
  7. Dejan Kovachev, Tian Yu, and Ralf Klamma. Adaptive computation offloading from mobile devices into the cloud. In Parallel and Distributed Processing with Applications (ISPA), 2012 IEEE 10th International Symposium on, pages 784–791. IEEE, 2012.
  8. Jan S Rellermeyer, Gustavo Alonso, and Timothy Roscoe. Rosgi: distributed applications through software modularization. In Proceedings of the ACM/IFIP/USENIX 2007 International Conference on Middleware, pages 1–20. Springer- Verlag New York, Inc., 2007.
  9. Jan S Rellermeyer, Oriana Riva, and Gustavo Alonso. Alfredo: an architecture for flexible interaction with electronic devices. In Proceedings of the 9th ACM/IFIP/USENIX International Conference on Middleware, pages 22–41. Springer- Verlag New York, Inc., 2008.
  10. Glenn E Krasner, Stephen T Pope, et al. A description of the model-view-controller user interface paradigm in the smalltalk-80 system. Journal of object oriented programming, 1(3):26–49, 1988.
  11. Lide Zhang, Birjodh Tiwana, Zhiyun Qian, ZhaoguangWang, Robert P Dick, Zhuoqing Morley Mao, and Lei Yang. Accurate online power estimation and automatic battery behavior based power model generation for smartphones. In Proceedings of the eighth IEEE/ACM/IFIP international conference on Hardware/software codesign and system synthesis, pages 105–114. ACM, 2010.
  14. OSGi Alliance. Osgitm service platform, core specification, release 4, version 4.1, 2007.
  16. Karthik Kumar and Yung-Hsiang Lu. Cloud computing for mobile users: Can offloading computation save energy? Computer, 43(4):51–56, 2010.
  17. Mohsen Sharifi, Somayeh Kafaie, and Omid Kashefi. A survey and taxonomy of cyber foraging of mobile devices. Communications Surveys & Tutorials, IEEE, 14(4):1232–1243, 2012.
  18. Muhammad Shiraz, Md Whaiduzzaman, and Abdullah Gani. A study on anatomy of smartphone. Computer Communication & Collaboration, 1:24–31, 2013.
  19. Xinwen Zhang, Sangoh Jeong, Anugeetha Kunjithapatham, and Simon Gibbs. Towards an elastic application model for augmenting computing capabilities of mobile platforms. In Mobile wireless middleware, operating systems, and applications, pages 161–174. Springer, 2010.


Application partitioning, Battery Consumption, Mobile cloud computing, Offloading