TASK OFFLOADING FRAMEWORK TO ENHANCE ENERGY EFFICIENCY OF SMARTPHONES

Ajay Bhosale, Shafi Pathan

Abstract


Although the evolution and enhancements that mobile devices have experienced, they are still considered as limited computing devices Cloud is a promising strategy to enhance the computing capability of today’s smartphones and to increase the battery life. Communication cost of task offloading of mobile devices is much more expensive than the one that is used in desktop devices. Challenges in consumption of the communication activity can be reduced by making an exact decision while performing the activity of task offloading. 3G and 4G devices are taking into consideration to develop an energy efficient model for task offloading. Task offloading has a great advantage over traditional endoscopy because it is possible and easy to use. We use five smartphones to conduct the experiment. The experimental results show that our estimation models precisely estimate the energy essential to offload tasks.

Keywords


Mobile Computing, Cloud Computing, Smartphones, Offloading Decision, Energy Saving, WLAN Energy, 3G Energy, 4G Energy, Energy Estimation.

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References


X. Ma, Y. Zhao, L. Zhang, H. Wang, and L. Peng, “When Mobile Terminals Meet the Cloud: Computation Offloading as the Bridge,” Network, IEEE, vol. 27, no. 5, pp. 28–33, 2013.

A. Abogharaf and K. Naik, “Client-Centric Data Streaming on Smartphones: An Energy Perspective,” in International Conference on Selected Topics in Mobile and Wireless Networking (MoWNeT), 2013, pp. 36–41.

Albasir, K. Naik, and T. Abdunabi, “Smart Mobile Web Browsing,” in The 6th IEEE International Conference on Ubi-Media Computing, Aizu-Wakamatsu, Japan, Nov. 2-4 2013.

K. Ullah and J. Nurminen, “Applicability of Different Models of Burstiness to Energy Consumption Estimation,” in 8th International Symposium on Communication Systems, Networks Digital Signal Processing (CSNDSP), Jul. 2012, pp. 1–6.

Models of Burstiness to Energy Consumption Estimation,” in 8th International Symposium on Communication Systems, Networks Digital Signal Processing (CSNDSP), Jul. 2012, pp. 1–6.

W. Zhang, Y. Wen, J. Wu, and H. Li, “Toward a Unified Elastic Computing Platform for Smartphones with Cloud Support,” Network, IEEE, vol. 27, no. 5, pp. 34–40, 2013.

L. Sarga, “Cloud Computing: An Overview,” Journal of Systems Integration, vol. 3, no. 4, pp. 3–14, 2012.

I Grigorik, High-Performance Browser Networking: What Every Web Developer Should Know about Networking and Web Performance. ” O’Reilly Media, Inc.”, 2013.

K. Ullah and J. Nurminen, “Applicability of Different Models of Burstiness to Energy Consumption Estimation,” in 8th International Symposium on Communication Systems, Networks Digital Signal Processing (CSNDSP), Jul. 2012, pp. 1–6.

H. Chen, F. Zhang, C. Chen, Z. Yang, R. Chen, B. Zang, W. Mao, H. Chen, F. Zhang, C. Chen, et al., Tamperresistant execution in an untrusted operating system using a virtual machine monitor, Technical Report, Parallel Processing Institute, Fudan University, FDUPPITR-2007-0801, 2007.

Gong, J. Liu, Q. Zhang, H. Chen, and Z. Gong, “The Characteristics of Cloud Computing,” in Proc. 39th Int Parallel Processing Workshops (ICPPW) Conf, 2010, pp. 275–279.

K. Kumar, J. Liu, Y.-H. Lu, and B. Bhargava, “A Survey of Computation Offloading for Mobile Systems,” Mobile Networks and Applications, pp. 1–12, 2012.

J. Baliga, R. W. A. Ayre, K. Hinton, and R. S. Tucker, “Green Cloud Computing: Balancing Energy in Processing, Storage, and Transport,” Proceedings of the IEEE, vol. 99, no. 1, pp. 149–167, Jan. 2011.

S. Hao, D. Li, W. Halford, and R. Govindan, “Estimating Android Applications’ CPU Energy Usage via Bytecode Profiling,” in First International Workshop on Green and Sustainable Software (GREENS), 2012, pp. 1–7.

A. Manjunatha, A. Ranabahu, A. Sheth, and K. Thirunarayan, “Power of Clouds in Your Pocket: An Efficient Approach for Cloud Mobile Hybrid Application Development,” in Proc.IEEESecond Int Cloud Computing Technology and Science (CloudCom) Conf, 2010, pp. 496–503.

M. Lauridsen, P. Mogensen, and L. Noel, “Empirical LTE Smartphone Power Model with DRX Operation for System Level Simulations,” in IEEE 78th Vehicular Technology Conference, Sep. 2013, pp. 1–6.

F. Qian, Z. Wang, A. Gerber, Z. Mao, S. Sen, and O. Spatscheck, “Profiling Resource Usage for Mobile Applications: A Cross-layer Approach,” in Proceedings of the 9th International Conference on Mobile Systems, Applications, and Services, ser. MobiSys ’11. ACM, 2011, pp. 321–334.


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