Abstract
Nowadays, mobile devices are very popular and accessible. Therefore users prefer to substitute mobile devices for stationary computers to run their applications. On the other hand, mobile devices are always resource-poor in contrast with stationary computers and portability and limitation on their weight and size restrict mobile devises’ processor speed, memory size and battery lifetime. One of the most common solutions, in pervasive computing environments, to resolve the challenges of computing on resource constrained mobile devices is cyber foraging, wherein nearby and more powerful stationary computers called surrogates are exploited to run the whole or parts of applications. However, cyber foraging is not beneficial for all circumstances. So, there should be a solver unit to choose the best location either the mobile device or a surrogate to run a task. In this paper, we propose a mechanism to select the best method between local execution on the mobile device and remote execution on nearby surrogates to run an application by calculating the execution cost according to the context’s metrics such as mobile device, surrogates, network, and application specifications. Experimental results show the superiority of our proposed mechanism compared to local execution of the application on the mobile device and blind task offloading with respect to latency.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
The Global Partnership for Development at a Critical Juncture. United Nations, New York, MDG GAP Task Force Report (2010)
Satyanarayanan, M., Bahl, P., Cáceres, R., Davies, N.: The Case for VM-Based Cloudlets in Mobile Computing. IEEE Pervasive Computing 8, 14–23 (2009)
Oh, J., Lee, S., Lee, E.-s.: An Adaptive Mobile System Using Mobile Grid Computing in Wireless Network. In: Gavrilova, M.L., Gervasi, O., Kumar, V., Tan, C.J.K., Taniar, D., Laganá, A., Mun, Y., Choo, H. (eds.) ICCSA 2006. LNCS, vol. 3984, pp. 49–57. Springer, Heidelberg (2006)
Ou, S., Yang, K., Zhang, Q.: An Efficient Runtime Offloading Approach for Pervasive Services. In: IEEE Wireless Communications & Networking Conference (WCNC 2006), Las Vegas, pp. 2229–2234 (2006)
Balan, R.K., Gergle, D., Satyanarayanan, M., Herbsleb, J.: Simplifying Cyber Foraging for Mobile Devices. In: 5th USENIX International Conference on Mobile Systems, Applications and Services (MobiSys), San Juan, Puerto Rico, pp. 272–285 (2007)
Flinn, J., Park, S., Satyanarayanan, M.: Balancing Performance, Energy, and Quality in Pervasive Computing. In: 22nd International Conference on Distributed Computing Systems (ICDCS 2002), Austria, pp. 217–226 (2002)
Chen, G., Kang, B.T., Kandemir, M., Vijaykrishnan, N., Irwin, M.J., Chandramouli, R.: Studying Energy Trade Offs in Offloading Computation/Compilation in Java-Enabled Mobile Devices. IEEE Transactions on Parallel and Distributed Systems 15, 795–809 (2004)
Satyanarayanan, M.: Pervasive Computing: Vision and Challenges. IEEE Personal Communication 8, 10–17 (2001)
Balan, R.K., Satyanarayanan, M., Park, S., Okoshi, T.: Tactics-Based Remote Execution for Mobile Computing. In: 1st International Conference on Mobile Systems, Applications and Services, San Francisco, pp. 273–286 (2003)
Gu, X., Messer, A., Greenbergx, I., Milojicic, D., Nahrstedt, K.: Adaptive Offloading for Pervasive Computing. IEEE Pervasive Computing Magazine 3, 66–73 (2004)
Ou, S., Yang, K., Liotta, A.: An Adaptive Multi-Constraint Partitioning Algorithm for Offloading in Pervasive Systems. In: 4th Annual IEEE International Conference on Pervasive Computing and Communications (PERCOM 2006), Pisa, Italy, pp. 116–125 (2006)
Song, X.: Seamless Mobility in Ubiquitous Computing Environments. PhD Thesis, Georgia Institute of Technology (2008)
Song, X., Ramachandran, U.: MobiGo: A Middleware for Seamless Mobility. In: 13th IEEE International Conference on Embedded and Real-Time Computing Systems and Applications (RTCSA 2007), Daegu, pp. 249–256 (2007)
Kristensen, M.D.: Empowering Mobile Devices through Cyber Foraging:The Development of Scavenger, an Open Mobile Cyber Foraging System. PhD Thesis, Department of Computer Science, Aarhus University, Denmark (2010)
Satyanarayanan, M.: Avoiding Dead Batteries. IEEE Pervasive Computing 4, 2–3 (2005)
Othrnan, M., Hailes, S.: Power Conservation Strategy for Mobile Computers Using Load Sharing. Mobile Computing and Communications Review 2, 19–26 (1998)
Cuervo, E., Balasubramanian, A., Cho, D.K., Wolman, A., Saroiu, S., Chandra, R., Bahl, P.: MAUI: Making Smartphones Last Longer with Code Offload. In: ACM MobiSys, San Francisco, USA, pp. 49–62 (2010)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2011 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Kafaie, S., Kashefi, O., Sharifi, M. (2011). Context-Aware Task Scheduling for Resource Constrained Mobile Devices. In: Snasel, V., Platos, J., El-Qawasmeh, E. (eds) Digital Information Processing and Communications. ICDIPC 2011. Communications in Computer and Information Science, vol 188. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-22389-1_23
Download citation
DOI: https://doi.org/10.1007/978-3-642-22389-1_23
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-22388-4
Online ISBN: 978-3-642-22389-1
eBook Packages: Computer ScienceComputer Science (R0)