Data offloading and task allocation for cloudlet-assisted ad hoc mobile clouds
Guo, X., Liu, L., Chang, Z., & Ristaniemi, T. (2018). Data offloading and task allocation for cloudlet-assisted ad hoc mobile clouds. Wireless Networks, 24(1), 79-88. https://doi.org/10.1007/s11276-016-1322-z
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Wireless NetworksDate
2018Copyright
© Springer Science+Business Media New York 2016. This is a final draft version of an article whose final and definitive form has been published by Springer Science+Business Media New York. Published in this repository with the kind permission of the publisher.
Nowadays, although the data processing capabilities of the modern mobile devices are developed in a fast speed, the resources are still limited in terms of processing capacity and battery lifetime. Some applications, in particular the computationally intensive ones, such as multimedia and gaming, often require more computational resources than a mobile device can afford. One way to address such a problem is that the mobile device can offload those tasks to the centralized cloud with data centers, the nearby cloudlet or ad hoc mobile cloud. In this paper, we propose a data offloading and task allocation scheme for a cloudlet-assisted ad hoc mobile cloud in which the master device (MD) who has computational tasks can access resources from nearby slave devices (SDs) or the cloudlet, instead of the centralized cloud, to share the workload, in order to reduce the energy consumption and computational cost. A two-stage Stackelberg game is then formulated where the SDs determine the amount of data execution units that they are willing to provide, while the MD who has the data and tasks to offload sets the price strategies for different SDs accordingly. By using the backward induction method, the Stackelberg equilibrium is derived. Extensive simulations are conducted to demonstrate the effectiveness of the proposed scheme.
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Springer New York LLC; Association for Computing Machinery, Inc.ISSN Search the Publication Forum
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