An efficient game theoretic based computation offloading framework for network optimisation in mobile cloud IoT systems

Mobile cloud computing (MCC) is visualised as an encouraging approach to increase the computational capabilities of mobile devices. With the advancement of internet of things (IoT) technologies and mobile cloud, a new concept is developed called as mobile cloud IoT (MCIoT) which is the convergence of IoT and mobile cloud. In this paper, we propose a nested game theoretic technique for computation offloading algorithms. Firstly we introduce a game theoretic approach for network selection based on strategic and repeated game theory. Then, for determining the portion of application to be offloaded we use bargaining game theory based on Rubinstein-Stahl's model. Then the selection of the best cloud is analysed using auction game theory and trading market theory. Numerical results show that the proposed scheme can achieve effective computation offloading mechanism under MCIoT systems.

[1]  Sungwook Kim,et al.  Nested game-based computation offloading scheme for Mobile Cloud IoT systems , 2015, EURASIP Journal on Wireless Communications and Networking.

[2]  Mihaela van der Schaar,et al.  Bargaining Strategies for Networked Multimedia Resource Management , 2007, IEEE Transactions on Signal Processing.

[3]  Bharat K. Bhargava,et al.  A Survey of Computation Offloading for Mobile Systems , 2012, Mobile Networks and Applications.

[4]  Gabriel-Miro Muntean,et al.  Game Theory-Based Network Selection: Solutions and Challenges , 2012, IEEE Communications Surveys & Tutorials.

[5]  Tao Li,et al.  A Framework for Partitioning and Execution of Data Stream Applications in Mobile Cloud Computing , 2012, 2012 IEEE Fifth International Conference on Cloud Computing.

[6]  Stephen S. Yau,et al.  Intelligent Planning for Developing Mobile IoT Applications Using Cloud Systems , 2014, 2014 IEEE International Conference on Mobile Services.

[7]  Athanasios V. Vasilakos,et al.  MuSIC: Mobility-Aware Optimal Service Allocation in Mobile Cloud Computing , 2013, 2013 IEEE Sixth International Conference on Cloud Computing.

[8]  Angelo Sifaleras,et al.  Convergence of Internet of things and mobile cloud computing , 2014 .

[9]  Haiyun Luo,et al.  Energy-optimal mobile application execution: Taming resource-poor mobile devices with cloud clones , 2012, 2012 Proceedings IEEE INFOCOM.

[10]  Sabuj Chowdhury,et al.  A Novel Mechanism on Network Selection for Fourth Generation Communication Networks , 2014 .

[11]  Miao Pan,et al.  Bargaining based pairwise cooperative spectrum sensing for Cognitive Radio networks , 2008, MILCOM 2008 - 2008 IEEE Military Communications Conference.

[12]  Sirin Tekinay,et al.  A survey of game-theoretic approaches in wireless sensor networks , 2008, Comput. Networks.

[13]  Vincenzo Grassi,et al.  A game-theoretic approach to computation offloading in mobile cloud computing , 2015, Mathematical Programming.

[14]  Moo Wan Kim,et al.  Adaptive QoS Mechanism for Wireless Mobile Network , 2010, J. Comput. Sci. Eng..

[15]  Massoud Pedram,et al.  A Nested Two Stage Game-Based Optimization Framework in Mobile Cloud Computing System , 2013, 2013 IEEE Seventh International Symposium on Service-Oriented System Engineering.

[16]  Dongman Lee,et al.  A virtual cloud computing provider for mobile devices , 2010, MCS '10.

[17]  K. J. Ray Liu,et al.  Game theory for cognitive radio networks: An overview , 2010, Comput. Networks.

[18]  Allen B. MacKenzie,et al.  Using game theory to analyze wireless ad hoc networks , 2005, IEEE Communications Surveys & Tutorials.

[19]  Theodore S. Rappaport,et al.  Wireless communications - principles and practice , 1996 .

[20]  Hongtu Zhao,et al.  Study on negotiation strategy , 2002 .

[21]  Ariel Rubinstein,et al.  A Course in Game Theory , 1995 .

[22]  Zhu Han,et al.  Cooperative Game Theory for Distributed Spectrum Sharing , 2007, 2007 IEEE International Conference on Communications.

[23]  Athanasios V. Vasilakos,et al.  Mobile Cloud Computing: A Survey, State of Art and Future Directions , 2013, Mobile Networks and Applications.

[24]  Dhananjay Singh,et al.  A survey of Internet-of-Things: Future vision, architecture, challenges and services , 2014, 2014 IEEE World Forum on Internet of Things (WF-IoT).

[25]  Azer Bestavros,et al.  Colocation Games and Their Application to Distributed Resource Management , 2009, HotCloud.

[26]  Antonio Pescapè,et al.  On the Integration of Cloud Computing and Internet of Things , 2014, 2014 International Conference on Future Internet of Things and Cloud.

[27]  Sokol Kosta,et al.  To offload or not to offload? The bandwidth and energy costs of mobile cloud computing , 2013, 2013 Proceedings IEEE INFOCOM.

[28]  Ragib Hasan,et al.  Aura: An IoT Based Cloud Infrastructure for Localized Mobile Computation Outsourcing , 2015, 2015 3rd IEEE International Conference on Mobile Cloud Computing, Services, and Engineering.

[29]  Xu Chen,et al.  Decentralized Computation Offloading Game for Mobile Cloud Computing , 2014, IEEE Transactions on Parallel and Distributed Systems.

[30]  Sergio Barbarossa,et al.  Joint allocation of computation and communication resources in multiuser mobile cloud computing , 2013, 2013 IEEE 14th Workshop on Signal Processing Advances in Wireless Communications (SPAWC).

[31]  Naixue Xiong,et al.  A game-theoretic method of fair resource allocation for cloud computing services , 2010, The Journal of Supercomputing.

[32]  Martin J. Osborne,et al.  An Introduction to Game Theory , 2003 .