Energy-aware offloading in mobile cloud systems with delay considerations

In Mobile Cloud Computing where computing power and data storage are moving away from mobile devices to remote computing resources, traffic computational offloading has been proposed as a key enabling technology to provide improved computational performance and maximize the battery lifetime of end devices. However, traffic offloading can only be adopted, if strict latency constraints imposed by the mobile cloud services are satisfied. To achieve this, significant amounts of computational and network resources need to be allocated, leading to increased operational and capital expenditures for the physical infrastructure providers. To address this issue, a multi-objective service provisioning scheme is proposed that tries to optimize the performance of both the network and computation infrastructure and the battery lifetime of the mobile devices under worst case delay conditions using network calculus theory.

[1]  Yonggang Wen,et al.  Energy-efficient scheduling policy for collaborative execution in mobile cloud computing , 2013, 2013 Proceedings IEEE INFOCOM.

[2]  Reza Nejabati,et al.  Virtualization of heterogeneous wireless-optical network and IT infrastructures in support of cloud and mobile cloud services , 2013, IEEE Communications Magazine.

[3]  Rajkumar Buyya,et al.  Heterogeneity in Mobile Cloud Computing: Taxonomy and Open Challenges , 2014, IEEE Communications Surveys & Tutorials.

[4]  Bo Li,et al.  eTime: Energy-efficient transmission between cloud and mobile devices , 2013, 2013 Proceedings IEEE INFOCOM.

[5]  Chonho Lee,et al.  A survey of mobile cloud computing: architecture, applications, and approaches , 2013, Wirel. Commun. Mob. Comput..

[6]  Dimitra Simeonidou,et al.  A converged network architecture for energy efficient mobile cloud computing , 2014, 2014 International Conference on Optical Network Design and Modeling.

[7]  Sergio Barbarossa,et al.  Computation offloading for mobile cloud computing based on wide cross-layer optimization , 2013, 2013 Future Network & Mobile Summit.

[8]  Markus Fidler,et al.  Survey of deterministic and stochastic service curve models in the network calculus , 2009, IEEE Communications Surveys & Tutorials.

[9]  Dusit Niyato,et al.  A Framework for Cooperative Resource Management in Mobile Cloud Computing , 2013, IEEE Journal on Selected Areas in Communications.

[10]  Chen-Khong Tham,et al.  Dynamic offloading algorithm in intermittently connected mobile cloudlet systems , 2014, 2014 IEEE International Conference on Communications (ICC).

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

[12]  John Byrne,et al.  Workload diversity and dynamics in big data analytics: implications to system designers , 2012, ASBD '12.

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

[14]  Markus Fidler.  Providing internet quality of service based on differentiated services traffic engineering , 2003 .

[15]  Jörg Ott,et al.  Optimizing Offloading Strategies in Mobile Cloud Computing , 2013 .

[16]  Jean-Yves Le Boudec,et al.  Network Calculus: A Theory of Deterministic Queuing Systems for the Internet , 2001 .

[17]  Jia Liu,et al.  Quality of Service Modelling of Virtualized Wireless Networks: A Network Calculus Approach , 2014, Mob. Networks Appl..

[18]  Muhammad Ali Imran,et al.  Cellular Energy Efficiency Evaluation Framework , 2011, 2011 IEEE 73rd Vehicular Technology Conference (VTC Spring).

[19]  N. Amaya,et al.  Time shared optical network (TSON): A novel metro architecture for flexible multi-granular services , 2011, 2011 37th European Conference and Exhibition on Optical Communication.

[20]  Wei-Tek Tsai,et al.  Energy Saving in Mobile Cloud Computing* , 2013, 2013 IEEE International Conference on Cloud Engineering (IC2E).

[21]  Paramvir Bahl,et al.  The Case for VM-Based Cloudlets in Mobile Computing , 2009, IEEE Pervasive Computing.

[22]  Yung-Hsiang Lu,et al.  Cloud Computing for Mobile Users: Can Offloading Computation Save Energy? , 2010, Computer.

[23]  Volker Sander,et al.  A parameter based admission control for differentiated services networks , 2004, Comput. Networks.

[24]  Rajkumar Buyya,et al.  Energy-aware resource allocation heuristics for efficient management of data centers for Cloud computing , 2012, Future Gener. Comput. Syst..

[25]  R. Nejabati,et al.  Performance analysis of hybrid network for cloud datacenter , 2012, 2012 4th Computer Science and Electronic Engineering Conference (CEEC).

[26]  Qiang Duan,et al.  Modeling and delay analysis for converged network-cloud service provisioning systems , 2013, 2013 International Conference on Computing, Networking and Communications (ICNC).