Performance evaluation of dynamic cloud resource migration based on temporal and capacity-aware policy for efficient resource sharing

This paper elaborates on practical considerations, such as location and capacity issues to offload resources, by adopting a rack based approach for the implementation. The proposed cooperative migration of resources enables efficient resource manipulation without any intermittent execution of the claimed tasks by the mobile devices, while it significantly reduces crash failures that lead all servers to become unavailable within a rack. In addition, this paper presents a modular resource migration scheme for failure-aware resource allocation, where according to the estimated performance of the resource sharing process (e.g. access time, service delay etc.) resources are migrated to another cloud rack based on the associated performance-oriented metrics. The proposed architecture is thoroughly evaluated through simulation tests for the resource migration policy used in the context of cloud rack failures for delay-bounded resource availability of mobile users, as well as for the efficiency of the proposed resource migration scheme.

[1]  George Mastorakis,et al.  Using Real-Time Backward Traffic Difference Estimation for Energy Conservation in Wireless Devices , 2012, AP2PS 2012.

[2]  Helen D. Karatza,et al.  Parallel Job Scheduling on a Dynamic Cloud Model with Variable Workload and Active Balancing , 2012, 2012 16th Panhellenic Conference on Informatics.

[3]  Byung-Gon Chun,et al.  Augmented Smartphone Applications Through Clone Cloud Execution , 2009, HotOS.

[4]  Ulrich Drepper,et al.  The Cost of Virtualization , 2008, ACM Queue.

[5]  George Mastorakis,et al.  Maximizing energy conservation in a centralized cognitive radio network architecture , 2013, 2013 IEEE 18th International Workshop on Computer Aided Modeling and Design of Communication Links and Networks (CAMAD).

[6]  Dan Meng,et al.  Failure Rules Based Node Resource Provision Policy for Cloud Computing , 2010, International Symposium on Parallel and Distributed Processing with Applications.

[7]  George Mastorakis,et al.  An energy-efficient routing protocol for ad-hoc cognitive radio networks , 2013, 2013 Future Network & Mobile Summit.

[8]  Mahadev Satyanarayanan,et al.  Towards seamless mobility on pervasive hardware , 2005, Pervasive Mob. Comput..

[9]  Byung-Gon Chun,et al.  CloneCloud: elastic execution between mobile device and cloud , 2011, EuroSys '11.

[10]  Kashi Venkatesh Vishwanath,et al.  Characterizing cloud computing hardware reliability , 2010, SoCC '10.

[11]  Rajkumar Buyya,et al.  Utility Computing and Global Grids , 2006, ArXiv.

[12]  Constandinos X. Mavromoustakis.  On the impact of caching and a model for storage-capacity measurements for energy conservation in asymmetrical wireless devices , 2008, 2008 16th International Conference on Software, Telecommunications and Computer Networks.

[13]  Joris Slegers,et al.  Evaluating the optimal server allocation policy for clusters with on/off sources , 2009, Perform. Evaluation.

[14]  Evangelos Kotsovinos.  Virtualization: blessing or curse? , 2011, Commun. ACM.

[15]  P. Mell,et al.  The NIST Definition of Cloud Computing , 2011 .

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

[17]  Oualid Jouini.  Analysis of a last come first served queueing system with customer abandonment , 2012, Comput. Oper. Res..

[18]  David A. Maltz,et al.  Network traffic characteristics of data centers in the wild , 2010, IMC '10.

[19]  M. Wiboonrat.  An Empirical Study on Data Center System Failure Diagnosis , 2008, 2008 The Third International Conference on Internet Monitoring and Protection.

[20]  Rajkumar Buyya,et al.  Utility Computing on Global Grids , 2012 .

[21]  George Mastorakis,et al.  On the performance response of delay-bounded energy-aware bandwidth allocation scheme in wireless networks , 2013, 2013 IEEE International Conference on Communications Workshops (ICC).

[22]  Odej Kao,et al.  Nephele: efficient parallel data processing in the cloud , 2009, MTAGS '09.

[23]  Constandinos X. Mavromoustakis,et al.  Resource and Scheduling Management in Cloud Computing Application Paradigm , 2013 .