An energy-efficient enhanced virtual resource provision middleware in clouds

In the past few years, cloud computing has emerged as a promising paradigm for delivering IT-infrastructures, platforms, applications and services. The consolidation of this new paradigm in both commercial business and academic research requires that the underlying resources should be economically managed. In this paper, we present a resource provision framework, which is aiming at improving the energy-efficiency of cloud-based data centres. The proposed framework is implemented as a lightweight middleware, which consists of three novel services that enable cloud providers to up/down scale their virtual resource pool in an efficient manner. Extensive experiments are conducted to evaluate the effectiveness and the performance of the proposed middleware in real-world cloud platform. The results indicate that it can significantly improving the energy-efficiency in virtualised clouds without significantly degradation on application performance.

[1]  Rajkumar Buyya,et al.  CloudSim: a toolkit for modeling and simulation of cloud computing environments and evaluation of resource provisioning algorithms , 2011, Softw. Pract. Exp..

[2]  Fred Douglis,et al.  Staring at Clouds , 2009, IEEE Internet Comput..

[3]  Asser N. Tantawi,et al.  Experience with Collaborating Managers: Node Group Manager and Provisioning Manager , 2005, ICAC.

[4]  Rajkumar Buyya,et al.  The Aneka platform and QoS-driven resource provisioning for elastic applications on hybrid Clouds , 2012, Future Gener. Comput. Syst..

[5]  Albert Y. Zomaya,et al.  Profit-Driven Service Request Scheduling in Clouds , 2010, 2010 10th IEEE/ACM International Conference on Cluster, Cloud and Grid Computing.

[6]  Luís Veiga,et al.  Heuristic for resources allocation on utility computing infrastructures , 2008, MGC '08.

[7]  Pasi Tyrväinen,et al.  Economic aspects of hybrid cloud infrastructure: User organization perspective , 2011, Information Systems Frontiers.

[8]  Niraj K. Jha,et al.  A Trusted Virtual Machine in an Untrusted Management Environment , 2012, IEEE Transactions on Services Computing.

[9]  Naveen Sharma,et al.  Towards autonomic workload provisioning for enterprise Grids and clouds , 2009, 2009 10th IEEE/ACM International Conference on Grid Computing.

[10]  Ricardo Graciani Diaz,et al.  Belle-DIRAC Setup for Using Amazon Elastic Compute Cloud , 2010, Journal of Grid Computing.

[11]  Eddy Caron,et al.  Using clouds to scale grid resources: An economic model , 2012, Future Gener. Comput. Syst..

[12]  Laurent Lefèvre,et al.  Designing and evaluating an energy efficient Cloud , 2010, The Journal of Supercomputing.

[13]  Carole A. Goble,et al.  CaGrid Workflow Toolkit: A taverna based workflow tool for cancer grid , 2010, BMC Bioinformatics.

[14]  Andrew Warfield,et al.  Xen and the art of virtualization , 2003, SOSP '03.

[15]  Rajarshi Das,et al.  Towards Commercialization of Utility-based Resource Allocation , 2006, 2006 IEEE International Conference on Autonomic Computing.

[16]  Jordi Torres,et al.  Economic model of a Cloud provider operating in a federated Cloud , 2012, Inf. Syst. Frontiers.

[17]  Qian Zhu,et al.  Resource Provisioning with Budget Constraints for Adaptive Applications in Cloud Environments , 2012, IEEE Trans. Serv. Comput..

[18]  Khaled Z. Ibrahim,et al.  Characterizing the Performance of Parallel Applications on Multi-socket Virtual Machines , 2011, 2011 11th IEEE/ACM International Symposium on Cluster, Cloud and Grid Computing.

[19]  Eero Vainikko,et al.  Adapting scientific computing problems to clouds using MapReduce , 2012, Future Gener. Comput. Syst..

[20]  Marius Hillenbrand,et al.  High performance cloud computing , 2013, Future Gener. Comput. Syst..

[21]  Sujata Banerjee,et al.  On energy efficiency for enterprise and data center networks , 2011, IEEE Communications Magazine.

[22]  Jeffrey S. Chase,et al.  Automated control in cloud computing: challenges and opportunities , 2009, ACDC '09.

[23]  Eyal de Lara,et al.  SnowFlock: rapid virtual machine cloning for cloud computing , 2009, EuroSys '09.

[24]  Andreas Polze,et al.  Trends and challenges in operating systems—from parallel computing to cloud computing , 2012, Concurr. Comput. Pract. Exp..

[25]  Young Ik Eom,et al.  VMMB: Virtual Machine Memory Balancing for Unmodified Operating Systems , 2012, Journal of Grid Computing.

[26]  Xilong Qu,et al.  Virtual machine power measuring technique with bounded error in cloud environments , 2013, J. Netw. Comput. Appl..