Energy aware scheduling of deadline-constrained tasks in cloud computing

Energy efficiency is the predominant issue which troubles the modern ICT industry. The ever-increasing ICT innovations and services have exponentially added to the energy demands and this proliferated the urgency of fostering the awareness for development of energy efficiency mechanisms. But for a successful and effective accomplishment of such mechanisms, the support of underlying ICT platform is significant. Eventually, Cloud computing has gained attention and has emerged as a panacea to beat the energy consumption issues. This paper scrutinizes the importance of multicore processors, virtualization and consolidation techniques for achieving energy efficiency in Cloud computing. It proposes Green Cloud Scheduling Model (GCSM) that exploits the heterogeneity of tasks and resources with the help of a scheduler unit which allocates and schedules deadline-constrained tasks delimited to only energy conscious nodes. GCSM makes energy-aware task allocation decisions dynamically and aims to prevent performance degradation and achieves desired QoS. The evaluation and comparative analysis of the proposed model with two other techniques is done by setting up a Cloud environment. The results indicate that GCSM achieves 71 % of energy savings and high performance in terms of deadline fulfillment.

[1]  San Murugesan,et al.  Harnessing Green IT: Principles and Practices , 2008, IT Professional.

[2]  Shailesh S. Deore,et al.  Energy-Efficient Scheduling Scheme for Virtual Machines in Cloud Computing , 2012 .

[3]  Shin Gyu Kim,et al.  Virtual machine scheduling for multicores considering effects of shared on-chip last level cache interference , 2012, 2012 International Green Computing Conference (IGCC).

[4]  Inderveer Chana,et al.  Resource Scheduling Techniques in Utility Computing: A Survey , 2014, Int. J. Syst. Serv. Oriented Eng..

[5]  Maziar Goudarzi,et al.  Variation-aware Server Placement and Task Assignment for Data Center Power Minimization , 2012, 2012 IEEE 10th International Symposium on Parallel and Distributed Processing with Applications.

[6]  Ching-Hsien Hsu,et al.  Energy-Efficient Resource Provisioning with SLA Consideration on Cloud Computing , 2012, 2012 41st International Conference on Parallel Processing Workshops.

[7]  Pascal Bouvry,et al.  Intelligent Decision Systems in Large-Scale Distributed Environments , 2011, Studies in Computational Intelligence.

[8]  Stéphane Vialle,et al.  Optimizing Computing and Energy Performances in Heterogeneous Clusters of CPUs and GPUs , 2012, Handbook of Energy-Aware and Green Computing.

[9]  J. Koomey Rebuttal to testimony on 'Kyoto and the internet: The energy implications of the digital economy' - eScholarship , 2000 .

[10]  Tharam S. Dillon,et al.  Cloud Computing: Issues and Challenges , 2010, 2010 24th IEEE International Conference on Advanced Information Networking and Applications.

[11]  Yue Gao,et al.  An energy and deadline aware resource provisioning, scheduling and optimization framework for cloud systems , 2013, 2013 International Conference on Hardware/Software Codesign and System Synthesis (CODES+ISSS).

[12]  Dang Minh Quan,et al.  T-Alloc: A practical energy efficient resource allocation algorithm for traditional data centers , 2012, Future Gener. Comput. Syst..

[13]  Xuejie Zhang,et al.  Design and implementation of an efficient load-balancing method for virtual machine cluster based on cloud service , 2011 .

[14]  Inderveer Chana,et al.  Artificial bee colony based energy‐aware resource utilization technique for cloud computing , 2015, Concurr. Comput. Pract. Exp..

[15]  Rajkumar Buyya,et al.  Energy Efficient Allocation of Virtual Machines in Cloud Data Centers , 2010, 2010 10th IEEE/ACM International Conference on Cluster, Cloud and Grid Computing.

[16]  R. Buyya,et al.  Green Cloud Computing and Environmental Sustainability , 2012 .

[17]  Christof Fetzer,et al.  Energy-aware scheduling for infrastructure clouds , 2012, 4th IEEE International Conference on Cloud Computing Technology and Science Proceedings.

[18]  Debora Di Giacomo,et al.  Cloud Computing Evaluation : How it Differs to Traditional IT Outsourcing , 2010 .

[19]  Albert Y. Zomaya,et al.  Priority-Based Scheduling for Large-Scale Distribute Systems with Energy Awareness , 2011, 2011 IEEE Ninth International Conference on Dependable, Autonomic and Secure Computing.

[20]  Sathish Gopalakrishnan,et al.  Sharp utilization thresholds for some realtime scheduling problems , 2009, PERV.

[21]  Ashok Narayan Patil,et al.  Energy-Efficient Job Scheduling and Allocation Scheme for Virtual Machines in Private Clouds , 2013 .

[22]  Dang Minh Quan,et al.  Energy Usage and Carbon Emission Optimization Mechanism for Federated Data Centers , 2012, E2DC.

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

[24]  Inderveer Chana,et al.  Energy Efficiency Techniques in Cloud Computing , 2015, ACM Comput. Surv..

[25]  Andrius Plepys,et al.  The Grey Side of ICT , 2002 .

[26]  Yi Zhong,et al.  State-of-the-art research study for green cloud computing , 2011, The Journal of Supercomputing.

[27]  Hannes Hartenstein,et al.  Confidential database-as-a-service approaches: taxonomy and survey , 2014, Journal of Cloud Computing.

[28]  Albert Y. Zomaya,et al.  A Taxonomy and Survey of Energy-Efficient Data Centers and Cloud Computing Systems , 2010, Adv. Comput..

[29]  Albert Y. Zomaya,et al.  Energy efficient utilization of resources in cloud computing systems , 2010, The Journal of Supercomputing.

[30]  Liang Zhong,et al.  EnaCloud: An Energy-Saving Application Live Placement Approach for Cloud Computing Environments , 2009, 2009 IEEE International Conference on Cloud Computing.

[31]  Rajkumar Buyya,et al.  Offer-based scheduling of deadline-constrained Bag-of-Tasks applications for utility computing systems , 2009, 2009 IEEE International Symposium on Parallel & Distributed Processing.

[32]  Rajkumar Buyya,et al.  Green Cloud Framework for Improving Carbon Efficiency of Clouds , 2011, Euro-Par.

[33]  Roberto Rojas-Cessa,et al.  Greedy scheduling of tasks with time constraints for energy-efficient cloud-computing data centers , 2015, Journal of Cloud Computing.

[34]  Dang Minh Quan,et al.  Energy Efficient Resource Allocation Strategy for Cloud Data Centres , 2011, ISCIS.

[35]  Alan D. George,et al.  The next frontier for communications networks: power management , 2004, Comput. Commun..

[36]  Rajkumar Buyya,et al.  Environment-conscious scheduling of HPC applications on distributed Cloud-oriented data centers , 2011, J. Parallel Distributed Comput..

[37]  Manish Parashar,et al.  Energy-efficient application-aware online provisioning for virtualized clouds and data centers , 2010, International Conference on Green Computing.

[38]  El-Ghazali Talbi,et al.  Parallel Evolutionary Algorithms for Energy Aware Scheduling , 2011, Intelligent Decision Systems in Large-Scale Distributed Environments.

[39]  Subhajyoti Bandyopadhyay,et al.  Cloud computing - The business perspective , 2011, Decis. Support Syst..

[40]  Feng Zhao,et al.  Virtual machine power metering and provisioning , 2010, SoCC '10.

[41]  Rajkumar Buyya,et al.  Optimal online deterministic algorithms and adaptive heuristics for energy and performance efficient dynamic consolidation of virtual machines in Cloud data centers , 2012, Concurr. Comput. Pract. Exp..