Smart Deployment of Virtual Machines to Reduce Energy Consumption of Cloud Computing Based Data Centers Using Gray Wolf Optimizer

The growth in demand for using cloud computing resources at massive data centers has led to high consumption of energy and, consequently, increased operating costs. Integration of cloud resources makes it possible to save time on the migration of loaded and unprocessed data centers, to qualified data centers, the release of idle nodes, and the reduction of virtual machine virtualization migration.

[1]  Nirwan Ansari,et al.  Optimizing Resource Utilization of a Data Center , 2016, IEEE Communications Surveys & Tutorials.

[2]  Lijun Xu,et al.  Oriented-SLA and Energy-Efficient Virtual Machine Management Strategy of Cloud Data Centers , 2016 .

[3]  Andrzej Kochut,et al.  Dynamic Placement of Virtual Machines for Managing SLA Violations , 2007, 2007 10th IFIP/IEEE International Symposium on Integrated Network Management.

[4]  Sudhir Shenai,et al.  Survey on Scheduling Issues in Cloud Computing , 2012 .

[5]  Lin Li,et al.  Energy Consumption Management of Virtual Cloud Computing Platform , 2017 .

[6]  Musbah Abdulgader,et al.  Efficient energy management for smart homes with grey wolf optimizer , 2017, 2017 IEEE International Conference on Electro Information Technology (EIT).

[7]  Lap-Mou Tam,et al.  A new optimization method, the Algorithm of Changes, for Bin Packing Problem , 2010, 2010 IEEE Fifth International Conference on Bio-Inspired Computing: Theories and Applications (BIC-TA).

[8]  Ayan Banerjee,et al.  Integrating cooling awareness with thermal aware workload placement for HPC data centers , 2011, Sustain. Comput. Informatics Syst..

[9]  Jie Wu,et al.  Energy efficient virtual machine placement algorithm with balanced and improved resource utilization in a data center , 2013, Math. Comput. Model..

[10]  Salima Benbernou,et al.  A survey on service quality description , 2013, CSUR.

[11]  Armel Esnault.  Energy-Aware Distributed Ant Colony Based Virtual Machine Consolidation in IaaS Clouds , 2012 .

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

[13]  Paul Shaw,et al.  A Constraint for Bin Packing , 2004, CP.

[14]  Luiz André Barroso,et al.  The Case for Energy-Proportional Computing , 2007, Computer.

[15]  César A. F. De Rose,et al.  Server consolidation with migration control for virtualized data centers , 2011, Future Gener. Comput. Syst..

[16]  Laurent Lefèvre,et al.  A survey on techniques for improving the energy efficiency of large-scale distributed systems , 2014, ACM Comput. Surv..