Double threshold energy aware load balancing in cloud computing

Nowadays implementation of local cloud is popular, organization are becoming aware of power consumed by unutilized resources. Reducing power consumption has been an essential requirement for cloud environments not only to decrease operating cost but also improve the system reliability. The energy-aware computing is not just to make algorithms run as fast as possible, but also to minimize energy requirements for computation. Our DT-PALB (Double Threshold Energy Aware Load Balancing) algorithm maintains the state of all compute nodes, and based on utilization percentages, decides the number of compute nodes that should be operating. We show that our solution provides adequate availability to compute node resources while decreasing the overall power consumed by the local cloud as compared to using load balancing techniques that are power aware.

[1]  Rajkumar Buyya,et al.  Managing Overloaded Hosts for Dynamic Consolidation of Virtual Machines in Cloud Data Centers under Quality of Service Constraints , 2013, IEEE Transactions on Parallel and Distributed Systems.

[2]  BuyyaRajkumar,et al.  Managing Overloaded Hosts for Dynamic Consolidation of Virtual Machines in Cloud Data Centers under Quality of Service Constraints , 2013 .

[3]  Hoi Chan,et al.  Dynamic Resource Allocation via Distributed Decisions in Cloud Environment , 2011, 2011 IEEE 8th International Conference on e-Business Engineering.

[4]  R. Prasad,et al.  Comparison of load balancing algorithms in a Cloud , 2012 .

[5]  Rajkumar Buyya,et al.  Energy-Efficient Management of Data Center Resources for Cloud Computing: A Vision, Architectural Elements, and Open Challenges , 2010, PDPTA.

[6]  Saudi Arabia,et al.  PERFORMANCE EVALUATION OF A CLOUD BASED LOAD BALANCER SEVERING PARETO TRAFFIC , 2011 .

[7]  Bu-Sung Lee,et al.  Optimization of Resource Provisioning Cost in Cloud Computing , 2012, IEEE Transactions on Services Computing.

[8]  Xuejie Zhang,et al.  A load balancing mechanism based on ant colony and complex network theory in open cloud computing federation , 2010, 2010 The 2nd International Conference on Industrial Mechatronics and Automation.

[9]  Ching-Chi Lin,et al.  Energy-efficient Virtual Machine Provision Algorithms for Cloud Systems , 2011, 2011 Fourth IEEE International Conference on Utility and Cloud Computing.

[10]  R. Yamini,et al.  Power management in cloud computing using green algorithm , 2012, IEEE-International Conference On Advances In Engineering, Science And Management (ICAESM -2012).

[11]  Chen Jing,et al.  A dynamic and integrated load-balancing scheduling algorithm for Cloud datacenters , 2011, 2011 IEEE International Conference on Cloud Computing and Intelligence Systems.

[12]  Jeffrey M. Galloway,et al.  Power Aware Load Balancing for Cloud Computing , 2011 .

[13]  Rajkumar Buyya,et al.  Adaptive threshold-based approach for energy-efficient consolidation of virtual machines in cloud data centers , 2010, MGC '10.

[14]  Djamal Zeghlache,et al.  Minimum Cost Maximum Flow Algorithm for Dynamic Resource Allocation in Clouds , 2012, 2012 IEEE Fifth International Conference on Cloud Computing.

[15]  Zenon Chaczko,et al.  Availability and Load Balancing in Cloud Computing , 2011 .