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Task-Based System Load Balancing in Cloud Computing Using Particle Swarm Optimization

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Abstract

Live virtual machine (VM) migration is a technique for achieving system load balancing in a cloud environment by transferring an active VM from one physical host to another. This technique has been proposed to reduce the downtime for migrating overloaded VMs, but it is still time- and cost-consuming, and a large amount of memory is involved in the migration process. To overcome these drawbacks, we propose a Task-based System Load Balancing method using Particle Swarm Optimization (TBSLB-PSO) that achieves system load balancing by only transferring extra tasks from an overloaded VM instead of migrating the entire overloaded VM. We also design an optimization model to migrate these extra tasks to the new host VMs by applying Particle Swarm Optimization (PSO). To evaluate the proposed method, we extend the cloud simulator (Cloudsim) package and use PSO as its task scheduling model. The simulation results show that the proposed TBSLB-PSO method significantly reduces the time taken for the load balancing process compared to traditional load balancing approaches. Furthermore, in our proposed approach the overloaded VMs will not be paused during the migration process, and there is no need to use the VM pre-copy process. Therefore, the TBSLB-PSO method will eliminate VM downtime and the risk of losing the last activity performed by a customer, and will increase the Quality of Service experienced by cloud customers.

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Notes

  1. Computing intensive is a term that applies to any computer application (task) that demands extensive computation, such as meteorology programs and other scientific applications.

  2. Data intensive is defined as a characterized application (task) by high volumes of data to be published and maintained over time.

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Authors and Affiliations

  1. Decision Systems and e-Service Intelligence Lab, Faculty of Engineering and Information Technology, Centre for Quantum Computation and Intelligent Systems, School of Software, University of Technology, Sydney, Sydney, Australia

    Fahimeh Ramezani, Jie Lu & Farookh Khadeer Hussain

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  1. Fahimeh Ramezani
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  2. Jie Lu
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  3. Farookh Khadeer Hussain
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Correspondence to Fahimeh Ramezani.

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Ramezani, F., Lu, J. & Hussain, F.K. Task-Based System Load Balancing in Cloud Computing Using Particle Swarm Optimization. Int J Parallel Prog 42, 739–754 (2014). https://doi.org/10.1007/s10766-013-0275-4

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  • DOI: https://doi.org/10.1007/s10766-013-0275-4

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