Interaction Artificial Bee Colony Based Load Balance Method in Cloud Computing

Rapidly development of the cloud computing and Internet makes load balance technique become more and more significant to us than ever. A perfect scheduling algorithm is the key to solve the load balance problems which can not only balance the load, but also can meet the users’ needs. An optimal load balance algorithm is proposed in this paper. Algorithm proposed in this paper can enhance production of the systems and schedule the tasks to virtual machines (VMs) more efficiently. Finishing time of all tasks in the same system will be less than others’. The simulation tools is the CloudSim.

[1]  Zheng Jun,et al.  Ant colony optimization algorithm for computing resource allocation based on cloud computing environment (Chinese) , 2010 .

[2]  Ladislau Bölöni,et al.  A Comparison of Eleven Static Heuristics for Mapping a Class of Independent Tasks onto Heterogeneous Distributed Computing Systems , 2001, J. Parallel Distributed Comput..

[3]  Yong Zhao,et al.  Cloud Computing and Grid Computing 360-Degree Compared , 2008, GCE 2008.

[4]  Bao Rong Chang,et al.  Evaluation of Virtual Machine Performance and Virtualized Consolidation Ratio in Cloud Computing System , 2013, J. Inf. Hiding Multim. Signal Process..

[5]  Jeng-Shyang Pan,et al.  Enhanced Artificial Bee Colony Optimization , 2022 .

[6]  Dan Zhu,et al.  Robust and Simple N-Party Entangled Authentication Cloud Storage Protocol Based on Secret Sharing Scheme , 2013, J. Inf. Hiding Multim. Signal Process..

[7]  L. D. Dhinesh Babu,et al.  Honey bee behavior inspired load balancing of tasks in cloud computing environments , 2013, Appl. Soft Comput..

[8]  Carlos Carleos,et al.  Genetic diversity measures of local European beef cattle breeds for conservation purposes , 2001, Genetics Selection Evolution.

[9]  Luis Rodero-Merino,et al.  A break in the clouds: towards a cloud definition , 2008, CCRV.

[10]  A.M. Rahmani,et al.  A Modified Simulated Annealing Algorithm for Static Task Scheduling in Grid Computing , 2008, 2008 International Conference on Computer Science and Information Technology.

[11]  Rajkumar Buyya,et al.  A Particle Swarm Optimization-Based Heuristic for Scheduling Workflow Applications in Cloud Computing Environments , 2010, 2010 24th IEEE International Conference on Advanced Information Networking and Applications.

[12]  Jiang Zuhua,et al.  Multi-objective integrated optimization research on preventive maintenance planning and production scheduling for a single machine , 2008 .