Cloudlet Scheduling with Particle Swarm Optimization

Cloud computing is a particularly interesting and truly complex concept of providing services over networks on demand. Many tools have previously been created to simulate the work of the clouds, such as CloudSim. The main use of these tools is evaluation and testing of architectures and services before deployment on network centers and hosts in order to avoid any potential failures or inconveniences. The benefits of using the pay-per-use clouds may be affected by underutilization of the already reserved resources, so the maximization of system utilization while simultaneously minimizing makespan is of great interest to cloud providers wishing to reduce costs. To minimize makespan and increase resource utilization, a hybrid of particle swarm optimization and simulated annealing is implemented inside of CloudSim to advance the work of the already implemented simple broker. The new method maximizes the resource utilization and minimizes the makespan.

[1]  Fangchun Yang,et al.  Energy-aware and revenue-enhancing Combinatorial Scheduling in Virtualized of Cloud Datacenter , 2012 .

[2]  Jinkuan Wang,et al.  Research on Resource Scheduling of Cloud Based on Improved Particle Swarm Optimization Algorithm , 2013, BICS.

[3]  R. Eberhart,et al.  Comparing inertia weights and constriction factors in particle swarm optimization , 2000, Proceedings of the 2000 Congress on Evolutionary Computation. CEC00 (Cat. No.00TH8512).

[4]  P. Mell,et al.  The NIST Definition of Cloud Computing , 2011 .

[5]  Hongli Zhang,et al.  A PSO-Based Hierarchical Resource Scheduling Strategy on Cloud Computing , 2012, ISCTCS.

[6]  James Kennedy,et al.  Particle swarm optimization , 2002, Proceedings of ICNN'95 - International Conference on Neural Networks.

[7]  Seyyed Mohsen Hashemi,et al.  A Review of Workflow Scheduling in Cloud Computing Environment , 2012 .

[8]  Gao Yue-lin,et al.  A New Particle Swarm Optimization Algorithm with Random Inertia Weight and Evolution Strategy , 2007, 2007 International Conference on Computational Intelligence and Security Workshops (CISW 2007).

[9]  Kamran Zamanifar,et al.  A Novel Particle Swarm Optimization Approach for Grid Job Scheduling , 2009, ICISTM.

[10]  S. N. Sivanandam,et al.  Multiprocessor Scheduling Using Hybrid Particle Swarm Optimization with Dynamically Varying Inertia , 2007, Int. J. Comput. Sci. Appl..

[11]  R. Eberhart,et al.  Empirical study of particle swarm optimization , 1999, Proceedings of the 1999 Congress on Evolutionary Computation-CEC99 (Cat. No. 99TH8406).

[12]  Hongying Huo,et al.  Improved PSO-based Task Scheduling Algorithm in Cloud Computing , 2012 .

[13]  Naveen Sharma,et al.  Towards autonomic workload provisioning for enterprise Grids and clouds , 2009, 2009 10th IEEE/ACM International Conference on Grid Computing.

[14]  Jun Zhang,et al.  An Ant Colony Optimization Approach to a Grid Workflow Scheduling Problem With Various QoS Requirements , 2009, IEEE Transactions on Systems, Man, and Cybernetics, Part C (Applications and Reviews).

[15]  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.

[16]  N Jaisankar,et al.  Comparison of Probabilistic Optimization Algorithms for Resource Scheduling in Cloud Computing Environment , 2013 .

[17]  Ethel Mokoto,et al.  Scheduling to Minimize the Makespan on Identical Parallel Machines: An LP-Based Algorithm , 1998 .

[18]  Russell C. Eberhart,et al.  A discrete binary version of the particle swarm algorithm , 1997, 1997 IEEE International Conference on Systems, Man, and Cybernetics. Computational Cybernetics and Simulation.

[19]  Octavian Morariu,et al.  A genetic algorithm for workload scheduling in cloud based e-learning , 2012, CloudCP '12.

[20]  Pisut Pongchairerks Particle swarm optimization algorithm applied to scheduling problems , 2009 .

[21]  Yuehui Chen,et al.  A Task Scheduling Algorithm Based on PSO for Grid Computing , 2008 .

[22]  Imtiaz Ahmad,et al.  Particle swarm optimization for task assignment problem , 2002, Microprocess. Microsystems.

[23]  Rajkumar Buyya,et al.  CloudSim: a toolkit for modeling and simulation of cloud computing environments and evaluation of resource provisioning algorithms , 2011, Softw. Pract. Exp..

[24]  Dan Tsafrir,et al.  Experience with using the Parallel Workloads Archive , 2014, J. Parallel Distributed Comput..

[25]  Yang Cao,et al.  Comparison of Job Scheduling Policies in Cloud Computing , 2013 .

[26]  Warren Smith,et al.  Benchmarks and Standards for the Evaluation of Parallel Job Schedulers , 1999, JSSPP.

[27]  Vahid Rafe,et al.  A survey on heuristic task scheduling on distributed systems , 2013 .

[28]  Rajkumar Buyya,et al.  Nature's heuristics for scheduling jobs on Computational Grids , 2000 .

[29]  Kusum Deep,et al.  Application of Globally Adaptive Inertia Weight PSO to Lennard-Jones Problem , 2011, SocProS.