Abstract
Cloud computing environments facilitate applications by providing virtualized resources that can be provisioned dynamically. Computing resources are delivered by Virtual Machines (VMs). In such a scenario, resource scheduling algorithms play an important role where the aim is to schedule applications effectively so as to reduce the turn-around time and improve resource utilization. In this paper, we present a Particle Swarm Optimization (PSO) based strategy schedules applications to cloud resource taking into account both transmission cost and current load. In addition, a novel inertia weight was introduced in order to get the global search and local search effectively and avoid plunging into the local optimum. Finally, we experiment with application workflows by varying its performance and convergence analysis.
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References
Shi, Y., Eberhart, R.C.: A modified particle swarm optimizer. In: Proceedings of IEEE International Conference on Evolutionary Computation, Anchorage, AK (1998)
Zavala, A.E.M., Aguirre, A.H., Villa Diharce, E.R., Rionda, S.B.: Constrained Optimization with an Improved Particle Swarm Optimization Algorithm. International Journal of Intelligent Computing and Cybernetics (2008)
Cloudsim, http://www.cloudbus.org/cloudsim
Wu, Z., Liu, X., Ni, Z., Yuan, D., Yang, Y.: A market-oriented Hierarchical Scheduling Strategy in Cloud Workflow Systems. The Journal of Supercomputing (2011)
Iosup, A., Ostermann, S., Yigitbasi, N., Prodan, R., Fahringer, T., Epema, D.: Performance Analysis of Cloud Computing Services for Many-tasks Scientific Computing. IEEE Transactions on Parallel and Distributed System (2010)
Lee, Z.Y., Wang, Y.: A Dynamic Priority Scheduling Algorithm on Service Request Scheduling in Cloud Computing. In: Proceeding of the 2011 International Conference on Electronic and Mechanical Engineering and Information Technology (2011)
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Zhang, H., Li, P., Zhou, Z., Yu, X. (2013). A PSO-Based Hierarchical Resource Scheduling Strategy on Cloud Computing. In: Yuan, Y., Wu, X., Lu, Y. (eds) Trustworthy Computing and Services. ISCTCS 2012. Communications in Computer and Information Science, vol 320. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-35795-4_41
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DOI: https://doi.org/10.1007/978-3-642-35795-4_41
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-35794-7
Online ISBN: 978-3-642-35795-4
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