Abstract
Public cloud providers provide Infrastructure as a Service (IaaS) to remote users. For IaaS providers, how to schedule tasks to meet peak demand is a big challenge. Previous researches proposed purchasing machines in advance or building cloud federation to resolve this problem. However, the former is not economic and the latter is hard to be put into practice at present. In this paper, we propose a hybrid cloud architecture, in which an IaaS provider can outsource its tasks to External Clouds (ECs) without establishing any agreement or standard when its local resources are not sufficient. The key issue is how to allocate users’ tasks to maximize its profit while guarantee QoS. The problem is formulated as a Deadline Constrained Task Scheduling (DCTS) problem which is resolved by standard particle swarm optimization (PSO), and compared with an exact approach (CPLEX). Experiment results show that Standard-PSO is very effective for this problem.
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Zhang, G., Zuo, X. (2013). Deadline Constrained Task Scheduling Based on Standard-PSO in a Hybrid Cloud. In: Tan, Y., Shi, Y., Mo, H. (eds) Advances in Swarm Intelligence. ICSI 2013. Lecture Notes in Computer Science, vol 7928. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-38703-6_24
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DOI: https://doi.org/10.1007/978-3-642-38703-6_24
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