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Issue No. 02 - March-April (2018 vol. 11)
ISSN: 1939-1374
pp: 306-317
Gongzhuang Peng , National CIMS Engineering Research Center, Department of Automation, Tsinghua University, China
Hongwei Wang , School of Engineering, University of Portsmouth, Portsmouth, United Kingdom
Jietao Dong , National CIMS Engineering Research Center, Department of Automation, Tsinghua University, China
Heming Zhang , National CIMS Engineering Research Center, Department of Automation, Tsinghua University, China
ABSTRACT
Cloud computing technologies have enabled a new paradigm for advanced product development powered by the provision and subscription of computational services in a multi-tenant distributed simulation environment. The description of computational resources and their optimal allocation among tenants with different requirements holds the key to implementing effective software systems for such a paradigm. To address this issue, a systematic framework for monitoring, analyzing and improving system performance is proposed in this research. Specifically, a radial basis function neural network is established to transform simulation tasks with abstract descriptions into specific resource requirements in terms of their quantities and qualities. Additionally, a novel mathematical model is constructed to represent the complex resource allocation process in a multi-tenant computing environment by considering priority-based tenant satisfaction, total computational cost and multi-level load balance. To achieve optimal resource allocation, an improved multi-objective genetic alqorithm is proposed based on the elitist archive and the K -means approaches. As demonstrated in a case study, the proposed framework and methods can effectively support the cloud simulation paradigm and efficiently meet tenants’ computational requirements in a distributed environment.
INDEX TERMS
Computational modeling, Cloud computing, Resource management, Collaboration, Load modeling, Optimization, Service-oriented architecture
CITATION

G. Peng, H. Wang, J. Dong and H. Zhang, "Knowledge-Based Resource Allocation for Collaborative Simulation Development in a Multi-Tenant Cloud Computing Environment," in IEEE Transactions on Services Computing, vol. 11, no. 2, pp. 306-317, 2018.
doi:10.1109/TSC.2016.2518161
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