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| Multi-tenant Service Customization Algorithm Based on MapReduce and Multi-objective Ant Colony Optimization |
| WANG Hui-Ying1,2,3, NI Zhi-Wei1,2, WU Zhang-Jun1,2 |
1.School of Management, Hefei University of Technology, Hefei 230009.
2.Key Laboratory of Process Optimization and Intelligent Decision Making of Ministry of Education, Hefei University of Technology, Hefei 230009
3.Department of Electronics and Information, Anhui Finance and Trade Vocational College, Hefei 230601 |
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Abstract Multi-tenant service customization is one of the key technologies to facilitate the agile SaaS multi-tenant architecture, and it can meet the ever-changing personalized demands from customers as well. The hierarchical graph and the customization process of multi-tenant service customization are employed in this paper, and a customization algorithm based on MapReduce and multi-objective ant colony optimization (MSCMA) is proposed. The most suitable business process and the optimized service composition can be found out from various business processes and massive services according to the non-functionality requirement of the tenant, and the optimization tasks can be fulfilled in distributed cloud computing environment in parallel by MSCMA. The results of the simulated experiment demostrate that MSCMA shows favorable convergence and scalability in solving multi-tenant service customization and the proposed algorithm has good ability in processing massive data and solving large scale problems.
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Received: 09 September 2013
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2014, Vol. 27 
