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
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.
WANG Hui-Ying,NI Zhi-Wei,WU Zhang-Jun. Multi-tenant Service Customization Algorithm Based on MapReduce and Multi-objective Ant Colony Optimization[J]. , 2014, 27(12): 1105-1116.
[1] Shi Y L, Luan S, Li Q Z, et al. TLA Based Customization and Ve-rification Mechanism of Business Process for SaaS. Chinese Journal of Computers, 2010, 33(11): 2055-2067 (in Chinese) (史玉良,栾 帅,李庆忠,等.基于TLA的SaaS业务流程定制及验证机制研究.计算机学报, 2010, 33(11): 2055-2067) [2] Lin H L, Han Y B. Performance Management for Multi-tenant Web Applications. Chinese Journal of Computers, 2010, 33(10): 1881-1895 (in Chinese) (林海略,韩燕波.多租户应用的性能管理关键问题研究.计算机学报, 2010, 33(10): 1881-1895) [3] Mietzner R, Metzger A, Leymann F, et al. Variability Modeling to Support Customization and Deployment of Multi-tenant-aware Software as a Service Applications // Proc of the ICSE Workshop on Principles of Engineering Service Oriented Systems. Vancouver, Canada, 2009: 18-25 [4] Zeng L Z, Benatallah B, Ngu A H H, et al. QoS-Aware Middleware for Web Services Composition. IEEE Trans on Software Engineering, 2004, 30(5): 311-327 [5] Canfora G, di Penta M, Esposito R, et al.An Approach for QoS-Aware Service Composition Based on Genetic Algorithms ∥ Proc of the 7th Annual Conference on Genetic and Evolutionary Computation. New York, USA: ACM Press, 2005: 1069-1075 [6] Fan X Q, Jiang C J, Fang X W, et al. Dynamic Web Service Selection Based on Discrete Particle Swarm Optimization. Journal of Computer Research and Development, 2010, 47(1): 147-156 (in Chinese) (范小芹,蒋昌俊,方贤文,等.基于离散微粒群算法的动态Web服务选择.计算机研究与发展, 2010, 47(1): 147-156) [7] Liu S L, Liu Y X, Zhang F, et al. A Dynamic Web Services Selection Algorithm with QoS Global Optimal in Web Services Composition. Journal of Software, 2007, 18(3): 646-656 (in Chinese) (刘书雷,刘云翔,张 帆,等.一种服务聚合中QoS全局最优服务动态选择算法.软件学报, 2007, 18(3): 646-656) [8] Jiang H H, Yang X H, Xu Y, et al. QoS-Aware Multi-path Web Service Composition Using Variable Length Chromosome Genetic Al- gorithm. Computer Integrated Manufacturing Systems, 2011, 17(6): 1334-1343 (in Chinese) (姜红红,杨小虎,徐 远,等.基于变长基因算法的服务质量驱动多路径Web服务组合.计算机集成制造系统, 2011, 17(6): 1334-1343) [9] Jia R Y, Wu Z J, Zhang Y W. Dynamic KaaS Combination Strategy Based on Multi-objective Ant Colony Optimization. Journal of South China University of Technology: Natural Science Edition, 2012, 40(6): 126-131, 158 (in Chinese) (贾瑞玉,伍章俊,张以文.基于多目标蚁群优化的知识即服务动态组合策略.华南理工大学学报:自然科学版, 2012, 40(6): 126-131, 158) [10] Wu H, Ni Z W, Wang H Y. MapReduce-Based Ant Colony Optimization. Computer Integrated Manufacturing Systems, 2012, 18(7): 1503-1509 (in Chinese) (吴 昊,倪志伟,王会颖.基于MapReduce的蚁群算法.计算机集成制造系统, 2012, 18(7): 1503-1509)
2014, Vol. 27 
