基于MapReduce和多目标蚁群算法的多租户服务定制算法

Multi-tenant Service Customization Algorithm Based on MapReduce and Multi-objective Ant Colony Optimization

多租户服务定制能满足租户不断变化的个性化服务需求,是实现灵活的SaaS多租户软件体系结构的核心技术之一.文中给出多租户服务定制的层次结构图和定制流程,并提出基于MapReduce和多目标蚁群算法的多租户服务定制算法(MSCMA).MSCMA从众多业务流程和海量服务中为租户定制出最适合的业务流程和优化的服务组合,并设计多目标蚁群算法,应用MapReduce云计算技术,在云计算环境中分布式并行地运行优化任务,并采用优良解保持策略和解多样性保持策略.实验表明,MSCMA在求解多租户个性化服务定制问题时表现出良好的收敛性和扩展性,具有处理海量数据和大规模问题的能力.

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 accordin~ to the non-functionalitvrequirement 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.