基于粒子群算法的工作流服务主体优选方法

Preferential Choice Scheme of Workflow Service Provider Based on Particle Swarm Optimization

研究工作流服务主体优选问题,在工作流系统中,工作机负载能力有差异性,而且整个系统负载具有动态性,传统算法难以获得最优工作流服务主体优选方案,导致系统资源利用率较低.为了提高系统资源利用率,系统负载保持均衡,提出一种粒子群算法的工作流服务主体优选方法.首先对工作流服务主体优选问题建立相应数学模型,然后采用粒子群算法对其进行求解,即工作流服务主体最优选择方案,最后进行仿真测试.测试结果表明,相对于传统方法,粒子群算法可以针对不同类型的任务分配不同的工作机,实现系统多种资源的负载均衡,提高系统资源的利用率.

Research on workflow service subject selection issues,in workflow management system,work load ability difference,and the system load is dynamic,the traditional algorithm is difficult to obtain the optimal workflow service subject optimization scheme,leading to low utilization rate of system resources.In order to keep the system responsible for balance,raise the utilization rate of resources system,a method based on particle swarm algorithm optimization method of workflow service subject.The workflow services body preferably built corresponding mathematical model,and then the particle swarm optimization algorithm to solve the model,workflow service main body the optimal solution,finally carries on the simulation test.The test results show that,compared with the traditional method,particle swarm optimization algorithm can be used for different types of task allocation in different working machine,improve the utilization rate of system resources,to achieve a variety of resource load balancing system.