Hierarchical Particle Swarm Optimization with Ortho-Cyclic Circles

Cloud computing is an emerging technology which deals with real world problems that changes dynamically. The users of dynamically changing applications in cloud demand for rapid and efficient service at any instance of time. To deal with this paper proposes a new modified Particle Swarm Optimization (PSO) algorithm that work efficiently in dynamic environments. The proposed Hierarchical Particle Swarm Optimization with Ortho Cyclic Circles (HPSO-OCC) receives the request in cloud from various resources, employs multiple swarm interaction and implements cyclic and orthogonal properties in a hierarchical manner to provide the near optimal solution. HPSO-OCC is tested and analysed in both static and dynamic environments using seven benchmark optimization functions. The proposed algorithm gives the best solution and outperforms in terms of accuracy and convergence speed when compared with the performance of existing PSO algorithms in dynamic scenarios. As a case study, HPSO-OCC is implemented in remote health monitoring application for optimal service scheduling in cloud. The near optimal solution from HPSO-OCC and Dynamic Round Robin Scheduling algorithm is implemented to schedule the services in healthcare.