The High Performance of a Task Scheduling Algorithm Using Reference Queues for Cloud- Computing Data Centers

Abstract

As the network technology continues to grow at a high rate of speed, the traditional network topology is improved with novel distributed topologies such as the Cloud computing network. A cloud computing environment consists of a huge number of processors and memories, high-speed networks, and various application services to provide a lot of services over the Internet for users. However, many services need to search for suitable service nodes, and the workload of each node can be unbalanced. Based on the reason above, the Reference Queue based Cloud Service Architecture (RQCSA) and Fitness Service Queue Selection Mechanism (FSQSM) are proposed to handle more tasks, lower the makespan and queue waiting time, and improve efficiency. Moreover, the tasks can be distributed more evenly to avoid overloading cluster managers and lower the efficiency of the system.