DAS: A dynamic assignment scheduling algorithm for stream computing in distributed applications

Due to the unpredictability of continuous data in distributed applications, it is hard for system to deal with data explosion in limited time. As a result, traditional static data storage technology fails to meet the demands for real-time data processing. To improve processing ability, many parallel processing structures are proposed, which brings up the problem that how the parallel machines can be scheduled to maximize their efficiency. Accordingly, a dynamic assignment scheduling algorithm for stream computing is proposed and a stream query graph is built to calculate the weight of every edge. The edge with the minimum weight is selected to send tuples. Simulation results show that the proper number of the logic machines could dramatically reduce system response time. Furthermore, system context switching is reduced by increasing the number of tuples sent every time.