METHOD FOR TASK SCHEDULING WITH GRANULARITY OF TASKS AND HOSTS FOR GRID-SYSTEM

Abstract

This study aims to increase the productivity of grid systems by an improved scheduling method. A brief overview and analysis of the main scheduling methods in grid systems are presented. A method for increasing efficiency by optimizing the task graph structure considering the grid system node structure is proposed. Depending on the selection of the optimization criterion of the optimal node search problem, a subset of nodes is determined, which provide the start-up of the complement in a minimum time, then, node with minimum cost is selected. Task granularity (the ratio between the amount of computation and transferred data) is considered to increase the efficiency of planning. An analysis of the impact on task scheduling efficiency in a grid system is presented. A correspondence of the task graph structure considering the node structure (in which the task is immersed) to the effectiveness of scheduling in a grid system is shown. The basic scheduling algorithm for consideration and modification is the Maui hierarchical scheduler algorithm. A modified method for scheduling tasks while considering their granularity is proposed. As part of this work, you have developed the GridSim toolbox by adding new entities to simulate planning and workflow processes in the grid-environment. The relevant algorithm for task scheduling in a grid system is developed. Simulation of the proposed algorithm using the modeling system GridSim is conducted. A comparative analysis between the modified algorithm and the algorithm of the hierarchical scheduler Maui is shown. The general advantages and disadvantages of the proposed algorithm are discussed. As a result of program operation, generated diagrams of loading of Grid-system nodes and communication channels. With the help of this program there was performed analysis of load of system nodes at different relations between number of tasks and Grid-system nodes. As the task queue increases, the efficiency of the modified scheduling algorithm increases significantly due to the higher and even loading of nodes and communication channels. With a modified algorithm, scheduling increases scheduler decision time.