چکیده (انگلیسی):

Grid computing plays an important role in solving largescale
computational problems in a high performance computing
environment. Scheduling of tasks to efficient and best suitable resource
is one of the most challenging phase in grid computing systems. Grid
environment reveals several challenges in efficient scheduling of
complex applications because of its heterogeneity, dynamic behavior
and shared resources. Scheduling of independent tasks in grid
computing is dealt by a number of heuristic algorithms. This study
proposes a new heuristic algorithm for mapping independent tasks in a
grid environment to be assigned optimally among the available
machines in a grid computing system. Due to the multi-objective
nature of the grid scheduling problem, several performance measures
and optimization criteria can be assumed to determine the quality of a
given schedule. The metrics used here include makespan and resource
utilization. This algorithm provides effective resource utilization by
reducing machine idle time and minimizes makespan. This algorithm
also balances load among the grid resources and produce high resource
utilization with low computational complexity. The proposed algorithm
is compared with other popular heuristics for performance measures.