Task scheduling in distributed computing systems with a genetic algorithm

Scheduling a directed acyclic graph (DAG) which represents the precedence relations of the tasks of a parallel program in a distributed computing system (DCS) is known as an NP-complete problem except for some special cases. Many heuristic-based methods have been proposed under various models and assumptions. A DCS can be classified in two types according to the characteristics of the processors on a network: a distributed homogeneous system (DHOS) and a distributed heterogeneous system (DHES). The paper defines a general model for a DHOS and a DHES and presents a genetic algorithm (GA) to solve the task scheduling problem in the defined DCS. The performance of the proposed GA is compared with the list scheduling algorithm in a DHOS and with the one-level reach-out greedy algorithm (OLROG) in a DHES. The proposed GA has shown better performance in various environments than other scheduling methods.