Implementation Methodology of Real-Valued Augmented Simulated Annealing Algorithm for Dependent Task Scheduling

As computing resources are distributed in multiple domains in the Internet, the computational and storage nodes and the underlying networks connecting them are heterogeneous. Thus the heterogeneity results in different capabilities for job processing and data access. To achieve the promising potentials of tremendous distributed resources, effective and efficient scheduling algorithms are fundamentally important. Real-valued Augmented Simulated Annealing (RASA) effectively exploits the essentials of Genetic Algorithm(GA) together with the basic concept of simulated annealing method guiding the search towards minimal energy states. This paper explains the methodology of application of RASA algorithm for the constrained task scheduling problems.