Memory Size Estimation of Supercomputing Nodes of Computational Grid using Queuing Theory

Grid computing principles focus on large-scale resource sharing in distributed systems in a flexible, secure and coordinated fashion. The most widespread contemplation is performance, because computational grid servers must offer cost-effective and high-availability services in the elongated period, thus they have to be scaled to meet the expected load. Performance measurements can be the base for performance modeling and prediction. With the help of performance models, the performance metrics (like buffer estimation, waiting time) can be determined at the development process. This paper describes the possible queue models those can be applied in the estimation of queue length to estimate the final value of the memory size. Both simulation and experimental studies using synthesized workloads and analysis of real-world Gateway Servers demonstrate the effectiveness of the proposed system. General Terms Grid Computing, Computational Grid, Distributed Computing, Cloud Computing.