Some New Methods for Ready Queue Processing Time Estimation Problem in Multiprocessing Environment

Abstract

Ready queue processing time estimation problem deals with many constraints. Because the processes which reside in the ready queue of computer memory come in varieties such as process size, process requirement indifferences and process types. To match up all these differences is a difficult task to solve so that the processes can be used to perform its task efficiently at any platform. A prior estimation of ready queue processing time helps to meet the system reliability and robustness. A pre-calculated time will ensure the system from failure; also, the backup of task performed can be maintained. In this paper, the existing methods on this approach are described, and how some new methods can be used for the better performance is demonstrated. For this purpose, some sampling techniques are used, and the lottery scheduling procedure is explained which very efficiently performs this task of scheduling on the basis of probabilistic approach and randomness property. The estimation is performed by using sampling methods; with the help of some mathematical calculations, the results are obtained, and finally, confidence interval will ensure the accuracy of the result. So that some new methods can be generated; this provides the result as more efficient than the previous ones. Although various scheduling schemes are available, the lottery scheduling scheme provides the fairness and also removes starvation. Rather than working on the complete data set, some samples can be generated to modularize the work which will be efficient too. So, this paper proposed some new methods in ready queue processing time estimation in multiprocessor environment.