A Study Of BNP Parallel Task Scheduling Algorithms Metric's For Distributed Database System

To solve number of complex scientific problems one must require elevated computation rate comparable to supercomputer. The modernization in latest technologies, communication and information lead to the development of distributed systems and parallel systems as an alternate to Super Computer for solving complex mathematical problems. Parallel processing is a method of executing the multiple tasks alongside on different processors. With the help of parallel processing one is able to solve the complex problems that require huge amount of processing time. In parallel processing or in distributed system task scheduling is one of the major problems. Distributed database system is defined as collection of computer that are connected with one another with the help of some network media over which data and tasks are scheduled for faster execution. The objective of this study is to analyze the various metrics of static (HLFET) and dynamic (DLS) BNP parallel scheduling algorithm in allocating the tasks of distributed database over number of processors. In the whole study the focus will be given on measuring the impact of number of processors on different metrics of performance like makespan, speed up and processor utilization by using HLFET and DLS, BNP task scheduling algorithms.