Agent Based Queue Aware Scheduling for Distributed Multicore System

In the current world of big data analytics and huge processing request from the client server system the service requirement from the computing cores has been growing exponentially. In this paper we proposed a novel idea wherein the agent will check the ready queue length dynamically and based on the threshold value comparison further scheduling has been done. There are three different variants of scheduling and load balancing are identified with respect to the queue length. Always the queue length is directly proportional to the number of tasks given to a particular node in the distributed system. Compared to the traditional scheduling algorithms, our approach increases the cores' throughput by 2.5%. In addition, we calculated that as compared to the preceding approaches, the typical hold time for work in the ready state has decreased to 1.25%. The primary benefit of this endeavor is when multiple jobs are submitted to the server then the proposed algorithm speed up the process of getting the jobs executed at a faster rate.