Avian Based Intelligent Algorithm to Provide Zero Tolerance Load Balancer for Cloud Based Computing Platforms

Abstract

Artificial intelligence changes the art of solving the computational problems from defined computing structures into disorganized computing structures with the interference of naturally-inspired activities. On this basis, many algorithms were proposed and applied successfully, those results give complete as well as partial solutions for their applications. In this article, the authors consider the same phenomena and the investigation area is a load balancer. The legitimate aim is to bring a zero-tolerance load balancer by applying artificial intelligence techniques. For this, the authors introduced an algorithm named the Eagle Fly algorithm, which is a natural inspired algorithm, completely based on eagle characteristic behavior. From this, the authors examine how tasks are fetched, computed, and server on-demands are supported. This article proves performance metrics received from eagle fly algorithm is good and the results were compared with other existing natural inspired algorithms.