Packet-Based Load Balancing Algorithms for Server Farms Using SDN

Abstract

The role of data centers has been becoming increasingly crucial in recent years, because there has been a growing emphasis on decentralizing data processing in IoT networking. The ability to swiftly respond to incoming requests has emerged as a pivotal metric for assessing data center systems. Load balancing challenges in data centers have persistently posed hurdles, affecting performance enhancement, availability improvement, and cost reduction. In this paper, we delve into the load balancing challenges in SDN-enabled data centers and introduce two novel load balancing methods. One method is the weighted minimum response time approach, while the other employs learning automata for load balancing. The former tackles the issue of server load fluctuations without the bias found in static weighting methods, whereas the latter seeks to equalize server loads for queries with established access patterns. We conducted straightforward computer simulations to evaluate the proposed methods. The results of computer experiments indicate the effectiveness of the proposed methods.