SDN-based server clusters with dynamic load balancing and performance improvement

Abstract

Software-defined networking (SDN) is a state-of-the-art architectural approach to network management that allows more flexible management of a complicated large-scale network. For providing services with high performance, availability, and scalability, server clustering is widely used. This study develops a server cluster based on OpenFlow, which is the most common SDN protocol. To utilize cluster resources effectively, this study focuses on the server-side load-balancing issue and increases the performance for a cluster of servers with different processing capabilities. We have proposed a novel load balancing algorithm, named dynamic weighted random selection (DWRS). DWRS considers the real-time server loads when dispatching requests to servers. Underutilized servers are assigned higher weights, so they have a higher possibility of being selected to process requests. To increase system performance, we modify the flow of packet handling in the Floodlight controller. A multi-threaded technique is used to effectively utilize the parallel processing capability of multiple cores, which speeds up the processing of packet-in messages when selecting the target server. This prevents the controller from becoming overloaded, especially when a large number of packet-in messages arrive. To demonstrate effectiveness and feasibility, we deploy our experimental environment using real hardware, instead of using Mininet to set up a virtual SDN testbed. Experimental results show that the proposed DWRS with multi-threaded implementation outperforms other policies, especially in a heterogeneous environment.