Server Load Balancing in Software-Defined Networks

Nowadays, web servers have to respond to the huge amount of requests; therefore, balancing the load between server replicas becomes vital and critical. Conventional load balancers have been dedicated hardware that is susceptible being a single point of failure, vendor-dependent and not flexible. In this work, we propose a flexible and programmable scheduling algorithm that ponders different type of requests, various server processing capacity based upon their CPU, memory usage, I/O rate, and a number of connections. This algorithm uses optimization algorithm, considering not only load of servers but also network congestion. The proposed algorithm includes four main phases. The first two phases have the responsibility of creating sub-topology that causes to increase performance and scalability of the proposed algorithm by reduction of overall solution space. In the third phase, the joint optimal network and server-side load balancing approach are performed, and in the last phase, the post-processing is performed in order to select the server, creates a path, and injects appropriate flow table entries on the OpenFlow switches. The evaluation results show that the dynamic load balancing algorithm significantly decreases response-time whereas increases throughput, in comparison with the existing load balancing algorithms.