A distributed load balancing and admission control algorithm based on Fuzzy type-2 and Game theory for large-scale SaaS cloud architectures

Abstract

With the advent of cloud computing and virtualization technologies, business models are created to serve users with applications, platforms or processing resources. One of these models is providing software as a service (SaaS) in cloud environments. Due to its user-friendly nature, the demand for SaaS is increasing exponentially in recent years, so geographically distributed cloud infrastructures are required for hosting such services. On the other hand, with the world wide spread of applications, users need to access them all over the world. Common centralized architecture of resources is not responsive and clusters of large-scale distributed servers are required to host applications in different geographical locations. In this paper, a novel two-layer (regional–local) distributed resource management algorithm is proposed which can handle management tasks such as requests admission control and load balancing in large scales. The proposed algorithm is scalable, in which the control tasks are divided among application and proxy servers. Therefore, each component performs the task of managing resources independently. To control the admission of requests, a Self-Adaptive Fuzzy type-2 Controller containing two fuzzy controllers is introduced. Also, for distributing requests and balancing load in the proxy servers, a Game theory based algorithm proposed which converged to Nash equilibrium. The proposed algorithm is implemented and tested using four physical machines. The algorithm is evaluated using two standard dynamic workloads. By deploying this algorithm, the average percentage of rejected requests and LBM value are improved compared to rival algorithms about 15% and 4.5% respectively.