Towards a novel service broker policy for choosing the appropriate data center in cloud environments

Providing cloud computing services leads to quick access of users to dynamic and distributed resources. Increasing demand has created challenges such as resource availability, privacy, and security to provide efficient services in cloud computing. Cloud environments contain various computing resources, and allocating a suitable node to process a request can improve the quality of service on a large scale. Load balancing is one of the strategies to improve service quality and resource utilization, which refers to the distribution of load among different nodes in a distributed system. The cloud application service broker is responsible for load balancing by choosing the appropriate geo-distributed datacenter to process the requests of each end user. Parameters such as transmission delay, network delay, processing time, number of servers, workload, and service cost can be considered to select a suitable datacenter in close proximity. To reduce the adverse effects of choosing a datacenter by a service broker, this paper presents Rank-based Load Balancing in Geo-Distributed datacenters (RLBGD) as an effective service broker strategy in cloud environments. RLBGD uses a weighted combination of several criteria such as processing time, number of servers, workload, processing speed, service cost, and response time for dynamic ranking and determining the appropriate datacenter. CloudAnalyst tool is used to simulate and analyze the performance of the proposed method. The results of experiments show the effectiveness of RLBGD in terms of metrics such as service cost and processing time in different scenarios.