An Empirical Analysis on Load Balancing and Service Broker Techniques using Cloud Analyst Simulator

Cloud computing technology provides sophisticated IT services that are presented to users in different ways based on their business requirements. Both services and assets are provided automatically at a specified time. Load balancing is one of important approaches that is used in a cloud environment for endorsing the performance level of the cloud resources. The load is allocated in all resources that contribute to the architecture of the virtualized data center to 1) minimize the time of user requests in the data center and to 2) maximize the system throughput. Many load balancing algorithms were developed by researchers in recent years. Those algorithms are classified into two main categories (static algorithms and dynamic algorithms). The main target is to optimize the cloud environment performance by reducing the overall cost by transmitting the user requests to prime nodes. In this paper, an empirical analysis is presented on both (Load Balancing and Service Broker) techniques using cloud analyst simulator. The analysis target is to study the behavior of three different load balancing algorithms (Round Robin, Throttled and Active Monitoring). Those algorithms contain several service broker techniques in the virtualized cloud data centers.