A novel weight-assignment load balancing algorithm for cloud applications

Load balancing dynamically optimizes cloud resources and performance, and enhances the performance of applications deployed on cloud. We have chosen to investigate the class of cloud deployed web-based threetier business applications. There is a problem with load balancing for this class of applications when they suffer from overload due to sudden flash crowds and resource failures. We propose a novel weight assignment load balancing algorithm to address this problem. Our approach utilises five carefully selected server metrics to efficiently distribute load among virtual machines. First, we validated our novel algorithm by comparing it with a baseline load-balancing algorithm and round-robin algorithm. Then, we experimentally evaluated our solution, by varying the number of user requests and carefully measuring response times and throughput. The experiments were performed on a private cloud environment testbed running OpenStack. Our experimental results show that our approach improves the response time of user requests by 5.66% compared to the baseline algorithm and 15.15% compared to round-robin algorithm in flash crowd scenario. In addition, while handling between 110% to 190% overload, our approach improved response times in all scenarios. Consequently, our novel algorithm outperforms the baseline and round-robin algorithms in overload conditions