Book Description

With the growing popularity of cloud computing today, its model will one day serve as the fifth utility service outside electricity, telephone, water and gas. Visualizing how this utility model will revolutionize the way people use computing resources requires that we take the big challenge of performance unpredictability associated with load imbalance, computing resource distribution inefficiency and minimum resource consumption into consideration. There is a need for developing a better model that will not only reduce cost but also make enterprise as per user's satisfaction. Improving resource utility and performance of distributed system in a way that willl yield better response time, processing time and efficient virtual machine monitoring is therefore, the concern of this research work. Throttled load balancing algorithm was analyzed and its deficiencies serve as a basis for improvement in the proposed system. The proposed system rearranges Virtual Machines (VMs) according to their threshold value and 80% threshold value for each machine serving as the maximum utilization range for cloudlets allocation. The proposed system then spreads load across all VMs until each machine attains 80% of its threshold value. If this level is attained and there are still cloudlets at the global queue, the 20% un-utilized threshold value can then be used. The system also monitors VM efficiency and stops allocation to any VM that does not perform to its optimum level. An extensive simulation was carried out to evaluate the proposed system using Cloud Analyst simulator in order to compare the existing system and the proposed system. The results show that the proposed system yields a better response time and lower turnaround time and provides efficient VM monitoring than the existing throttled load balancer.