Authors : Neha Tyagi, Ajay Rana and Vineet Kansal
Abstract: Today, there is trend for distributed cloud computing to be followed as new worldwide pattern of processing. It is an advanced style of utilizing the power of internet to offer assets remotely. However, distributed cloud computing has many difficulties, for example, poor asset usage which has a deep effect on the execution of distributed computing. Such issues emerged because of the tremendous quantity of data. Therefore, the requirement intended for productive and capable distributed cloud computing load harmonizing calculations is a standout amongst the most imperative issues around to enhance the execution of cloud processing. Many investigators proposed numerous load balancing and process programming algorithms in the calculation of cloud but there still remains incompetency within the hardware functioning and lack of load balancing. Thus, this study endorses a set of rules for load balancing to enhance the overall performance and effectiveness in diverse cloud computing environment. We advocate a fusion set of rules based on priority and batch rules, taking advantages of weighted optimization algorithm and equally spread current execution algorithms. The algorithm reflects the current resource records and the capability issue of central processing unit to acquire the targets. The fused algorithm has been evaluated and are compared with different algorithms using Cloud Analyst Simulator. The results demonstrated progress in migration time, reaction time and scalability, availability and reliability of resources with energy-consumption and throughput via. considering the modern-day aid records and the central processing unit potential factor in comparison with different algorithms.
Neha Tyagi, Ajay Rana and Vineet Kansal, 2019. Weighted Optimization Load Balancing Algorithm in Virtualization. Journal of Engineering and Applied Sciences, 14: 8386-8402.