Admissions Open
Admissions Open
A cloud computing provides the platform where numerous users and companies are connected for accessing different types of services such as software, applications, platforms and infrastructure. This technique utilizes various online web based processing structures. There is one major issue regarding the energy consumption and dissipation of cloud server during processing of their routine tasks. In this research work, our chief focus is to investigate and reduce energy consumption with enhanced scheduling approach based on multi-layer architecture. Here, we propose and implement a multi-layer scheduling approach and request the load balancer for managing multiple job queues along with effective resources utilization over cloud network. This is performed by the creation of client server database on the cloud where the servers are categorized as highest, intermediate and lowest priority server on the basis of the configurational parameters of processing speed, RAM and time; while the client requests are classified on the basis of urgency (processing need) and assigned the priorities likewise. A high priority job request is executed by higher configuration server while the lower tasks are accomplished by the lower configuration servers; that helps in energy saving..We evaluate our work with various performance parameters viz. energy, network (processor) utilization and response (processing) time to get optimal results. The evaluation work involves different scheduling and load balancing cloud computing algorithms viz Round Robin procedure, Minimum Completion Time (MCT) algorithm and Opportunistic Load Balancing (OLB) etc.; for efficiently utilizing the resources. The comparative study of the proposed algorithmic approach outperforms the earlier ones and yields better energy efficiency.