Research Area:  Cloud Computing
Cloud computing technology is a prominent technique among available techniques for deploying and allocating computing resources across applications. Due to digitalization the size of data is now rapidly increasing and necessitating the establishment of additional computing facilities and capabilities. To handle enormous, volumes of relevant data most cloud providers are using a fairly high commuting technology that utilizes a massive amount of energy to give the finest capabilities and activities to attract customers, this is also possible to maintain system resources. This paper describes the EEPSA method, which is a new energy efficiency priority scheduling system for cloud computing that can help minimize overall energy utilization. The proposed approach mainly emphasizes the pre-emptive aspect and calculates the energy usage for all the workloads scheduling on virtual machines. To reduce the particular energy usage all the requests have been routed to processing servers, not only based on an optimum fit value but also system accessibility. Our proposed EEPSA technique focuses mostly on the proactive elements and estimates the energy consumption amongst all operations scheduled on all of the VMs (virtual machines). An experimental analysis compares the effectiveness of the proposed EEPSA approach to existing methods in based on energy usage, number of tasks migrated, as well as processing time.
Author(s) Name:  Sarita Simaiya; Vinay Gautam; Umesh Kumar Lilhore; Atul Garg; Pinaki Ghosh; Naresh Kumar Trivedi; Abhineet Anand
Conferrence name:  2nd International Conference on Smart Electronics and Communication (ICOSEC)
Publisher name:  IEEE
Volume Information:  Volume
Paper Link:   https://ieeexplore.ieee.org/abstract/document/9591967