Abstract
Cloud computing provides useful services to users with extensive and scalable resources that virtualized over the internet. It defined as a collection of the communication and computing resources located in the data-center. The service based on on-demand is subject to QoS, the load balance, and certain other constraints with a direct effect on the user’s consumption of resources that are controlled by this cloud infrastructure. It is considered a popular method as it has several advantages that have been provided by a cloud infrastructure. The cloud scheduling algorithm’s primary goal was to bring down the time taken for completion (the cost of execution) of the task graph. The start time and the finish time for the task node influence the task graph completion completed to the time (the cost). The task node sort order an essential aspect that influences the start time and the finish time for every task node. In a hybrid cloud, efficient dense particle mass-based cloud scheduling is efficient because users need to maintain the security of the hybrid cloud. Different algorithms with different algorithms suggested by researchers in the cloud. This paper proposes particle swarm optimization (PSO)-based cloud optimal scheduling. Effective results obtained in an efficient fuzzy mass-based PSO cloud scheduling.
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Sirisati, R.S., Vishnu Vardhana Rao, M., Dilli Babu, S., Narayana, M.V. (2021). An Energy-Efficient PSO-Based Cloud Scheduling Strategy. In: Saini, H.S., Sayal, R., Govardhan, A., Buyya, R. (eds) Innovations in Computer Science and Engineering. Lecture Notes in Networks and Systems, vol 171. Springer, Singapore. https://doi.org/10.1007/978-981-33-4543-0_79
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