Load Balancing and Predictive Analysis Model Implementation in Public Cloud

Abstract

The data centre is fundamental to cloud computing. Data centers are currently being strained by the rising demand for cloud computing services. Cloud computing practices are very important in terms of device performance and schedule that can make it easier for users to distribute the workload among network resources. Any data-center services can eventually become overloaded/ under loaded, resulting in increased energy usage, as well as decreased functionality and resource waste.As a result, this paper uses a contextual with multiple metrics to adopt optimization algorithms that are implemented by load balancing. Load balancing with system integration strengthens resource utilization but can increase Performance of System (Latency) metrics. This research aims to incorporate a new system for congestion control and server expansion including migration latency, device threshold, QoS, and energy consumption.