OPTIMIZING PEAK LOAD MANAGEMENT IN DATA CENTERS THROUGH THE WATER SHOWER MODEL APPROACH FOR ENHANCED RESOURCE UTILIZATION AND CARBON EMISSION REDUCTION

Abstract

Data centers are important for addressing increasing demand for digital services, yet peak user
requests sometimes causes server overload, slow response time, high energy use and high
carbon emissions. Water Shower Model (WSM) is a novel data center peak load control system
that optimizes resource efficiency and reduces carbon emissions. Research suddenly highlights
the challenges of managing user demands, which often causes server overload, slow response
time and high energy consumption. The purpose of this project is to appropriately allocate
server workloads, reducing the carbon footprint. Qualitative Research is complemented by
simulation experiments using the results of the Vellore Institute of Technology using the
Publication System and Learning Management System Log Records. WSM framework user
request types using a balanced exemplary dynamic voltage carbon scaling (BET-Devcs) and
multi-kui scheduling using a finished queue monitor to allocate containers and virtual machines
based on ROR or RWR. WSM performs better than an ant colony and honey bees by equally
assigning the workload in all servers, preventing overloads, reducing the reaction time and
reducing carbon emissions. Compared to the baseline model, the user's bases had rapid average
response time and low power consumption and carbon counterparts. Parallel distribution cloud
infrastructure improves reliability and stability. The management of data center workload with
WSM is scalable and environmentally friendly. It improves user satisfaction, reduces
operational costs, and environmentally promotes durable IT practices, making it a viable pattern
for future cloud infrastructure.