Virtualized Clouds and Energy Aware Scheduling Using EARH

Cloud applications are deployed in remote data centers (DCs) where high capacity servers and storage systems are located. A fast growth of demand for cloud based services results into establishment of enormous data centers consuming high amount of electrical power. Energy efficient model is required for complete infrastructure to reduce functional costs while maintaining vital Quality of Service (QoS). Furthermore, most algorithms schedule tasks according to their average-case execution times and do not consider task execution times with probability distributions in the real-world. In realizing this, we study the problem of scheduling a bag-of-tasks application, made of a collection of independent stochastic tasks with normal distributions of task execution times, on platform with deadline and energy consumption budget constraints Energy optimization can be achieved by combining resources as per the current utilization, efficient virtual network topologies and status of computing hardware and nodes. So we implement the EARH system to implement the rolling-horizon optimization to efficiently guarantee the schedulability of real-time tasks and at the same time striving to save energy by dynamic VMs consolidation.. Keywords— virtualized cloud, real-time, energy-aware, scheduling, rolling-horizon, elasticity