Scheduling Effective Cloud Updates in Streaming Data Warehouses using RECSS Algorithm

摘要

With the growth of data computing, energy saving is a major concern in data mining system. This is because large scale data centers have become common in computing industry, and there has been a significant increase in energy consumption at these data centers. Energy conservation brings several important benefits such as minimizing performance losses, achieving target battery lifetime, maximizing resource utilization, minimizing power consumption are some of the purposes of energy consumption. Thus energy consumption becomes a key issue to address in this proposed work. To overcome the above, a task scheduling algorithm is needed for minimizing energy consumption in cloud computing system. In this paper, RECSS, a rolling energy cuckoo scale scheduling approach is proposed for real-time task scheduling in virtualized clouds. RECSS minimizes the energy consumed by virtual machines for executing the tasks as well as increases the resource utilization without compromising the overall performance. Experimental results indicate that the proposed approach brings about a significant amount of energy conservation. The comparison is made with cuckoo search algorithm and EARH algorithm.