Author : P.Dhivya 1
Date of Publication :23rd March 2018
Abstract: The process of extracting the required information and discovering the patterns from large data sets and transforming the data sets to the understandable patterns or structures is the concept of data mining. The required essential methods are applied for data pattern extraction. The most significant sectors such as marketing organizations, finance, health care systems, educational institutions, banking etc., use the concept of data mining for their specific purposes. Major concern of this strategy is the energy consumption by the Central Processing Unit (CPU) during the extraction process of the required information from the servers and the processing time utilized for the data retrieval is also considered[1]. In this paper, we propose the Online Scheduled-Energy Saving (OSES) algorithm which increases the efficiency of the CPU in servers by reducing the energy and time consumption for the query process in the web search engines. When the query is entered in web search engines, the query efficient predictors calculates the processing time and processing volume and this algorithm forwards the query to the respective query processing node. Thus, due to this task by the algorithm, energy consumption of the CPU in servers can be minimized[2]. Keywords- Data set, Energy consumption, DES (Dynamic Equal Sharing), Heuristic online algorithm, Optimal online algorithm, Query Efficiency Predictors (QEP)
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