Abstract

Abstract

Abstract
During the last few years, we have been witnessing a significant increase in research about the development and production of hardware and software components with low levels of energy consumption. Today, energy consumption is one of the most critical issues in the area of information technologies and communication. One of the fractions in which this concern is most evident is in the management of database systems, with particular emphasis on those commonly designated as data centers. On these systems daily run a large amount of data querying processes, monitored and controlled by high sophisticated database management systems, which are responsible to establish efficient processing plans to support them. Using the information provided by a querying execution plan, especially the one related to the operators they used to perform database operations, we designed and developed an alternative method to define energy consumption plans for database queries. In this paper we present how such method works on the estimation of the energy consumption of each database operator integrated in the execution plan of a query at compile time. With it, we build up its corresponding energy consumption plan for executing the query, taking into consideration as well the characteristics of the computational platforms used for that.

Abstract
This paper showcases MDSheet, a framework aimed at improving the engineering of spreadsheets. This framework is model-driven, and has been fully integrated under a spreadsheet system. Also, its practical interest has been demonstrated by several empirical studies.

Abstract

Abstract