Context: Information Technology consumes up to 10 of the world's electricity generation, contributing to CO2 emissions and high energy costs. Data centers, particularly databases, use up to 23 of this energy. Therefore, building an energy-efficient (green) database engine could reduce energy consumption and CO2 emissions. Goal: To understand the factors driving databases' energy consumption and execution time throughout their evolution. Method: We conducted an empirical case study of energy consumption by two MySQL database engines, InnoDB and MyISAM, across 40 releases. We examined the relationships of four software metrics to energy consumption and execution time to determine which metrics reflect the greenness and performance of a database. Results: Our analysis shows that database engines' energy consumption and execution time increase as databases evolve. Moreover, the Lines of Code metric is correlated moderately to strongly with energy consumption and execution time in 88 of cases. Conclusions: Our findings provide insights to both practitioners and researchers. Database administrators may use them to select a fast, green release of the MySQL database engine. MySQL database-engine developers may use the software metric to assess products' greenness and performance. Researchers may use our findings to further develop new hypotheses or build models to predict greenness and performance of databases.
Some researchers have concentrated on the idea of benchmarking and examining power measurement. @cite_42 described a tool that approximates the energy consumption of software in order to help concerned consumers make knowledgeable decisions about the software they use. @cite_58 introduced a complete system power simulator that represents the CPU, the hierarchy of memory and a low-power disk subsystem and calculates the power performance of both side applications and the OS.
@cite_42 @cite_58
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The energy consumption of computers has become an important environmental issue. This paper describes the development of Green Tracker, a tool that estimates the energy consumption of software in order to help concerned users make informed decisions about the software they use. We present preliminary results gathered from this system's initial usage. Ultimately the information gathered from this tool will be used to raise awareness and help make the energy consumption of software a more central concern among software developers. Power dissipation has become one of the most critical factors for the continued development of both high-end and low-end computer systems. We present a complete system power simulator, called SoftWatt, that models the CPU, memory hierarchy, and a low-power disk subsystem and quantifies the power behavior of both the application and operating system. This tool, built on top of the SimOS infrastructure, uses validated analytical energy models to identify the power hotspots in the system components, capture relative contributions of the user and kernel code to the system power profile, identify the power-hungry operating system services and characterize the variance in kernel power profile with respect to workload. Our results using Spec JVM98 benchmark suite emphasize the importance of complete system simulation to understand the power impact of architecture and operating system on application execution.