Most modern information technology devices use the Internet for creating, reading, updating, and deleting shared data through remote inter-process communication (IPC). To evaluate the energy consumption of IPC technologies and the corresponding run-time performance implications, we performed an empirical study on popular IPC systems implemented in Go, Java, JavaScript, Python, PHP, Ruby, and C#. We performed our experiments on computer platforms equipped with Intel and ARM processors. We observed that JavaScript and Go implementations of gRPCoffer the lowest energy consumption and execution time. Furthermore, by analysing their system call traces, we found that inefficient use of system calls can contribute to increased energy consumption and poor execution time.

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Motivation: In modern IT systems, the increasing demand for computational power is tightly coupled with ever higher energy consumption. Traditionally, energy efficiency research has focused on reducing energy consumption at the hardware level. Nevertheless, the software itself provides numerous opportunities for improving energy efficiency. Goal: Given that energy efficiency for IT systems is a rising concern, we investigate existing work in the area of energy-aware software development and identify open research challenges. Our goal is to reveal limitations, features, and tradeoffs regarding energy-performance for software development and provide insights on existing approaches, tools, and techniques for energy-efficient programming. Method: We analyze and categorize research work mostly extracted from top-tier conferences and journals concerning energy efficiency across the software development lifecycle phases. Results: Our analysis shows that related work in this area has focused mainly on the implementation and verification phases of the software development lifecycle. Existing work shows that the use of parallel and approximate programming, source code analyzers, efficient data structures, coding practices, and specific programming languages can significantly increase energy efficiency. Moreover, the utilization of energy monitoring tools and benchmarks can provide insights for the software practitioners and raise energy-awareness during the development phase.

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Motivation: The energy efficiency of it-related products, from the software perspective, has gained vast popularity the recent years and paved a new emerging research field. However, there is limited number of research works regarding the energy consumption of relatively small programming tasks. This knowledge is critical to be known especially in cases where millions of small tasks are running in parallel on multiple devices all around the globe. Goal: In this preliminary study, we aim to identify energy implications of small, independent tasks developed in different programming languages; compiled, semi-compiled, and interpreted ones. Method: To achieve our purpose, we collected, refined, compared, and analyzed a number of implemented tasks from Rosetta Code, that is a publicly available Repository for programming chrestomathy. Results: Our analysis shows that among compiled programming languages such as C, C++, Java, and Go offer the highest energy efficiency for all of our tested tasks compared to C#, vb.net, and Rust. Regarding interpreted programming languages php, Ruby, and JavaScript exhibit the most energy savings compared to Swift, R, Perl, and Python.@en