The IoT energy challenge: A software perspective

Abstract

The Internet of Things (IoT) sparks a whole new world of embedded applications. Most of these applications are based on deeply embedded systems that have to operate on limited or unreliable sources of energy, such as batteries or energy harvesters. Meeting the energy requirements for such applications is a hard challenge, which threatens the future growth of the IoT. Software has the ultimate control over hardware. Therefore, its role is significant in optimizing the energy consumption of a system. Currently, programmers have no feedback on how their software affects the energy consumption of a system. Such feedback can be enabled by energy transparency, a concept that makes a program's energy consumption visible, from hardware to software. This paper discusses the need for energy transparency in software development and emphasizes on how such transparency can be realized to help tackling the IoT energy challenge.

9 pages, 1 figure

References in corpus (4)

• Exploring performance and power properties of modern multicore chips via simple machine models
• Energy Transparency for Deeply Embedded Programs
• Inferring Parametric Energy Consumption Functions at Different Software Levels: ISA vs. LLVM IR
• On the limitations of analysing worst-case dynamic energy of processing

Cited by in corpus (8)

• TDMA in Adaptive Resonant Beam Charging for IoT Devices
• When parallel speedups hit the memory wall
• Model-Based Design of Energy-Efficient Applications for IoT Systems
• Lost in translation: Exposing hidden compiler optimization opportunities
• Evaluating the effects of reducing voltage margins for energy-efficient operation of MPSoCs
• A Comprehensive and Accurate Energy Model for Arm's Cortex-M0 Processor
• Low-Latency Massive Access with Multicast Wake Up Radio
• Wireless Energy Transmission Channel Modeling in Resonant Beam Charging for IoT Devices