Abstract
The Internet of Things (IoT) is revolutionizing technology in a wide variety of areas, from smart healthcare to smart transportation. Due to the increasing trend in the number of IoT devices and their different levels of energy requirements, one of the significant concerns in IoT implementations is powering up the IoT devices with conventional limited lifetime batteries. One efficient solution to prolong the lifespan of these implementations is to integrate energy harvesting technologies into IoT systems. However, due to the characteristics of the energy harvesting technologies and the different energy requirements of the IoT systems, this integration is a challenging issue. Since Medium Access Control (MAC) layer operations are the most energy-consuming processes in wireless communications, they have undergone different modifications and enhancements in the literature to address this issue. Despite the essential role of the MAC layer to efficiently optimize the energy consumption in IoT systems, there is a gap in the literature to systematically understand the possible MAC layer improvements allowing energy harvesting integration. In this survey paper, we provide a unified framework for different wireless technologies to measure their energy consumption from a MAC operation-based perspective, returning the essential information to select the suitable energy harvesters for different communication technologies within IoT systems. Our analyses show that only 23% of the presented protocols in the literature fulfill Energy Neutral Operation (ENO) condition. Moreover, 48% of them are based on the hybrid approaches, which shows its capability to be adapted to energy harvesting. We expect this survey paper to lead researchers in academia and industry to understand the current state-of-the-art of energy harvesting MAC protocols for IoT and improve the early adoption of these protocols in IoT systems.
Highlights
The Internet of Things (IoT) enables the connection and data transferring over the Internet for a massive number of physical objects, which are equipped with distinct hardware and software to enhance a wide range of applications and services [1]
ALOHA + Time Division Multiple Access (TDMA): This combination is divided into three mechanisms, which are known as Frame ALOHA (FA), Frame Slotted ALOHA (FSA) [40], and Time Slotted Channel Hopping (TSCH) [41]
We provided a thorough review of the Medium Access Control (MAC) layer operations and different MAC optimization techniques, which some of them are employed in the current IoT wireless communication technologies
Summary
The Internet of Things (IoT) enables the connection and data transferring over the Internet for a massive number of physical objects, which are equipped with distinct hardware and software to enhance a wide range of applications and services [1]. The analysis from “The Shift Project” [4] conveys that the increasing trend of IoT connected devices leads to a Computational Annual Growth Rate of 4.5% in the expected energy consumption of IoT deployments (from 2312 TWh in 2015 to 4350 TWh in 2025) According to these predictions, in the near future, powering up IoT devices with conventional batteries with a limited lifetime, which requires frequent replacement, is a concerning issue and may cause system failure [5]. The limited lifetime of the conventional batteries, which increases the maintenance cost, number of replacements, and negative impact on the environment, in a system with a few devices do not raise an issue, whereas, in networks with millions or even billions of devices, it becomes a significant issue Since these battery limitations threaten the rapid development of the IoT paradigm, academia and industry have become interested in extending the lifetime of IoT devices while maintaining optimal performance. Fulfilling this condition under specific considerations (e.g., small size of the energy harvester) and the whole system’s requirements remains a gap in the literature
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