Understanding the IoT connectivity landscape: a contemporary M2M radio technology roadmap

By Sergey D. Andreev, O. Galinina, Alexander Pyattaev, M. Gerasimenko, T. Tirronen, J. Torsner, J. Sachs, Mischa Dohler, Yevgeni Koucheryavy. IEEE Communications Magazine, 2015

294 citations recorded by the source corpus.

This article addresses the market-changing phenomenon of the Internet of Things (IoT), which relies on the underlying paradigm of machine-to-machine (M2M) communications to integrate a plethora of various sensors, actuators, and smart meters across a wide spectrum of businesses. Today the M2M landscape features an extreme diversity of available connectivity solutions which, due to the enormous economic promise of the IoT, need to be harmonized across multiple industries. To this end, we comprehensively review the most prominent existing and novel M2M radio technologies, as well as share our first-hand real-world deployment experiences, with the goal to provide a unified insight into enabling M2M architectures, unique technology features, expected performance, and related standardization developments. We pay particular attention to the cellular M2M sector employing 3GPP LTE technology. This work is a systematic recollection of our many recent research, industrial, entrepreneurial, and standardization efforts within the contemporary M2M ecosystem.

Subfields: Biomedical Engineering, Computer Networks and Communications, Electrical and Electronic Engineering

View Paper: https://www.semanticscholar.org/paper/8c9f3dcd83b2d2365f3e8bbb0e9cc9f1f549f964

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Biomedical Engineering

In Computer Networks and Communications

In Electrical and Electronic Engineering

Citations in the corpus

Deep Reinforcement Learning for Offloading and Resource Allocation in Vehicle Edge Computing and Networks (2019, background): “T HE EVOLVING Internet of Things (IoT) system requires highly scalable infrastructure to adaptively provide proper services for different applications in distinct domains [1]–[3].”
5G-Enabled Tactile Internet (2016, background): “recent work has concentrated to incorporating very heterogeneous trusted/untrusted real-time/non-real-time traffic into 3GPP mobile systems [68]–[73].”
Internet of Things in the 5G Era: Enablers, Architecture, and Business Models (2016, background): “in enabling a global IoT in the upcoming future [15].”
Energy-Efficient Wireless Sensor Networks for Precision Agriculture: A Review (2017, background): “Cellular technologies are grown and developed to play a crucial role in the IoT realm [9].”
On the coverage of LPWANs: range evaluation and channel attenuation model for LoRa technology (2015, unknown): “, thermostat control and security systems) [4-5].”
A Comprehensive Survey on Internet of Things (IoT) Toward 5G Wireless Systems (2020, methodology): “Control and user signals are routed through nodes and consider both licensed and unlicensed spectrum bands to bring the diverse in the heterogeneous networks [47].”
A Survey on 5G Networks for the Internet of Things: Communication Technologies and Challenges (2018, background): “To improve the network performance and throughput while considering dense and congested areas [81], [82] enhanced”
Deploying Fog Computing in Industrial Internet of Things and Industry 4.0 (2018, background): “Other than smart parking proposed by Andreev [17], in which vehicles get to know about vacant parking slots in real time, parking can be enhanced in many ways.”
Low Power Wide Area Networks: An Overview (2016, background): “Due to this reason, increasing number of recently published studies [59], [60] and IETF draft documents [61], [62] do not enlist IEEE 802.”