Investigating Low Energy Wireless Networks for the Internet of Things

Branden Ghena

EECS Department
University of California, Berkeley
Technical Report No. UCB/EECS-2020-209
December 17, 2020

http://www2.eecs.berkeley.edu/Pubs/TechRpts/2020/EECS-2020-209.pdf

The Internet of Things (IoT) encompasses a broad array of technologies that connect the physical world with large-scale data processing and storage. Today, we can build ultra-low power devices that last for decades on ambient energy and we can deploy highly scalable internet services to process streams of IoT data. The dominant challenge of IoT lies in connecting these two domains. To meet this challenge, many new networks have been developed with low-energy, low-throughput, and predominantly uplink use cases in mind.

In this work, we explore the capabilities and limitations of several recent IoT-focused networks. While these novel networks are not yet deployed at scale, modeling aspects of them enables us to predict the success or failure of particular applications and explore the ramifications of potential protocol improvements.

In the local-area domain, Bluetooth Low Energy (BLE) has arisen as an ubiquitous method of connecting deployed devices directly to users' smartphones. One communication mechanism that BLE provides is the advertisement a simple, periodic, broadcast message intended for device discovery. With advertisements, we can create a single-hop, star-topology network in full compliance with the BLE specification that allows any number of devices to send data to any number of gateways. By modeling advertisement transmissions, we can accurately predict congestion in advertisement networks, which enables an a priori understanding of performance and an in-situ adaptation mechanism to meet reliability expectations.

In the wide-area domain, multiple low-power, wide-area networks (LPWANs) have arisen to enable city-scale deployments. Their ability to transmit at ranges over a kilometer while drawing only a few hundred milliwatts could enable exciting new applications. To understand LPWAN capabilities, we propose a new metric, bit flux, which describes communication in terms of throughput over a coverage area. By using bit flux to model the performance of networks and the needs of applications, we demonstrate problems with the existing designs of several LPWANs that make them unsuitable for many real-world deployments.

In both domains, we explore the strengths and weaknesses of communication technologies and their potential to serve real-world applications. The potential for these networks to promote a new generation of easy-to-deploy sensors is high. However, through the application of communication models, we demonstrate both potential use cases and also very real concerns that may limit them. By uncovering concerns that future deployments will face, we hope to guide improvements to these protocols that will improve their use and support the growth of the Internet of Things.

Advisor: Prabal Dutta


BibTeX citation:

@phdthesis{Ghena:EECS-2020-209,
    Author = {Ghena, Branden},
    Title = {Investigating Low Energy Wireless Networks for the Internet of Things},
    School = {EECS Department, University of California, Berkeley},
    Year = {2020},
    Month = {Dec},
    URL = {http://www2.eecs.berkeley.edu/Pubs/TechRpts/2020/EECS-2020-209.html},
    Number = {UCB/EECS-2020-209},
    Abstract = {The Internet of Things (IoT) encompasses a broad array of technologies that connect the physical world with large-scale data processing and storage. Today, we can build ultra-low power devices that last for decades on ambient energy and we can deploy highly scalable internet services to process streams of IoT data. The dominant challenge of IoT lies in connecting these two domains. To meet this challenge, many new networks have been developed with low-energy, low-throughput, and predominantly uplink use cases in mind.

In this work, we explore the capabilities and limitations of several recent IoT-focused networks. While these novel networks are not yet deployed at scale, modeling aspects of them enables us to predict the success or failure of particular applications and explore the ramifications of potential protocol improvements.

In the local-area domain, Bluetooth Low Energy (BLE) has arisen as an ubiquitous method of connecting deployed devices directly to users' smartphones. One communication mechanism that BLE provides is the advertisement a simple, periodic, broadcast message intended for device discovery. With advertisements, we can create a single-hop, star-topology network in full compliance with the BLE specification that allows any number of devices to send data to any number of gateways. By modeling advertisement transmissions, we can accurately predict congestion in advertisement networks, which enables an a priori understanding of performance and an in-situ adaptation mechanism to meet reliability expectations.

In the wide-area domain, multiple low-power, wide-area networks (LPWANs) have arisen to enable city-scale deployments. Their ability to transmit at ranges over a kilometer while drawing only a few hundred milliwatts could enable exciting new applications. To understand LPWAN capabilities, we propose a new metric, bit flux, which describes communication in terms of throughput over a coverage area. By using bit flux to model the performance of networks and the needs of applications, we demonstrate problems with the existing designs of several LPWANs that make them unsuitable for many real-world deployments.

In both domains, we explore the strengths and weaknesses of communication technologies and their potential to serve real-world applications. The potential for these networks to promote a new generation of easy-to-deploy sensors is high. However, through the application of communication models, we demonstrate both potential use cases and also very real concerns that may limit them. By uncovering concerns that future deployments will face, we hope to guide improvements to these protocols that will improve their use and support the growth of the Internet of Things.}
}

EndNote citation:

%0 Thesis
%A Ghena, Branden
%T Investigating Low Energy Wireless Networks for the Internet of Things
%I EECS Department, University of California, Berkeley
%D 2020
%8 December 17
%@ UCB/EECS-2020-209
%U http://www2.eecs.berkeley.edu/Pubs/TechRpts/2020/EECS-2020-209.html
%F Ghena:EECS-2020-209