Efficient Data Collection and Communication of Industrial Internet of Things Solutions
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Journal Title
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Sähkötekniikan korkeakoulu |
Master's thesis
Authors
Date
2024-01-22
Department
Major/Subject
Communications Engineering
Mcode
ELEC3029
Degree programme
CCIS - Master’s Programme in Computer, Communication and Information Sciences (TS2013)
Language
en
Pages
46+1
Series
Abstract
The Internet of Things is gaining increasing attention from the industrial domain, where billions of industrial devices and sensors around the world are being connected to cloud-hosted services for monitoring, management, and optimization. While the increasing scale of the device fleet causes large data volumes that be injected into the network, communication efficiency becomes one of the major concerns. IoT product vendors seek to transfer data between devices and cloud services in a more efficient way thus reducing the transmission cost. Specifically, the requirement is to optimize the data communication while keeping the valuable information. This thesis takes IoT solutions that have direct cloud connectivity as a starting point and investigates approaches to reduce the data volume being transmitted in cloud communications. The process of data transmission over cloud connectivity indicates that the reduction in data usage can be achieved in two aspects, i.e., reducing the protocol overhead and optimizing the data payload. Therefore, this thesis investigates methods based on the two aspects. Firstly, this thesis investigates the possibility of reducing data usage by changing to a more lightweight protocol. Specifically, it focuses on two messaging protocols for transferring data between IoT devices and cloud services. MQTT is a publish/subscribe messaging protocol that is well known for its popularity in IoT applications. It is a lightweight protocol that is used to exchange data between IoT nodes. LwM2M is a promising protocol that enables IoT functionalities and it is claimed to consume less data than MQTT when used for exchanging data. This thesis studied their features and how to use them to periodically report data to cloud services, in order to do experimental comparison. Secondly, this thesis aims to enable data aggregation through short-range radio technologies. To achieve this, it proposes a solution that utilizes Bluetooth Low Energy to perform data aggregation locally before uploading to the cloud. This solution describes how to create local Bluetooth networks with a group of devices that are connected to the cloud directly. After Bluetooth networks are created, data generated by different devices can be sent to one aggregator node and then enhance the data efficiency. Furthermore, this thesis built the testbeds based on the two proposed methods and used them for experimental evaluation. The experiment results show that LwM2M consumes 9% less NB-IoT data than MQTT while sending the same total amount of payload data. The experiment results also show that the proposed Bluetooth-enabled data aggregation is feasible and can reduce the total payload by 18%.Description
Supervisor
Jäntti, RikuThesis advisor
Pang, ZhiboDobrijevic, Ognjen
Keywords
IoT, MQTT, LwM2M, Bluetooth, efficiency