A study of over-the-air (OTA) update systems for CPS and IoT operating systems

Villegas, Mónica M.; Orellana, Cristian; Astudillo, Hernán

doi:10.1145/3344948.3344972

Cited by 11 publications

(5 citation statements)

References 13 publications

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“…The operational flow of OTA-TinyML is shown in Figure 1, comprising two parts. The first part circled (1), explained in Section IV-A, contains a method, that upon demand, fetches ML model files from the cloud server on the edge devices. The second part circled (2), explained in Section IV-B, contains a method to enable storage of fetched files in internal memory or external file systems, then the loading and model execution.…”

Section: Ota-tinyml Designmentioning

confidence: 99%

“…OTA updates are one of the famous techniques to remotely, efficiently, and reliably update devices in the field. It not only improves safety and compliance but also reduces operational & maintenance costs and offers the potential for enhanced revenue streams, as the OEMs can offer add-on services without having expensive service technicians perform the updates in person [1]. However, these benefits must be balanced by the risks.…”

Section: Introductionmentioning

confidence: 99%

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OTA-TinyML: Over the Air Deployment of TinyML Models and Execution on IoT Devices

Sudharsan

Breslin

Tahir

et al. 2022

IEEE Internet Comput.

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IoT devices and networks are distributed by nature and very often IoT devices are deployed at remote locations with limited physical access. To ensure the latest firmware, security patches & configuration settings in remote IoT devices, Original Equipment Manufacturers (OEMs) send device-specific, Over-The-Air (OTA) packages in a scalable way. The OTA updates are a great facility to update and control distributed IoT devices remotely using cloud services. However, so far, the major focus of OTA is generally limited to remote patching or updates to remove any software bugs and security flaws. Recently, Edge Computing is getting popular where IoT devices are equipped with ML data models to perform edge analytics at the device level. However, existing methods to deploy ML models on IoT devices still require physical access to the devices. OTA techniques for ML models deployments bring unique challenges such as security & privacy issues due to remote access, limited resources at the device level to fit in ML models, and diverse hardware and software specifications of IoT devices. This paper presents a novel OTA technique to remotely deploy tiny ML models over IoT devices and perform tasks such as ML model updates, firmware re-flashing, re-configuration, or re-purposing. We discuss relevant challenges for OTA ML deployment over IoT both at the scientific and engineering level. We propose an IoT hardware-friendly approach named OTATinyML to enable resource-constrained IoT devices to perform end-to-end fetching, storage, and execution of many TinyML models. OTA-TinyML loads the C source file of ML models from a web server into the embedded IoT devices via HTTPS. It is compatible with a range of IoT development boards and ML models from text, speech & image domains. OTA-TinyML is tested by performing remote fetching of 6 types of ML models, storing them on 4 types of memory units, then loading and executing on 7 popular MCU boards.

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Section: Ota-tinyml Designmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

OTA-TinyML: Over the Air Deployment of TinyML Models and Execution on IoT Devices

Sudharsan

Breslin

Tahir

et al. 2022

IEEE Internet Comput.

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“…The AWS IoT core consists of five services that maintain the needs of all IoT devices, connect to AWS cloud, manage devices, update over-the-air (OTA) [39], and secure the IoT devices. It uses the TLS communication protocol to encrypt all communication [40].…”

Section: Aws Iot Core Framementioning

confidence: 99%

Design of Scalable IoT Architecture Based on AWS for Smart Livestock

Dineva

Atanasova

2021

Animals

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In the ecological future of the planet, intelligent agriculture relies on CPS and IoT to free up human resources and increase production efficiency. Due to the growing number of connected IoT devices, the maximum scalability capacity, and available computing power of the existing architectural frameworks will be reached. This necessitates finding a solution that meets the continuously growing demands in smart farming. Cloud-based IoT solutions are achieving increasingly high popularity. The aim of this study was to design a scalable cloud-based architecture for a smart livestock monitoring system following Agile methodology and featuring environmental monitoring, health, growth, behaviour, reproduction, emotional state, and stress levels of animals. The AWS services used, and their specific tasks related to the proposed architecture are explained in detail. A stress test was performed to prove the data ingesting and processing capability of the proposed architecture. Experimental results proved that the proposed architecture using AWS automated scaling mechanisms and IoT devices are fully capable of processing the growing amount of data, which in turn allow for meeting the required needs of the constantly expanding number of CPS systems.

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“…MOAP, a Multihop Over-the-Air Programming [50] mechanism focused on being memory and energy efficient, was frequently used for update dissemination as well. In terms of newer embedded operating systems, RIOT OS [51] and ARM mbed [52] are often cited in surveys [21,23,41,53,54] and used by solutions [11,55].…”

Section: Related Workmentioning

confidence: 99%

“…For Jaouhari and Bouvet [23], the comparison is focused on security features and hardware support, which is the focus of their work. A comparison of both open source and private projects and their support for OTA updates is made by Villegas et al [54], the authors found that many solutions did not specify anything related to OTA in their documentation, and suggest separating the logical structure of the updates from the technologies used, this way the structure can become a standard, allowing companies to build on the implementation. One such attempt at standardization was made by IETF and will be explained in more detail in the next section.…”

Section: Node Addressingmentioning

confidence: 99%

Design and evaluation of a method for Over-the-Air firmware updates for IoT devices

Júlia Berriel de Sousa

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ResumoA área de Internet das Coisas (IoT, em inglês) vem ganhando atenção nos últimos anos, e apesar da grande quantidade de investimentos, ainda há muitos desafios a serem superados em todas as partes da arquitetura. Um desafio é desenvolver uma aplicação duradoura. Com relação aos dispositivos, um dos fatores que mais contribui para a longevidade é a habilidade de atualizar o firmware dos dispositivos. Em termos práticos, atualização de firmware ou software over-the-air (OTA) é uma parte crucial da arquitetura de IoT, junto com a capacidade de gerenciá-los remotamente.Essa dissertação explica a arquitetura de IoT através de uma visualização em camadas e como atualizações OTA são parte dela. Como uma solução para esse problema, um método para atualização de firmware OTA, e a sua implementação é apresentado. Esse método é baseado no padrão recentemente proposto pela Internet Engineering Task Force (IETF), na forma do RFC 9019. A solução proposta é avaliada através de dois cenários de teste: um com 20 dispositivos IoT restritos conectados a uma plataforma IoT na nuvem e de código aberto, através de uma rede WiFi, o outro cenário consiste em um conjunto de 75 dispositivos implantados espalhados por uma grande área geográfica como parte de uma aplicação real. Resultados mostram que a solução apresentada é adequada para dispositivos restritos a tem pouco impacto no tráfego de rede.

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A study of over-the-air (OTA) update systems for CPS and IoT operating systems

Cited by 11 publications

References 13 publications

OTA-TinyML: Over the Air Deployment of TinyML Models and Execution on IoT Devices

OTA-TinyML: Over the Air Deployment of TinyML Models and Execution on IoT Devices

Design of Scalable IoT Architecture Based on AWS for Smart Livestock

Design and evaluation of a method for Over-the-Air firmware updates for IoT devices

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