IoTRepair: Systematically Addressing Device Faults in Commodity IoT

Norris, Michael; Çelik, Berkay; Venkatesh, P.; Zhao, Shulin; McDaniel, Patrick; Sivasubramaniam, Anand; Tan, Gang

doi:10.1109/iotdi49375.2020.00021

Cited by 10 publications

(4 citation statements)

References 16 publications

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“…ECCO [27] is an orchestration framework that enables edge-cloud collaborative computing for road context assessment to detect and react efficiently to road hazards. IoTREPAIR [28] is a fault-handling system for IoT that integrates with fault identification modules to track faulty devices, provides a library of fault-handling functions for effectively handling different fault types and provides a fault handler on top of the library for autonomous IoT fault handling, with deployed devices, user preferences, and developer configuration as input. LinkLab [29] is a scalable IoT testbed for heterogeneous devices that not only supports running experiments but also supports remote development via a web-based IDE and remote compiling.…”

Section: Related Workmentioning

confidence: 99%

BULWARK: A Framework to Store IoT Data in User Accounts

Reed

Tosun

2022

IEEE Access

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The explosive growth of the Internet of Things (IoT) devices raises serious concerns for a user's privacy and security because the existing software framework on these devices often support various default features and generate large data sets. Moreover, many IoT devices incorporate a manufacturer-owned cloud-based back-end support to process and store the generated data while simultaneously sharing with third parties. Clearly, in such an industry-driven environment with the desire to use the IoT data as a revenue stream, it is a challenge for users to control IoT data. Device manufacturers utilize an opaque software design where user data is generated and stored with little transparency. Manufacturers use EULAs as a legal construct to protect a manufacturer's legal standing and to explain a device's behavior, however this explanation is vague and lacks the necessary details for a user to determine a device's acceptable use and it has become increasingly difficult for users to secure and maintain their data. Fortunately, as the privacy minded user base of IoT devices grows, the manufacturers will be forced to implement a new framework that can enable users to have more control on the creation of their IoT data, and to store/disseminate such data in a secure and private manner. In this paper, we address this lack of transparency from manufacturers and address the issues of privacy and security by proposing a new framework called Bulwark, for manufacturer use on IoT devices and mobile applications. Proposed framework enables the user to generate and manage a set of data controlling rules, and store the result in their personal cloud account, while providing a dashboard data reporting tool enabling data transparency and supporting good user choices. The user's ability to access, disseminate and secure IoT generated data, is now available within our proposed framework. Using reverse engineering, simulation and implementation of open source solutions, we demonstrate support for a set of common devices. Each device executed the framework, while communicating with a mobile application and cloud services. Rules were generated for each message and telemetry was returned to the mobile application for dashboard rendering. We stored generated data in the cloud using our own account, while maintaining the free tier for each of the cloud services. Network usage increased between 4% and 9% while storage size grew between 0% and 2% larger, as compared to using the device without the framework. Our framework demonstrates support for a multitude of devices, by either open source or support for similar feature sets. This framework is easy to integrate and we anticipate wide spread adoption.

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Section: Related Workmentioning

confidence: 99%

BULWARK: A Framework to Store IoT Data in User Accounts

Reed

Tosun

2022

IEEE Access

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“…For this reason, there is already some research done for fault detection in IoT systems. IoTRepair [ 34 ] is a fault diagnosis system for IoT systems. Its diagnosis is facilitated by developer configuration files along with user preferences and works by monitoring the states of each sensor and how they correlate with the states of their neighbours.…”

Section: Related Workmentioning

confidence: 99%

IoTCrawler: Challenges and Solutions for Searching the Internet of Things

Iggena¹,

Ilyas²,

Fischer³

et al. 2021

Sensors

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Due to the rapid development of the Internet of Things (IoT) and consequently, the availability of more and more IoT data sources, mechanisms for searching and integrating IoT data sources become essential to leverage all relevant data for improving processes and services. This paper presents the IoT search framework IoTCrawler. The IoTCrawler framework is not only another IoT framework, it is a system of systems which connects existing solutions to offer interoperability and to overcome data fragmentation. In addition to its domain-independent design, IoTCrawler features a layered approach, offering solutions for crawling, indexing and searching IoT data sources, while ensuring privacy and security, adaptivity and reliability. The concept is proven by addressing a list of requirements defined for searching the IoT and an extensive evaluation. In addition, real world use cases showcase the applicability of the framework and provide examples of how it can be instantiated for new scenarios.

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“…The faults that are generally induced in the IoT system include Cascading faults [14,15], Pattern faults [16], and device-to-device communication faults [17]. Various faults occurring within the devices have been reviewed by Norris et al, [18,19].…”

Section: Introductionmentioning

confidence: 99%

Implementing Dual Base Stations within an IoT Network for Sustaining the Fault Tolerance of an IoT Network through an Efficient Path Finding Algorithm

Sastry

Budaraju

2023

Sensors

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The IoT networks for implementing mission-critical applications need a layer to effect remote communication between the cluster heads and the microcontrollers. Remote communication is affected through base stations using cellular technologies. Using a single base station in this layer is risky as the fault tolerance level of the network will be zero when the base stations break down. Generally, the cluster heads are within the base station spectrum, making seamless integration possible. Implementing a dual base station to cater for a breakdown of the first base station creates huge remoteness as the cluster heads are not within the spectrum of the second base station. Furthermore, using the remote base station involves huge latency affecting the performance of the IoT network. In this paper, a relay-based network is presented with intelligence to fetch the shortest path for communicating to reduce latency and sustain the fault tolerance capability of the IoT network. The results demonstrate that the technique improved the fault tolerance of the IoT network by 14.23%.

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IoTRepair: Systematically Addressing Device Faults in Commodity IoT

Cited by 10 publications

References 16 publications

BULWARK: A Framework to Store IoT Data in User Accounts

BULWARK: A Framework to Store IoT Data in User Accounts

IoTCrawler: Challenges and Solutions for Searching the Internet of Things

Implementing Dual Base Stations within an IoT Network for Sustaining the Fault Tolerance of an IoT Network through an Efficient Path Finding Algorithm

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