Optimized differencing algorithm for firmware updates of low-power devices

Kachman, Ondrej; Baláž, Marcel

doi:10.1109/ddecs.2016.7482473

Cited by 15 publications

(8 citation statements)

References 7 publications

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“…This chapter provides experimental results that show, how various configurations of our methodology may be the most suitable for the different scenarios of over-the-air updates. In [10], we presented our differencing algorithm that outperforms existing solutions. Therefore, we use it for the following experiments executed on the ATmega32u4 microcontroller.…”

Section: Resultsmentioning

confidence: 99%

“…Generating delta files. Many differencing algorithms have been developed for various networks of embedded devices [9] [10]. These algorithms are designed to generate very small delta files (deltas, patches).…”

Section: Main Challenges For the Remote Reprogramming Methodsmentioning

confidence: 99%

“…The last problem deals with the implementation of the update procedure on the target devices. Reprogramming code is often embedded into the bootloader [4] or resides in its own reserved space [10]. The updates of this code are very rare and critical.…”

Section: Main Challenges For the Remote Reprogramming Methodsmentioning

confidence: 99%

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Configurable Reprogramming Methodology for Embedded Low-Power Devices

Kachman

Baláž

2017

IFIP Advances in Information and Communication Technology

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Section: Resultsmentioning

confidence: 99%

Section: Main Challenges For the Remote Reprogramming Methodsmentioning

confidence: 99%

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Configurable Reprogramming Methodology for Embedded Low-Power Devices

Kachman

Baláž

2017

IFIP Advances in Information and Communication Technology

Self Cite

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“…Many differencing algorithms assume abundance of spare memory [60] at the node side for firmware reconstruction, something not always true due to the constrained nature of several IoT node types. In [66], the authors propose a differencing algorithm, known as DG, for nodes that lack external memory. The algorithm by exploiting the fact that two sequential firmware versions usually share many common parts, places the two images side-by-side and executes an XOR operation between the corresponding bytes, aiming to reveal the sequences of the non-matching bytes.…”

Section: Delta Generator (Dg)mentioning

confidence: 99%

Firmware over-the-air programming techniques for IoT networks -- A survey

Arakadakis¹,

Charalampidis²,

Makrogiannakis³

et al. 2020

Preprint

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The devices forming the Internet-of-Things (IoT) networks need to be re-programmed over-the-air, so that new features are added, software bugs or security vulnerabilities are resolved and their applications can be re-purposed. The limitations of IoT devices, such as installation in locations with limited physical access, resource-constraint nature, large scale and high heterogeneity, should be taken into consideration for designing an efficient and reliable pipeline for over-the-air programming (OTAP). In this work, we present a survey of OTAP techniques, which can be applied to IoT networks. We highlight the main challenges and limitations of OTAP for IoT devices and analyse the essential steps of firmware update process, along with different approaches and techniques that implement them. In addition, we discuss schemes that focus on securing the OTAP process. Finally, we present a collection of state-of-the art open-source and commercial platforms that integrate secure and reliable OTAP.

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“…Additionally, memory must be set aside to store this firmware as well as room for the current image and any future image [8,9]. Memory requirements may be slightly reduced by using delta updates [[10], [11], [12]] but this is only helpful when modifying code but not completely changing applications. These memory requirements become increasingly problematic for constrained applications where devices have lower power and reduced storage so memory cannot so easily be set aside for such applications.…”

Section: Additional Informationmentioning

confidence: 99%