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Trust assessment in 32 KiB of RAM : multi-application trust-based task offloading for resource-constrained IoT nodes
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Bradbury, Matthew S., Jhumka, Arshad and Watson, Tim (2021) Trust assessment in 32 KiB of RAM : multi-application trust-based task offloading for resource-constrained IoT nodes. In: Symposium on Applied Computing, Virtual conference, Republic of Korea, 22-26 Mar 2021. Published in: SAC '21: Proceedings of the 36th Annual ACM Symposium on Applied Computing pp. 184-193. ISBN 9781450381048. doi:10.1145/3412841.3441898
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Official URL: https://doi.org/10.1145/3412841.3441898
Abstract
There is an increasing demand for Internet of Things (IoT) systems comprised of resource-constrained sensor and actuator nodes executing increasingly complex applications, possibly simultaneously. IoT devices will not be able to execute computationally expensive tasks and will require more powerful computing nodes, called edge nodes, for such execution, in a process called computation offloading. When multiple powerful nodes are available, a selection problem arises: which edge node should a task be submitted to? This problem is even more acute when the system is subjected to attacks, such as DoS, or network perturbations such as system overload. In this paper, we present a trust model-based system architecture for computation offloading, based on behavioural evidence. The system architecture provides confidentiality, authentication and non-repudiation of messages in required scenarios and will operate within the resource constraints of embedded IoT nodes. We demonstrate the viability of the architecture with an example deployment of Beta Reputation System trust model on real hardware.
| Item Type: | Conference Item (Paper) | ||||||
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| Subjects: | T Technology > TK Electrical engineering. Electronics Nuclear engineering | ||||||
| Divisions: | Faculty of Science > Computer Science | ||||||
| Library of Congress Subject Headings (LCSH): | Internet of things, Computer networks -- Security measures, Cloud computing, Application software | ||||||
| Journal or Publication Title: | SAC '21: Proceedings of the 36th Annual ACM Symposium on Applied Computing | ||||||
| Publisher: | ACM | ||||||
| ISBN: | 9781450381048 | ||||||
| Official Date: | 22 March 2021 | ||||||
| Dates: |
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| Page Range: | pp. 184-193 | ||||||
| DOI: | 10.1145/3412841.3441898 | ||||||
| Status: | Peer Reviewed | ||||||
| Publication Status: | Published | ||||||
| Publisher Statement: | Permission to make digital or hard copies of part or all of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for third-party components of this work must be honored. For all other uses, contact the owner/author(s). | ||||||
| Access rights to Published version: | Restricted or Subscription Access | ||||||
| Copyright Holders: | © 2021 Copyright held by the owner/author(s) | ||||||
| RIOXX Funder/Project Grant: |
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| Conference Paper Type: | Paper | ||||||
| Title of Event: | Symposium on Applied Computing | ||||||
| Type of Event: | Conference | ||||||
| Location of Event: | Virtual conference, Republic of Korea | ||||||
| Date(s) of Event: | 22-26 Mar 2021 | ||||||
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