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Data for 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) Data for Trust assessment in 32 KiB of RAM : multi-application trust-based task offloading for resource-constrained IoT nodes. [Dataset]
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Official URL: http://doi.org/10.5281/zenodo.4312801
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: | Dataset | ||||||
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Subjects: | T Technology > TK Electrical engineering. Electronics Nuclear engineering | ||||||
Divisions: | Faculty of Science, Engineering and Medicine > Science > Computer Science | ||||||
Type of Data: | Modelling data | ||||||
Library of Congress Subject Headings (LCSH): | Internet of things, Computer networks -- Security measures, Cloud computing, Application software | ||||||
Publisher: | University of Warwick, Department of Computer Science | ||||||
Official Date: | 10 March 2021 | ||||||
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Status: | Not Peer Reviewed | ||||||
Publication Status: | Published | ||||||
Media of Output (format): | .flash .pyterm | ||||||
Access rights to Published version: | Open Access (Creative Commons) | ||||||
Copyright Holders: | University of Warwick | ||||||
Description: | Data record consists of a zip archive containing the raw data and an accompanying readme file. |
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