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Data for Trust trackers for computation offloading in edge-based IoT networks
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Bradbury, Matthew S., Jhumka, Arshad and Watson, Tim (2021) Data for Trust trackers for computation offloading in edge-based IoT networks. [Dataset]
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Official URL: http://doi.org/10.5281/zenodo.4339398
Abstract
Wireless Internet of Things (IoT) devices will be deployed to enable applications such as sensing and actuation. These devices are typically resource-constrained and are unable to perform resource-intensive computations. Therefore, these jobs need to be offloaded to resource-rich nodes at the edge of the IoT network for execution. However, the timeliness and correctness of edge nodes may not be trusted (such as during high network load or attack). In this paper, we look at the applicability of trust for successful offloading. Traditionally, trust is computed at the application level, with suitable mechanisms to adjust for factors such as recency. However, these do not work well in IoT networks due to resource constraints. We propose a novel device called Trust Tracker (denoted by Σ) that provides higher-level applications with up-to-date trust information of the resource-rich nodes. We prove impossibility results regarding computation offloading and show that Σ is necessary and sufficient for correct offloading. We show that, Σ cannot be implemented even in a synchronous network and we compute the probability of offloading to a bad node, which we show to be negligible when a majority of nodes are correct. We perform a small-scale deployment to demonstrate our approach.
Item Type: | Dataset | ||||||
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Subjects: | Q Science > QA Mathematics Q Science > QA Mathematics > QA76 Electronic computers. Computer science. Computer software T Technology > TK Electrical engineering. Electronics Nuclear engineering |
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Divisions: | Faculty of Science, Engineering and Medicine > Science > Computer Science | ||||||
Type of Data: | Modelling data | ||||||
Library of Congress Subject Headings (LCSH): | Internet of things, Machine-to-machine communications, Edge computing | ||||||
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): | .pdf .py .txt | ||||||
Copyright Holders: | University of Warwick | ||||||
Description: | Data record consists of a zip archive containing the data codes and instructions for experiment set up, as well as an accompanying readme file. Further information on specific data can be found in the accompanying readme file. |
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