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Information management for trust computation on resource-constrained IoT devices
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Bradbury, Matthew S., Jhumka, Arshad and Watson, Tim (2022) Information management for trust computation on resource-constrained IoT devices. Future Generation Computer Systems, 135 . pp. 348-363. doi:10.1016/j.future.2022.05.004 ISSN 0167-739X.
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WRAP-information-management-trust-computation-resource-constrained-IoT-devices-2022.pdf - Published Version - Requires a PDF viewer. Available under License Creative Commons Attribution 4.0. Download (1239Kb) | Preview |
Official URL: https://doi.org/10.1016/j.future.2022.05.004
Abstract
Resource-constrained Internet of Things (IoT) devices are executing increasingly sophisticated applications that may require computational or memory intensive tasks to be executed. Due to their resource constraints, IoT devices may be unable to compute these tasks and will offload them to more powerful resource-rich edge nodes. However, as edge nodes may not necessarily behave as expected, an IoT device needs to be able to select which edge node should execute its tasks. This selection problem can be addressed by using a measure of behavioural trust of the edge nodes delivering a correct response, based on historical information about past interactions with edge nodes that are stored in memory. However, due to their constrained memory capacity, IoT devices will only be able to store a limited amount of trust information, thereby requiring an eviction strategy when its memory is full of which there has been limited investigation in the literature. To address this, we develop the concept of the memory profile of an agent and that profile’s utility. We formalise the profile eviction problem in a unified profile memory model and show it is NP-complete. To circumvent the inherent complexity, we study the performance of eviction algorithms in a partitioned profile memory model using our utility metric. Our results show that localised eviction strategies which only consider one specific type of information do not perform well. Thus we propose a novel eviction strategy that globally considers all types of trust information stored and we show that it outperforms local eviction strategies for the majority of memory sizes and agent behaviours. In this paper, we develop a concept of information utility to a trust model and formalise the problem of information eviction, which we prove to be NP-complete. We then investigate the usefulness of different eviction strategies to maximise the utility of information stored to enable trust-based task offloading.
Item Type: | Journal Article | ||||||||
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Subjects: | Q Science > QA Mathematics > QA76 Electronic computers. Computer science. Computer software | ||||||||
Divisions: | Faculty of Science, Engineering and Medicine > Science > Computer Science Faculty of Science, Engineering and Medicine > Engineering > WMG (Formerly the Warwick Manufacturing Group) |
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Library of Congress Subject Headings (LCSH): | Internet of things, Gateways (Computer networks), Memory management (Computer science), Cache memory | ||||||||
Journal or Publication Title: | Future Generation Computer Systems | ||||||||
Publisher: | Elsevier Science BV | ||||||||
ISSN: | 0167-739X | ||||||||
Official Date: | October 2022 | ||||||||
Dates: |
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Volume: | 135 | ||||||||
Page Range: | pp. 348-363 | ||||||||
DOI: | 10.1016/j.future.2022.05.004 | ||||||||
Status: | Peer Reviewed | ||||||||
Publication Status: | Published | ||||||||
Access rights to Published version: | Open Access (Creative Commons) | ||||||||
Date of first compliant deposit: | 31 May 2022 | ||||||||
Date of first compliant Open Access: | 31 May 2022 | ||||||||
RIOXX Funder/Project Grant: |
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