Honeybee-RS: Enhancing Trust through Lightweight Result Validation in Mobile Crowd Computing

Mobile Crowd Computing (MCC) leverages the collaborative power of nearby devices to solve resource-intensive tasks, offering transformative potential across various fields. However, ensuring device reliability—which directly impacts the trustworthiness of devices in MCC environments—poses a significant challenge. Balancing validation accuracy with performance and energy efficiency is particularly difficult due to MCC’s dynamic and resource-constrained decentralized nature. Existing validation methods are not feasible in MCC, as they can negatively affect speed and energy consumption. This paper introduces the Honeybee-RS framework, a novel approach for validating offloaded computational results in MCC environments. Honeybee-RS provides delegator-based validation mechanisms and derives reliability scores from the validation process. Experiments demonstrate the effectiveness of these mechanisms, significantly enhancing reliability in MCC while maintaining performance.

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Publication Details

Published
2024-12-17
DOI
https://doi.org/10.1109/trustcom63139.2024.00356
Primary Topic
Mobile Crowdsensing and Crowdsourcing
Type
article
Field-Weighted Citation Impact
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article

Honeybee-RS: Enhancing Trust through Lightweight Result Validation in Mobile Crowd Computing

Sanjay Segu Nagesh, Pubudu N. Pathirana, Niroshinie Fernando, Azadeh Ghari Neiat et al.
Mobile Crowdsensing and Crowdsourcing
article

Honeybee-RS: Enhancing Trust through Lightweight Result Validation in Mobile Crowd Computing

Sanjay Segu Nagesh, Pubudu N. Pathirana, Niroshinie Fernando, Azadeh Ghari Neiat, Seng W. Loke
article en

Abstract

Mobile Crowd Computing (MCC) leverages the collaborative power of nearby devices to solve resource-intensive tasks, offering transformative potential across various fields. However, ensuring device reliability—which directly impacts the trustworthiness of devices in MCC environments—poses a significant challenge. Balancing validation accuracy with performance and energy efficiency is particularly difficult due to MCC’s dynamic and resource-constrained decentralized nature. Existing validation methods are not feasible in MCC, as they can negatively affect speed and energy consumption. This paper introduces the Honeybee-RS framework, a novel approach for validating offloaded computational results in MCC environments. Honeybee-RS provides delegator-based validation mechanisms and derives reliability scores from the validation process. Experiments demonstrate the effectiveness of these mechanisms, significantly enhancing reliability in MCC while maintaining performance.

Deakin University (AU), The University of Queensland (AU)
Openalex Percentile: Top 69%
Mobile Crowdsensing and Crowdsourcing
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