Forming Teams of Smart Objects to Support Mobile Edge Computing for IoT-Based Connected Vehicles

This paper proposes a collaborative framework to support task offloading in connected vehicular environments. The approach relies on the dynamic formation of temporary teams of connected vehicles in a mobile edge computing scenario. A novel trust model is introduced, which integrates both quality of service and quality of results into a unified reliability score, and combines this score with distributed reputation to build a comprehensive trust metric. This trust metric is then exploited to guide a decentralized team formation algorithm, ensuring lightweight, interpretable, and scalable decision-making processes. Simulation results demonstrate that the proposed framework improves task execution quality and fairness, especially for low-performing vehicles. These contributions highlight the novelty and strengths of our collaborative model, positioning it as a promising solution for enhancing cooperation in vehicular edge systems.

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Institutions

Publication Details

Journal
Applied Sciences
Published
2025-08-29
DOI
https://doi.org/10.3390/app15179483
Citations
1
Primary Topic
Blockchain Technology Applications and Security
Type
article
Field-Weighted Citation Impact
3.25

Funders

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article

Forming Teams of Smart Objects to Support Mobile Edge Computing for IoT-Based Connected Vehicles

Giuseppe M. L. Sarnè, Domenico Rosaci, Fabrizio Messina
1 citations
Applied Sciences
Blockchain Technology Applications and Security
3.25
article

Forming Teams of Smart Objects to Support Mobile Edge Computing for IoT-Based Connected Vehicles

Giuseppe M. L. Sarnè, Domenico Rosaci, Fabrizio Messina
article en
1 citations

Abstract

This paper proposes a collaborative framework to support task offloading in connected vehicular environments. The approach relies on the dynamic formation of temporary teams of connected vehicles in a mobile edge computing scenario. A novel trust model is introduced, which integrates both quality of service and quality of results into a unified reliability score, and combines this score with distributed reputation to build a comprehensive trust metric. This trust metric is then exploited to guide a decentralized team formation algorithm, ensuring lightweight, interpretable, and scalable decision-making processes. Simulation results demonstrate that the proposed framework improves task execution quality and fairness, especially for low-performing vehicles. These contributions highlight the novelty and strengths of our collaborative model, positioning it as a promising solution for enhancing cooperation in vehicular edge systems.

Applied SciencesVol. 15(17)
University of Catania (IT), University of Reggio Calabria (IT), University of Milano-Bicocca (IT)
Università di Catania
Openalex Percentile: Top 7%
Blockchain Technology Applications and Security
3.25
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Forming Teams of Smart Objects to Support Mobile Edge Computing for IoT-Based Connected Vehicles — Giuseppe M. L. Sarnè, Domenico Rosaci, et al. · Applied Sciences (2025) | TGRS Research Map | TGRS