2022
Weerapanpisit, Ponlawat; Trilles-Oliver, Sergio; Huerta-Guijarro, Joaquín; Painho, Marco
A Decentralized Location-Based Reputation Management System in the IoT Using Blockchain Journal Article
In: IEEE Internet of Things Journal, vol. 9, no. 16, pp. 15100 - 15115, 2022, ISSN: 2327-4662.
Abstract | Links | BibTeX | Tags: blockchain, Internet of things, location-based services, spatial indexing
@article{Weerapanpisit2022a,
title = {A Decentralized Location-Based Reputation Management System in the IoT Using Blockchain},
author = {Ponlawat Weerapanpisit and Sergio Trilles-Oliver and Joaquín Huerta-Guijarro and Marco Painho},
doi = {https://doi.org/10.1109/JIOT.2022.3147478},
issn = {2327-4662},
year = {2022},
date = {2022-08-15},
journal = {IEEE Internet of Things Journal},
volume = {9},
number = {16},
pages = {15100 - 15115},
abstract = {The Internet of Things (IoT) allows an object to connect to the Internet and observe or interact with a physical phenomenon. The communication technologies allow one IoT device to discover and communicate with another in order to exchange services, in a similar way to what humans do in their social networks. Knowing the reputation of another device is important to consider whether it is trustworthy before establishing a new connection and thus, avoid possible unexpected behaviors as a consequence. Trustworthiness, as a property of a device, can be affected by different factors including its geographical location. Hence, this research work proposes an architecture to manage reputation values of end devices in an IoT system based on the area where they are located. A cloud–fog–edge architecture is proposed, where the fog layer uses the Blockchain technology to keep the reputation management system consistent and fault tolerant across different nodes. The location-based part of the system was done by storing geographical areas in smart contracts (coined as geospatial smart contracts) and making the reputation values subject to different regions depending on the geographical location of the device. To reduce the complexity of the spatial computation, the geographical data are geocoded by either one of two different spatial indexing techniques. This work also introduced two different structures for storing geocoded areas based on either cell list or tree structure. Finally, three experiments to test the proposed architecture are presented, to deploy the architecture in IoT devices, and to compare the two geocoding techniques in smart contracts.},
keywords = {blockchain, Internet of things, location-based services, spatial indexing},
pubstate = {published},
tppubtype = {article}
}
The Internet of Things (IoT) allows an object to connect to the Internet and observe or interact with a physical phenomenon. The communication technologies allow one IoT device to discover and communicate with another in order to exchange services, in a similar way to what humans do in their social networks. Knowing the reputation of another device is important to consider whether it is trustworthy before establishing a new connection and thus, avoid possible unexpected behaviors as a consequence. Trustworthiness, as a property of a device, can be affected by different factors including its geographical location. Hence, this research work proposes an architecture to manage reputation values of end devices in an IoT system based on the area where they are located. A cloud–fog–edge architecture is proposed, where the fog layer uses the Blockchain technology to keep the reputation management system consistent and fault tolerant across different nodes. The location-based part of the system was done by storing geographical areas in smart contracts (coined as geospatial smart contracts) and making the reputation values subject to different regions depending on the geographical location of the device. To reduce the complexity of the spatial computation, the geographical data are geocoded by either one of two different spatial indexing techniques. This work also introduced two different structures for storing geocoded areas based on either cell list or tree structure. Finally, three experiments to test the proposed architecture are presented, to deploy the architecture in IoT devices, and to compare the two geocoding techniques in smart contracts.