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Title	Combinatorial Double Auction For Multi-Resource Trading In Iot Applications
ID_Doc	14802
Authors	Ranjbaran S.; Jafari A.R.; Crespi N.; Correia S.D.
Year	2025
Published	Discover Internet of Things, 5, 1
DOI	http://dx.doi.org/10.1007/s43926-025-00166-w
Abstract	The proliferation of Internet of Things (IoT) devices has opened new roads for collaborative distributed applications, particularly in smart city environments, where a variety of resources, including sensing, actuation, computation, and storage, are essential for providing effective location-based services. This paper specifically focuses on the sharing of heterogeneous resources among IoT applications in smart cities. By leveraging game-theoretic principles, this study addresses resource allocation through a combinatorial double auction. The solution is rooted in the concept of Social IoT (SIoT), where Internet-connected objects create dynamic social networks based on rules set by their owners. Social relationships, such as ownership and co-location, are leveraged to form groups offering enhanced reliability resource bundles. The proposed solution offers several key economic properties, including incentive compatibility, individual rationality, and a balanced budget, while maintaining low computational complexity. Simulation results demonstrate that the proposed combinatorial double auction mechanism achieves over 70% successful resource allocation for up to 1000 requests, maintains computational efficiency with execution times under 30 s, and ensures economic properties such as incentive compatibility and individual rationality, making it a scalable and practical solution for large-scale smart city IoT applications. © The Author(s) 2025.
Author Keywords	Combinatorial double auction; Edge computing; Resource sharing; Smart cities; Social Internet of Things

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