Article Dans Une Revue Discover Internet of Things Année : 2025

Combinatorial double auction for multi-resource trading in IoT applications

Résumé

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 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.

Dates et versions

hal-05102281 , version 1 (07-06-2025)

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Citer

Sara Ranjbaran, Amir Reza Jafari, Noel Crespi, Sérgio Correia. Combinatorial double auction for multi-resource trading in IoT applications. Discover Internet of Things, 2025, 5 (69), ⟨10.1007/s43926-025-00166-w⟩. ⟨hal-05102281⟩
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