Socially Aware Multi-Resource Trading for IoT Applications in Smart Cities using Auction theory

Abstract

The availability of a large number of devices in the Internet of Things (IoT) allows us to carry out distributed applications in a collaborative fashion. This approach is especially beneficial in smart city scenarios, wherein different types of resources (i.e., for sensing and actuation, in addition to computation and storage) are key to providing effective location-based services. This article addresses sharing heterogeneous resources for IoT applications in smart cities. Specifically, it takes a gametheoretic approach and addresses the problem of allocating resources from different devices as a combinatorial double auction. Features specific to IoT devices, including their affinity (e.g., ownership and co-location), are leveraged to form groups that offer resource bundles with a certain reliability. The proposed solution incurs a low computational complexity and achieves several important economic properties: incentive compatibility, individual rationality, and a balanced budget. Simulations based on a large-scale dataset demonstrate that the combinatorial double auction is effective and can be completed in a short time.