The proliferation of wireless sensors has given rise to Public Sensing (PS) as a vibrant data-sharing model. This vision can be extended under the umbrella of the Internet of Things (IoT) to include versatile data sources within smart cities such as cellphones, Radio Frequency Identification (RFID) tags and sensors on roads, buildings and living spaces. The facilitation of such a vision faces many challenges in terms of interoperability, resource management and pricing. In this paper, we present a priced public sensing (PPS) framework for IoT architectures. Our framework caters for service-based applications in smart cities where data is provided via a data cloud of multifarious data sources. We propose online heuristics for public data delivery in smart city settings. We also introduce a pricing utility function for data acquisition. Our pricing function takes into account resource limitations in terms of delay, capacity and lifetime on the data providers' side; as well as user's quality and trust requirements from the requesters' side. We present simulation results showing the efficiency of our scheme as compared to other wireless sensor and mobile Ad-hoc schemes with respect to scalability, lifetime, delay, delivery ratio and price.
utility functions, Wireless sensor networks, public sensing, internet of things, heuristic algorithms
Waleed Alsalih, "A Priced Public Sensing Framework for Heterogeneous IoT Architectures", IEEE Transactions on Emerging Topics in Computing, , no. 1, pp. 1, PrePrints PrePrints, doi:10.1109/TETC.2013.2278698