Toward Efficient Data Trading in AI Enabled Reconfigurable Wireless Sensor Network Using Contract and Game Theories

Reconfigurable Wireless Sensor Network (RWSN) schedules a set of devices with reconfigurable wireless interface to accomplish different data collection plans in a cost-effective way. AI technologies are applied to optimize decision making for high-level network reconfiguration. Besides, AI based dat...

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Bibliographic Details
Published in:IEEE transactions on network science and engineering 2022-01, Vol.9 (1), p.98-108
Main Authors: Huang, Xumin, Garg, Sahil, Nie, Jiangtian, Lim, Wei Yang Bryan, Qi, Yuanhang, Zhang, Yang, Hossain, M. Shamim
Format: Article
Language:English
Subjects:
AI enabled reconfigurable wireless sensor network
Artificial intelligence
Consumers
contract theory
Contracts
Data collection
Data mining
data trading
Decision making
Electronic devices
Game theory
Games
High level networks
non-cooperative game
Reconfiguration
Sensors
Task analysis
Wireless networks
Wireless sensor networks
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Summary:Reconfigurable Wireless Sensor Network (RWSN) schedules a set of devices with reconfigurable wireless interface to accomplish different data collection plans in a cost-effective way. AI technologies are applied to optimize decision making for high-level network reconfiguration. Besides, AI based data mining tools are exploited by third parities to extract useful information underlying raw data. This leads to the emergence of AI enabled RWSN. We further study a data trading market to provide the data-centric environment for large-scale applications of AI enabled RWSN. A network operator employs the devices to gather environmental data, and sells the collected data to interested third parities as data consumers. After that, two-level optimizations are performed to ensure efficient data trading. In data collection, a contract based incentive mechanism is presented for the network operator to stimulate the devices and simultaneously achieve the contractor's goal subject to feasible constraints. In data selling, a non-cooperative game is formulated among multiple data consumers. They balance the data demand since the final data price is correlated with the total data demand. Nash equilibrium is analyzed and solved under different conditions. Finally, numerical results are provided to demonstrate the effectiveness of our scheme.
ISSN:2327-4697
2334-329X
DOI:10.1109/TNSE.2020.3013064