An intelligent incentive mechanism for coverage of data collection in cognitive internet of things

Cognitive Internet of Things (CIoT) is viewed as the current IoT integrated with cognitive and cooperative mechanisms to promote performance and achieve intelligence. Intelligence sensing has recently become a key research field. We consider the sensing information coverage issues with intelligent technologies, where people contribute data samples for CIoT captured by sensors, typically on smartphones. For CIoT, deficiencies of sensing information coverage result in loss of human life and social unrest. To tackle this challenge, in this paper, we first propose a new metric, called the Quality of Information Coverage (QIC), which characterizes information coverage quality and rewards for data sensing to maximize the QIC. Furthermore, a market-based incentive mechanism is formulated to guarantee the QIC. We analyze the market equilibrium point, and obtain an optimal expression for generating maximum payoffs for CIoT and reporters. Finally, the effects of a market-based incentive mechanism are examined through extensive simulations. The results demonstrate that the intelligent incentive control mechanism reaches the equilibrium point with a higher QIC than other existing schemes. The QIC algorithm proposed in this paper ensures that the standard deviation number of collected data samples for some areas is reduced by 50%-75%, compared to the existing algorithms, thus, these data samples are balanced. Compare to these non-QIC-aware algorithms, the average price of sensing data is reduced by 18.94%. (C) 2019 Elsevier B.V. All rights reserved.