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Mobile crowdsensing (MCS) has been intensively explored recently due to its flexible and pervasive sensing ability. Although many incentive mechanisms have been built to attract extensive user participation, Most of these mechanisms focus only on independent task scenarios, where the sensing tasks are independent of each other. On the contrary, we focus on a periodical task scenario, where each user participates in the same type of sensing tasks periodically. In this paper, we consider the long-term user participation incentive in a general periodical MCS system from a frugality payment perspective. We explore the issue under both semi-online (the intra-period interactive process is synchronous while the inter-period interactive process is sequential and asynchronous during each period) and online user arrival models (the previous two interactive processes are sequential and asynchronous). In particular, we first propose a semi-online frugal incentive mechanism by introducing a Lyapunov method. Moreover, we also extend it to an online frugal incentive mechanism, which satisfies the constant frugality. Besides, the two mechanisms can also satisfy computational efficiency, asymptotical optimality, individual rationality and truthfulness. Through extensive simulations, we evaluate the performance and validate the theoretical properties of our online mechanisms.
Mobile Crowdsensing has shown a great potential to address large-scale problems by allocating sensing tasks to pervasive Mobile Users (MUs). The MUs will participate in a Crowdsensing platform if they can receive satisfactory reward. In this paper, i
Incentive mechanism plays a critical role in privacy-aware crowdsensing. Most previous studies on co-design of incentive mechanism and privacy preservation assume a trustworthy fusion center (FC). Very recent work has taken steps to relax the assumpt
Mobile crowdsensing has shown a great potential to address large-scale data sensing problems by allocating sensing tasks to pervasive mobile users. The mobile users will participate in a crowdsensing platform if they can receive satisfactory reward.
Miners in a blockchain system are suffering from ever-increasing storage costs, which in general have not been properly compensated by the users transaction fees. This reduces the incentives for the miners participation and may jeopardize the blockch
Vehicular mobile crowd sensing is a fast-emerging paradigm to collect data about the environment by mounting sensors on vehicles such as taxis. An important problem in vehicular crowd sensing is to design payment mechanisms to incentivize drivers (ag