Timeliness-Aware Incentive Mechanism for Vehicular Crowdsourcing in Smart Cities

Abstract

Vehicular crowdsourcing is a promising paradigm that takes advantage of powerful onboard capabilities of vehicles to perform various tasks in smart cities. To fulfill this vision, a well-designed incentive mechanism is essential to stimulate the participation of vehicles. In this paper, we propose a timeliness-aware incentive mechanism for vehicular crowdsourcing by taking vehicle’s uncertain travel time into account. In view of the stochastic nature of traffic conditions, we derive a tractable expression for the probability distribution of task delay based on a discrete-time traffic model. By leveraging reverse auction framework, we model the utility of a service requester as a function in terms of <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">uncertain</i> task delay and incurred payment. To maximize the requester’s utility under a budget constraint, we cast the mechanism design as a non-monotone submodular maximization problem over a knapsack constraint. Based on this formulation, we develop a <underline xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">t</u> ruthful <underline xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">b</u> udgeted <underline xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">u</u> tility <underline xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">m</u> aximization <underline xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">a</u> uction (TBUMA), which is truthful, budget feasible, profitable, individually rational and computationally efficient. Through extensive trace-based simulations, we demonstrate the effectiveness of our proposed incentive mechanism.