TGBA: A two-phase group buying based auction mechanism for recruiting workers in mobile crowd sensing

Mobile crowd sensing (MCS) has become a promising paradigm to perceive the environment with the help of smart phones. Providing monetary rewards is an effective way to encourage smart phone users to contribute good quality data. However, the cost for long-term data collection in a wide area could be unaffordable for a MCS requester. In this paper, we enable data requesters to recruit sensing workers in a group buying way. Requesters with similar data demand can form a group to share the payment, which significantly reduces the cost. Each group has an agent, which represents all group members to compete in recruiting sensing workers. In this paper, we propose a group buying based auction mechanism for MCS, which consists of two phases. In the first phase, requesters submit their demands of sensing data and bids to their group agent, the group agent decides the winners of this group and the affordable payment collected from the winners. In the second phase, group agents attend the auction for recruiting sensing workers. If a group agent wins a worker, his group members pay the worker and obtain the demanding data. Two algorithms are proposed for each phase of TGBA. We have proved that TGBA is computationally efficient and possesses good economic properties such as individual rationality, budget balance and truthfulness, no matter whichever algorithm is chosen for the two phases. Extensive simulations are conducted, which show our proposed algorithms achieve better performance than the baseline mechanism without group buying. (C) 2018 Elsevier B.V. All rights reserved.