Incentives for Delay-Constrained Data Query and Feedback in Mobile Opportunistic Crowdsensing

. 2016 Jul 21;16(7):1138. doi: 10.3390/s16071138

Algorithm 1: Incentive algorithm for delay-constrained data query and feedback.

1:
When User i meets User j, User i updates his or her $D C C P$ , $D R C P$ and $D F C P$ and creates his or her candidate query, reply and feedback lists, i.e., $L_{i} = L_{j} - (L_{i} \cap L_{j})$ , ${\hat{L}}_{i} = {\hat{L}}_{j} - ({\hat{L}}_{i} \cap {\hat{L}}_{j})$ and ${\overset{ˇ}{L}}_{i} = {\overset{ˇ}{L}}_{j} - ({\overset{ˇ}{L}}_{i} \cap {\overset{ˇ}{L}}_{j})$ .
2:
if User i is the data provider for query q in $L_{i}$ then
3:
replies to the query and gives back to User j;
4:
$L_{i} = L_{i} - {q}$ ;
5:
$γ_{q} = γ_{q} - 1$ ;
6:
else if User i is the query issuer for reply $\hat{q}$ in ${\hat{L}}_{i}$ then
7:
pays a number of credits to User j;
8:
else if User i is the receiver for feedback f in ${\overset{ˇ}{L}}_{i}$ then
9:
pays a number of credits to User j;
10:
end if
11:
Users i and j exchange queries, replies and feedbacks pair by pair according to the Nash bargaining solution.