Requester mobility for mobile crowdsensing system: A dynamic alliance-based incentive mechanism

In the Mobile Crowdsensing (MCS) system, due to the heterogeneity of requesters, they are in mobile which means requesters will join or leave the MCS system at different times and their data demands are time-varying. The uncertainty of requesters caused by requester mobility will generate the instability of the match between requesters and participants which means the established matching algorithm cannot be completed due to the dissatisfaction of requesters and participants caused by the changes in the intensity of competition. For requester mobility, we design a dynamic alliance-based incentive mechanism where requesters can leave, join the MCS system separately, and change their data needs. To the instability, we divide the dynamic mechanism into different stages and will update the matching rules in each stage. A unique algorithm based on the dynamic Stackelberg game and the corresponding updated algorithm is proposed to analyze the matching strategies of requesters and participants to make an optimal match. By proving the stability of the updated rules, we guarantee the stability of the match with requester mobility. Through numerical analysis, alliance formation can significantly reduce weak requesters’ costs by at most 90%. Besides, in our mechanism any requester participates in the game at most twice, the chosen rate can be up to 100%.