With　the　rapid　popularization　of　mobile　devices,　the　mobile　crowdsourcing　has　become　a　hot　topic　in　order　to　make　full　use　of　the　resources　of　mobile　devices.　To　achieve　this　goal,　it　is　necessary　to　design　an　excellent　incentive　mechanism　to　encourage　more　mobile　users　to　actively　undertake　crowdsourcing　tasks,　so　as　to　achieve　maximization　of　certain　economic　indicators.　However,　most　of　the　reported　incentive　mechanisms　in　the　existing　literature　adopt　a　centralized　platform,　which　collects　the　bidding　information　from　workers　and　task　requesters.　There　is　a　risk　of　privacy　exposure.　In　this　paper,　we　design　a　decentralized　auction　framework　where　mobile　workers　are　sellers　and　task　requesters　are　buyers.　This　requires　each　participant　to　make　its　own　local　and　independent　decision,　thereby　avoiding　centralized　processing　of　task　allocation　and　pricing.　Both　of　them　aim　to　maximize　their　utilities　under　the　budget　constraint.　We　theoretically　prove　that　our　proposed　framework　is　individual　rational,　budget　balanced,　truthful,　and　computationally　efficient,　and　then　we　conduct　a　group　of　numerical　simulations　to　demonstrate　its　correctness　and　effectiveness.　©　2022,　The　Author(s),　under　exclusive　license　to　Springer　Nature　Switzerland　AG.