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Contexts, the pieces of information that capture the characteristics of computing environments, are often inconsistent in the dynamic and uncertain pervasive computing environments. Various schemes have been proposed to check context consistency for pervasive applications. However, existing schemes implicitly assume that the contexts being checked belong to the same snapshot of time. This limitation makes existing schemes do not work in pervasive computing environments, which are characterized by the asynchronous coordination among computing devices. The main challenge imposed on context consistency checking by asynchronous environments is how to interpret and detect concurrent events. To this end, we propose in this paper the concurrent events detection for asynchronous consistency checking (CEDA) algorithm. An analytical model, together with corresponding numerical results, is derived to study the performance of CEDA. We also conduct extensive experimental evaluation to investigate whether CEDA is desirable for context-aware applications. Both theoretical analysis and experimental evaluation show that CEDA accurately detects concurrent events in time in asynchronous pervasive computing environments, even with dynamic changes in message delay, duration of events and error rate of context collection.