Optimizing distributed Top-k queries on uncertain data

With the advances in technology of CPS (Cyper Physical System), it is found that uncertain data arises in many important domains, such as WSN, RFID, P2P system, and so on. It poses a great challenge on Top-k query processing, which is a very common and crucial application in data management. In this paper, we summarize several semantics of top-k queries on uncertain data and propose an optimized algorithm DMPUTop-k for processing most probable uncertain Top-k queries(MPUTop-k) in the distributed environment. In addition, we analyze the equivalence between MPUTop-k and UTop-k in some special cases. The experiments on real dataset show that our technique can greatly reduce the bandwidth consumption for processing Top-k queries in distributed uncertain dataset.