Abstract: This paper presents an efficient reverse k nearest neighbor search algorithm.Under the conditions that the secondary storage is cheap and the current computers are powerful enough,the algorithm pre-computes the mutual distance between objects of the dataset,and organizes them into index blocks that are stored in secondary memory and can be update offline automatically by the computer.Only the necessary block into memory is needed,and the reverse k nearest neighbor(RkNN) query for any k can be straightforwardly dore.The time complexity of the query is O(N).To reduce the consumption of the I/O cost for the index block,this paper proposes a method to compress the index block by using the necessary binary bits to store the distance and reducing the redundancy to a minimum level,which effectively improves the efficiency of the algorithm.Finally,experiments show the effectiveness and efficiency of the proposed algorithms.