Wireless Sensor Networks(WSNs) is one of the core components of the Internet of Things(IoTs).Data query processing is a very important research area in Wireless Sensor Networks.Join queries can monitor similar network environments in different positions.Top-k join queries further obtain k similar network environments which have the maximum(or minimum) combination scores.The top-k join query calculates the combination score of matching tuples according to scoring function and reports the top-k matching tuples which have the maximum(or minimum) combination score.In this paper,we propose a Basic Top-k Join Queries(BTJQ) algorithm.In BTJQ,the base station sorts the tuples based on the score attribute values in descending order.Then the base station gets the tuples from the sorted list in turn and produces the join result and calculates the combination score.If the join result meets the stop condition,the base station stops taking tuples and outputs the final top-k join result.Based on the BTJQ,we propose a Centralized Top-k Join Queries(CTJQ) algorithm and Optimize Centralized Top-k Join Queries(OCTJQ) algorithm.For a different scenario,we propose a Distributed Top-k Join Queries(DTJQ) algorithm.Experiments on real-world data set show that our algorithms outperform the typical algorithm SENS-Join.