## 1 Introduction  
Technological advances, decreasing production costs and increasing capabilities have made sensor networks suitable for many application fields such as various scientific and commercial applications including warehouse management, battlefield surveillance and environmental monitoring [1-4]. Thanks to the advanced technology, over time sensor networks have been adopted in an all-around industry. Gathering data to be aware of any states by using those sensors is achieved by modeling it as a distributed database where sensor readings are collected and processed using queries [5-7].  
Especially, sensor node components of sensor networks obtain the state information from sensor device parts on those nodes and store those data. Accordingly, each sensor node in a sensor network is regarded as a distributed database system generating a data stream and has been studied as a sensor database [7]. In query processing of sensor networks, the join operation costs much in sensor networks for correlating sensor readings like distributed database environments [8]. Therefore, many researchers have studied reducing the cost in sensor environment [1].  
In a sensor network environment, a query is issued for retrieving and gathering the real time state information. The form of a well-used query in a sensor network is using an SQL-like declarative language [8]. The collected data in a sensor network can be seen as one distributed relation over the sensor nodes, called the sensor relation. The query operations are also served restrictively because of the limitation of the environments. Further, most previous solutions either assume that nodes have sufficient memory to buffer the partition of the join relations assigned to them for processing, or that the amount of memory available at each node is known in advance and the assigned data partitions can be set accordingly [1]. Under these assumptions, it is hard to apply assumptions to real life.  
Therefore, we consider the communication cost aspect and we propose an Incremental Join Algorithm (IJA) as an in-network join strategy which is an efficient join processing in sensor networks and minimizes communication cost. The IJA strategy is capable of reducing communication cost and utilizing data by gathering real-time state information from sensors which is one of sensor network features. In sensor network environments, it is hard to send all data stored at each node to server located in the center as we consider in the assumptions. Therefore it needs to be filtered whether data are sent or not. The problem in the previous studies is that the results processed in the previous steps would be ignored as a query happens. However, as a different point between the earlier studies and this paper, this algorithm for processing query uses the previous result and just sends the operations needed to be joined to the final node. Therefore assume previous join results are stored in temporary repository to process efficiently. To evaluate the performance, we compare the IJA strategy to the conventional algorithms including synopsis strategy. The remainder of the paper is structured as follows. In the next section, we describe typical join strategies in sensor networks including synopsis to compare. In Section 3, we introduce and explain an incremental join algorithm. And we analyze the performance and compare IJA to typical join strategy including synopsis algorithm. In Section 5, we conclude with future works.