Skip to Main Content
Sensor networks are multi hop wireless networks formed by a large number of resource-constrained sensor nodes. The events detected by the sensor generate a stream of data. Centralized join query processing algorithm incur more communication overhead due to frequent exchange of data between the sink and the sensor nodes. To query or access data generated by the sensor nodes, the sensor network can be viewed as a distributed database. Communication-efficient implementation for join of multiple data streams in a sensor network is particularly challenging due to unique characteristics of the sensor networks such as limited memory and battery energy on individual nodes. Hence the design of Distributed Nested Loop Join Processing (DNLJP) algorithm has been proposed in this paper. The proposed scheme groups sensors based on geographic locations to form a cluster and perform the query processing in a distributed manner over the data collected across different regions. DNLJP also optimizes the query based on the desired optimization criteria like query cost, query execution time etc., and applies the corresponding query processing technique to achieve the desired result. Analysis shows that the communication overhead of the proposed distributed algorithm is reasonably low and the efficiency of the query processing is considerably improved over a wide range of query.