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Sensor networks are widely used in environmental exploration, military systems, and factory production monitoring. They usually have limited battery source and link bandwidth. Many algorithms have been proposed till now that considered three functional components namely data gathering (sensing and acquisition), data transport and data analysis (processing). In general power is consumed whenever a bit is generated, transmitted or processed. So, various network architectures and different protocols have been proposed for saving energy consumption and extending the life time of sensor node. Our aim, therefore, is to reduce the number of bits to be transported to achieve energy efficiency. This can be done by recognizing the type of stream data, compression based on the source and grooming/aggregation of the traffic. So, we have developed a compression algorithm which is based on identified distribution of sensed stream data of source which aims to reduce network traffic in order to save power by combining both compression algorithm and state model.