Efficient and Adaptive Data Aggregation for Wireless Sensor Network

Sensor networks are event-based systems that diff er from traditional communication networks in several ways: sensor networks have severe energy constraints, redundant low-rate data, and many-to-one flows. The problem of energy-efficient reliable wireless communication in the presence of unreliable or lossy wireless link layers in multi-hop wireless networks has been a serious issue. In this paper, A novel approach for data gathering in wireless sensor networks is proposed which involves data fusion with broken Links. The number of transmissions by the sensor node is limited by approximating the sensor data at the sink using prediction Approach with buffered datasets. By adaptively using redundant transmission on fusion routes without acknowledgments, packets with more information are delivered with higher reliability. The proposed method is effective and greatly reduces the number of transmissions to the sink node which considered the compromised nodes data forwarding. That optimally solves the minimum energy reliable communication problem in presence of unreliable links.