Abstract :
In wireless sensor networks (WSNs), where the battery supply is extremely limited, reduction in transmission is necessary for lengthening the life span of the networks. However, the QoS of transmission is always impaired when data aggregation mechanisms are applied. In this article, we put forward a new approach-Adaptive Data Aggregation Mechanism (ADAM) to solve this dilemma, based on a unique characteristic in WSNs on LEACH protocol: the resemblance of data sent from neighboring nodes. Adopting ADAM, the cluster head examines the statistical characters of packets received from surrounding nodes to achieve the optimal aggregation parameters, breaks the data into blocks and then use a shorter data pattern to represent repeating blocks in transmission so as to minimize inter-node level redundancy. At the sink, applying the inverse-operation, the original information can be totally recovered. The specific message formats, the algorithm and the parameters such as frame size and block size are devised and tested in the following passages. And from the simulation, we prove the effectiveness of ADAM in realizing data fusion with remarkable compression ratio and thus expanding the lift-time of the networks.
