The design of energy-saving filtering mechanism for sensor networks

The transmission of massive highly related data could generally exist in gathering scenario of sensor networks and lead to the depletion of valuable energy resource. According to the above energy waste problem, an effective filtering mechanism is proposed in the paper to enhance the energy-efficiency of data-gathering. Many current researches adopt clustering method and aggregation technology to lower energy cost during the process in data transmission, while our proposed filtering framework mainly puts emphasis on inhibiting the production of redundant loads at the gathering source to greatly reduce energy cost using self-adaptive filtering scheme, which is constructed by prediction module for mining the time domain association, self-learning module for modifying model and driving module for executing filtering operation. We can prove the above filter components combined with the running of error-driving rule and threshold-distributing rule can effectively decrease the quantity of data transmission in networks based on QoS requirement. Finally, the simulation results show that the proposed filtering mechanism can do better than some classical data gathering approaches on the aspect of energy-saving effect.