A Data Fusion Approach for Power Saving in Wireless Sensor Networks Reporter : Chi-You Chen

Outline Introduction Sensor networks architecture Energy saving technique in sensor network Data Fusion in wireless sensor network Conclusion

Introduction A senor network is composed of sensing, data processing, and communicating components. Because the tiny sensor is extremely energy-limited, the lifetime of sensor network becomes an obstacle for its application. In order to conserve the sensor energies, a lot of research has been directed towards energy-efficient routes in sensor network.

Sensor networks architecture A sensor network consists of hundreds of sensor nodes, each with sensing, data processing and communicating components, as shown in fig.1

Sensor networks architecture In wireless sensor network, sensor nodes communicate with each other by radio, infrared or optical media. The sink may communicate with the user by Internet or satellite. The structure of the sensor network is shown in Fig.2. The low-cost sensor network can be used for various application areas, for example, health, military, home and so on.

Sensor networks architecture

Energy saving technique in sensor network The protocol stack The protocol stack includes the physical layer, data link layer, network layer, transport layer, application layer. In this paper, Fusion function is built on the network layer, as show in Fig. 3.

Energy saving technique in sensor network

Routing models in network layer In order to reduce the energy consumed by each sensor, routing models in sensor network have shifted address-centric routing (AC) to data-centric (DC) routing.

Energy saving technique in sensor network In the address–centric approach, each source sends its data separately to the sink. In the data-centric approach, the data from the two sources is aggregated at fusion node, and the combined data is sent from fusion node to the sink.

Energy saving technique in sensor network Directed diffusion Directed diffusion is based on data-centric protocol that can coordinate to perform distributed sensing of an environmental phenomenon.

Data Fusion in wireless sensor network Fusion level and energy consuming The key idea is to combine data from different sensors to eliminate redundant transmissions, and provide rich, useful information of the environment being monitored, as shown in fig.6.

Data Fusion in wireless sensor network The simplest data aggregation function is duplicate suppression if two sources both send the same data, fusion node will send only one of these forward. Other aggregation functions could be max, min, or any other function with multiple inputs.

Data Fusion in wireless sensor network A three-level hierarchy is widely accepted by data fusion practitioners. These three levels are data-level fusion, feature-level fusion and decision-level fusion

Data Fusion in wireless sensor network Fusion technique sensor fusion is concerned with distributed detection, target identification, decision fusion. Various techniques such as least square method, Bayesian method, Dempster-Shafer, Fuzzy logic has been proposed. All of these techniques used for fusion are not as simple as max, min, however, sensor node are so limited in computational capacities that some technique may be difficulty for sensor nodes implementing

Conclusion Data fusion, or data aggregation, is a technique for power saving in sensor networks. fusion function holds the promise of achieving high performance at a low cost in terms of energy and communication