First, each sensor samples, senses and detects
events. Then a hash function is applied on the event key, and events are stored
at a ???home??? sensor node which is the closest to the hash value of the event
key. This technique is called a Distributed Hash Table (DHT) [16, 17, 18].
To process a query, the same hash function is applied first. Then the query
is sent to the node with the closest hash value for further processing. From
the above description, we can see that this model pushes all computation and
communication to sensor nodes.
The problem with this model is that sensors are assumed to have almost
the same communication and computation capabilities as normal computers.
In addition, DHT is only suitable for key queries, which incurs large communication
cost.
2.4 Hierarchical model
Based on the above survey on existing works on sensor data management in
pervasive computing, [9] proposes a new hierarchical system model, which is
shown in Figure 3. This model includes two layers: sensor network layer and
proxy network layer. This model combines in-network programming, adaptive
query processing and e?±cient content-based search techniques. In the lower
level, sensor network layer, sensor nodes have certain computation and storage
capabilities. Sensors have three functions: receiving commands from proxy,
performing local computation and delivering data to proxy. Sensor nodes receive
control commands including sampling rate, delivery rate and operations
that need to be performed from the proxy layer.
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