7.4 DATA AGGREGATION
A common scenario of sensor networks involves the deployment of hundreds or thousands of low-cost, low-power sensor nodes in a region from where information will be collected periodically. Sensor nodes must sense their nearby environment and send the information to a sink or actuator, from which the collected information can be further processed or made available to the user. In the most basic reporting schemes, each sensor independently sends its data to the associated actuator using routing operations that generates a lot of redundant traffic if the data is geographically or temporally correlated for example, if two neighboring, or successive, measure values are expected to be close to one another). Data aggregation arises from the observation that most of this redundancy could be avoided if the data were partially processed locally to the sensors, for example, by averaging it over time or space before forwarding it. This is what data aggregation does, by applying fusion/consolidation functions to the data along its way to the sink. Example of such functions include average, maximum, minimum, sum, count, or deviation, that can be applied either periodically or on-demand.
Once these functions are chosen and combined, the main problem of data aggregation is to build the overlay structure along which data will be effectively aggregated. This structure must be as efficient as possible to allow a fast aggregation while maximizing the lifetime of the network (i.e., ...
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