A query in Cougar consists of a query on stored data and query on sensor
data. That is, a query on relational data and a query on time serial data. A
continuous query is defined as a permanent view which remains unchangeable
in a given period. During the continuous query in Cougar, the queried relation
and the time serial can be updated. Update on relational data includes
inserting into, deleting from and updating on tuples in the table. Update on
time serial means inserting a new tuple into the time serial.
3.2 Query Language
There are a lot of characteristics of sensor data in sensor networks, such as real
time, periodicity, uncertainty etc. Till now, query schemes proposed include
snapshot query, continuous query, event-based query, life-cycle based query
and accuracy-based query. For sensor networks, it is very important to design
a general, simple, e?±cient, extendable, expressible query language based on
query schemes and characteristics of sensor data.
Query Language in TinyDB
TinyDB??™s query language is based on SQL, and we will refer to it as TinySQL.
Query Language in TinySQL supports selection, projection, determining sampling
rate, group aggregation, user defined aggregation, event trigger, lifetime
query, setting storing point and simple join [15].
The Grammar of TinySQL query language is as follows:
SELECT select-list
[FROM sensors]
WHERE predicate
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Chapter 12 Data Management in Sensor Networks
[GROUP BY gb-list]
[HAVING predicate]
[TRIGGER ACTION command-name[(param)]]
[EPOCH DURATION time]
where, select??’list is the attribute list of the unlimited virtual relational table,
which can include an aggregation function.
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