Sensor Network Databases
November 3, 2016
Categorised in: Data Communicaiton & Wireless Sensor Networks
Sensor Network as Database: Think of a sensor network as a distributed database that store data within the network and allow queries to be injected anywhere in the network.
Research issues
- how is data stored and organized after sensing
- what’s the user interface to the sensor database
- How does an external query find and process the data in an efficient manner?
Challenges
The system is highly volatile
Relational tables are not static
- New data is continuously sensed
High communication cost
- In-net processing during query execution
Arbitrarily long delay and rate of data arrival is variable
Limited storage
- Older data has to be discarded
- Keep statistics
Long-running, continuous queries
Example Query
High-level query interface such as SQL
For next 3 hours, retrieve every 10 minutes the max rainfall level in each county in California, if it is greater than 3.0 inch.
SELECT max (rainfal_Level) ,county FROM sensors
Where STATE = California GROUP BY country
HAVING max (rainfal_Level) > 3.0in
DURATION [ now, now+180min]
SAMPLING PERIOD 10 min
Issues
How to identify relevant sensors?
Computation vs. communication tradoff Where to process query?
- Inside the sensor network (route query)
- At centralized location (route data) – Large amount of data transfer -> not efficiency
- How to process?
Sensor Network Database
SQL type query interface.
Distributed query execution.
Represents each sensor as ADT (applies encapsulation as OOP).
Each measurement is associate with a time stamp.
Whenever a signal processing function returns value a record is inserted into virtual relations (never updated or deleted).
Probabilistic queries
Uncertainty in reading due to noise environmental disturbances.
Gaussian ADT (GADT) which models probability distribution function over possible measurement values.
•Example
SELECT *
From Sensors
WHERE Sensor.Temp.Prob([67.5,68.5]>=0.6)
TinyDB Query Processing
System designed to support in-network
aggregate query processing.
SQL type query interface.
Support functions like: min,max,count,sum,average
Data Indices and Range Queries
Key idea: pre-storing the answers to certain special queries
One-dimensional indices
- Recognized subset: the subset of data forming pre-stored answers
Example:
- Counting cars passing in each sensor
- Query for counts over various contiguous segments
Sensor Network Platforms and tools
Commercially available sensor nodes :
- Specialized sensing platform such as Spec node designed at University of California-Berkeley.
- Generic Sensor platform – Berkeley Mote.
- High bandwidth sensing platform such as iMote.
- Gateway Platform such as Stargate. (sink node).
Pratik Kataria is currently learning Springboot and Hibernate.
Technologies known and worked on: C/C++, Java, Python, JavaScript, HTML, CSS, WordPress, Angular, Ionic, MongoDB, SQL and Android.
Softwares known and worked on: Adobe Photoshop, Adobe Illustrator and Adobe After Effects.