The National Weather Sensor Grid
∗
Hock Beng Lim, Keck Voon Ling, Wenqiang Wang, Yuxia Yao, Mudasser Iqbal,
Boyang Li, Xiaonan Yin, Tarun Sharma
Intelligent Systems Centre
Nanyang Technological University
limhb@ntu.edu.sg
http://nwsp.ntu.edu.sg/nwsp
Categories and Subject Descriptors
C.2.4 [Distributed Systems]: Distributed applications
General Terms
Design, Experimentation, Measurement
Keywords
Sensor Networks, Grid Computing, Sensor Grid, Sensor
Data Management, Data Visualization, Web Integration
1 Introduction
With the rapid advances in technologies such as MEMS
sensors, low-power embedded processing and wireless net-
working, sensor networks are becoming more powerful in
terms of data acquisition and processing capabilities. Sensor
networks can now be deployed in the physical world for var-
ious important applications such as environmental monitor-
ing, weather monitoring and modeling, military surveillance,
healthcare monitoring, tracking of goods and manufacturing
processes, smart homes and offices, etc.
The field of sensor networks has grown dramatically in
recent years. However, it remains a daunting challenge to
deploy large-scale sensor networks. It is also difficult to in-
tegrate sensor networks with existing IT infrastructures such
as the Internet. Thus, sensor networks often operate as sepa-
rate information silos, and the sensor resources and data can-
not be easily shared. In fact, with a large number of sensor
devices potentially deployed over a wide area, sensor net-
works are important distributed computing resources that can
be shared by different users and applications.
Grid computing is an established standards-based ap-
proach to solve large-scale problems through coordinated
sharing of distributed and heterogeneous resources in dy-
namic virtual organizations. Most existing developments in
grid computing focus on compute grids, which provide dis-
tributed computational resources for compute-intensive ap-
plications, and data grids, which provide seamless access to
large amounts of distributed data and storage resources.
∗
This work is supported in part by Microsoft Research under
the SensorMap Request for Proposals (RFP) 2007.
Copyright is held by the author/owner(s).
SenSys’07,
November 6–9, 2007, Sydney, Australia.
ACM 1-59593-763-6/07/0011
Most recently, the concept of sensor grids [1] has received
increasing attention from the research community. Sensor
grids extend the grid computing paradigm to the sharing of
sensor resources in sensor networks. A sensor grid inte-
grates sensor networks with the computational and storage
resources in the conventional grid fabric. The vast amount
of data collected by the sensors can be stored, processed and
analyzed by the computational and data storage resources of
the grid. Sensor resources can be efficiently shared by differ-
ent users and applications through the resource sharing and
coordination capabilities of the grid.
The National Weather Study Project (NWSP) is a large-
scale community-based environmental initiative in Singa-
pore that aims to promote the awareness about weather pat-
terns, climate change, global warming and the environment.
In this project, hundreds of mini weather stations are de-
ployed in schools throughout Singapore. Each weather sta-
tion contains several sensors for measuring weather param-
eters such as temperature, rainfall, humidity, wind speed
and direction, etc. Since the geographical locations of these
school weather stations cover most parts of Singapore, the
microclimate weather data from these stations provide a
good profile of the weather patterns within Singapore.
We are designing and building the National Weather Sen-
sor Grid (NWSG) to support and to realize the full poten-
tial of the NWSP. The NWSG has several important fea-
tures. First, it connects the weather stations via the Inter-
net to automatically collect and aggregate weather data in
real-time. Second, the weather data are logically stored in a
Central Data Depository (CDD) which can be implemented
using distributed data storage resources. Third, the NWSG
integrates computational resources for the compute-intensive
processing of weather data. Fourth, the weather data can be
easily accessible and shared via the web through mash-ups,
blogs, and other user applications. We are developing tech-
niques and tools to efficiently publish, query, process, visu-
alize, archive and search the vast amount of weather data.
Finally, the NWSG should be scalable to handle hundreds
of weather stations, and also extensible to handle different
types of sensors besides weather stations.
At present, we have developed a prototype of the NWSG
with several connected weather stations. This prototype en-
ables us to improve the design of the sensor grid architecture.
It also provides several useful services for the users to access
and visualize the weather data.
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