Integration of Sensor Web services into Grid environment

Sensor Web is an emerging paradigm and technology stack for integration of heterogeneous sensors into common informational infrastructure. The basic functionality required from such infrastructure is remote data access with filtering capabilities, sensors discovery and triggering of events by sensors conditions.
Sensor Web is governed by the set of standards developed by Open Geospatial Consortium [1. It should be also mentioned that Sensor Web paradigm assumes that sensors may belong to different organizations with different access policies or, in broader sense, to different administrative domains. However existing standards stack doesn’t provide any means for enforcing data access policies leaving it to underlying technologies. One possible way for handling informational security issues in Sensor Web is using of Grid approach.
To check Sensor Web technology applicability for real world tasks we have decided to try it for solving the problem of floods monitoring and prediction using satellite remote sensing data, in situ data and results of simulations.
The problem of floods monitoring by itself consumes data from many heterogeneous data sources such as remote sensing satellites (we are using data of ASAR, MODIS and MERIS sensors), in situ observations (water levels, temperature, humidity, etc). Floods prediction is adding the complexity of physical simulation to the task.
To predict flooding parameters such as rivers stage/discharge and extents of flooded areas we use cascade of simulation models: regional numerical weather prediction (NWP) model, hydrological model and hydraulic model. This approach was modelled after successful work of Hluchy et. al. [2] considering Slovakian watersheds. To obtain quantitative estimates of precipitation and other meteorological forcing WRF (Weather Research&Forecasting) regional NWP model is used. WRF model is a joint development of a number of USA agencies and universities (http://wrf-model.org). This model was configured and adapted to the territory of Ukraine to run with spatial resolution of 10 km. Currently we routinely produce 72-hours weather forecasts every 6 hours [3].
In order to provide access to hydrometeorological observations over the regions of interest we have deployed Sensor Observation Service implementation on the site of Space Research Institute of NASU-NSAU. We have studied two possible implementations of SOS for particular task of serving temperature sensors data. Implementations under study were:
UMN Mapserver v5 (http://mapserver.gis.umn.edu/)
52North SOS (http://52north.org/)
The best experience received was with 52North SOS server. Its main disadvantage is complex and non optiman relational database scheme. However it was possible to adapt existing database structure to the one, required by 52North using a number of SQL views and synthetic tables.
We have used 52North implementation for building a testbed SOS server providing data of temperature sensors over Ukraine and South Africa regions. The server is available by URL http://web.ikd.kiev.ua:8080/52nsos/sos.
Sensor Web services like SOS, SPS and SAS can benefit from integration with Grid platform like Globus Toolkit [4]. Many Sensor Web features can take advantage of Grid platform services, in particular:
Sensors discovery could be performed through combination of Index Service and Trigger Service;
High-level access to XML description of sensors and services could be provided through queries to Index Service;
Grid platform provides convenient way for implementation of notifications and event triggering using corresponding platform components;
Reliable File Transfer service provides reliable data transfer for large datasets;
Globus Security Infrastructure provides enforcement of data and services access policies in a very flexible way thus allowing implementation of desired security policy.
Authors have developed a testbed SOS Service using Globus Toolkit as a platform. For now, this service works as proxy translating and redirecting user request to usual HTTP SOS server. The current version uses client side libraries for interacting with SOS provided by 52North in their OX-Framework. Next version will include in service implementation of SOS-server functionality.
Grid service implementing SOS provides the interface specified in SOS reference document. The key difference between interfaces of standard and Grid based implementations of SOS lies in encoding of service requests. The standard implementation uses custom serialization for requests and responses and Grid based implementation uses standard SOAP encoding.
This work is supported by ESA CAT-1 project “Wide Area Grid Testbed for Flood Monitoring using Spaceborne SAR and Optical Data” (No. 4181); joint project of INTAS, the Centre National d’Etudes Spatiales (CNES) and the National Space Agency of Ukraine (NSAU), “Data Fusion Grid Infrastructure” (Ref. Nr 06-1000024-9154); joint project of the Science & Technology Center in Ukraine (STCU) and the National Academy of Sciences of Ukraine (NASU), “Grid Technologies for Multi-Source Data Integration” (No. 4928), and the Ministry of Education and Science of Ukraine, “Development of Integrated Remote Sensing Data Processing System using Grid Technologies” (No. M/72-2008).
References
1. Mike Botts, George Percivall, Carl Reed, John Davidson. OGC Sensor Web Enablement: Overview and High Level Architecture (OGC 07-165). http://portal.opengeospatial.org/files/?artifact_id=25562
2.Hluchy L., et al. Collaborative environment for Grid-based flood prediction // Computing and Informatics, Vol. 24, 2005, 1001-1022.
3.Shelestov A., Kravchenko O., Ilin M. Geospatial data visualisation in Grid system on Ukrainian segment of GEOSS/GMES// Proc. of the V-th International Conference “Information Research&Applications”. — Varna (Bulgaria). — June 26-30, 2007. — Vol. 2. — P. 422-428.
4. I. Foster. Globus Toolkit Version 4: Software for Service-Oriented Systems // IFIP International Conference on Network and Parallel Computing, Springer-Verlag LNCS 3779, 2005, pp. 2-13.diction, International Journal “Information Theories and Applications”, 2008, Volume 15, Number 1, P. 76-83.