Scalable Knowledge-based Middleware for Networked Systems
The OntoNet project investigates scalable, knowledge-based middleware supporting content-based addressing and routing in mobile, networked systems. It incorporates and integrates two aspects: Ontological reasoning about system resources and declarative networking within routing components. At the application layer is OntoNet, a knowledge-based framework for representing and reasoning on system elements. Declarative, formal techniques provide service discovery and composition, content-based messaging, and distributed querying using OWL-Net, a subset of the OWL description logic. This work includes development of propagation strategies that are efficient and robust in mobile, networked environments. Network layer support is provided by declarative networks, a rule-based framework for compact, high-level protocol specifications. Declarative networking enables rapid prototyping and verification as well as online adaptation and meta-reasoning. This research will include extension of declarative networking to more readily support highly dynamic mobile wireless systems.
Project Members
Students
- Joseph B. Kopena
- Duc N. Nguyen
Faculty:
- Boon Thau Loo, University of Pennsylvania
- William C. Regli, Drexel University
Publications
- Ontologies for Distributed Command and Control Messaging. [PDF]
Duc N. Nguyen, Joseph B. Kopena, Boon Thau Loo, and William C. Regli.
6th International Conference on Formal Ontology in Information Systems (FOIS), May 2010. (39% acceptance) - Message Models and Aggregation in Knowledge Based Middleware for
Rich Sensor Systems.
[Paper]
Joseph B. Kopena, William C. Regli, and Boon Thau Loo.
6th International Workshop on Data Management for Sensor Networks (DMSN), in conjunction with VLDB, Lyon, France, Aug 2009. - OntoNet: Scalable Knowledge-Based Networking. [Paper] [Talk]
Joseph B. Kopena and Boon Thau Loo.
4th International Workshop on Networking meets Databases (NetDB), in conjunction with ICDE, Cancun, Mexico, Apr 2008.
Acknowledgments
This work is partially sponsored by NSF CCF-0820208. Any opinions, findings, and conclusions or recommendations expressed in this material are those of the author(s) and do not necessarily reflect the views of the National Science Foundation.