Great Innovative Ideas are a way to showcase the exciting new research and ideas generated by the computing community.
The following Great Innovative Idea is from Tamraparni Dasu, Yaron Kanza, and Divesh Srivastava, from AT&T Labs-Research. They were one of the Blue Sky Award winners at the ACM SIGSPATIAL 2017 conference for their paper, Geotagging IP Packets for Location-Aware Software-Defined Networking in the Presence of Virtual Network Functions.
When routing IP packets on the Internet, the geographic location of routers and switches can be taken into account and utilized, to improve security and support applications such as copyright protection, location-based services, etc. Our main idea is to add to IP packets geotags with spatio-temporal information about the traveled route, e.g., the geographic location of the source. We suggest to use packet encapsulation to add geotags without interfering with the content of packets. We also suggest to use hashed locations, to reduce the size of tags, and to support cryptographically-signed geotags for applications in which there is a risk that geotags would be spoofed.
To cope with the rigidness of traditional routing technology, we propose the use of software-defined networking (SDN) and network function virtualization (NFV) as technologies that would facilitate geotagging and would add flexibility to it. Geotagging applications would be deployed as virtual network functions, and the control over the routing, which SDN provides, would be used to route packets via appropriate virtual network functions, for adding, removing or using geotags. This will create a synergy between networking and spatio-temporal technologies, to improve both the network management and location-based services.
Adding geotags to IP packets has the potential to define new types of applications that combine networking technologies with spatio-temporal algorithms and systems, and it may also strengthen existing networking capabilities. It can be used for geofencing or geoblocking, to restrict network flows or the delivery of content to specific areas, e.g., for protecting sensitive data transfer, for copyright protection, etc. Geotagged IP packets could provide useful information about the interrelationships between geographic locations, times and anomalies in network traffic, to understand better the dynamics of large-scale networks and improve them. For location-based services, reliable knowledge of the origin of requests could simplify and improve the service, e.g., by providing service to devices in which the GPS receiver is disabled. Clearly, privacy restrictions should still be maintained.
The ability to take into account spatio-temporal information when routing IP packets may be used to design new types of routing, e.g., adding geospatial restrictions for security, but also for learning about network usages and about connections between people, e.g., finding correlations between connections in the cyberspace and real-world geographic connections. This may introduce research questions in economy, social sciences, demography, etc. It may also require developing appropriate tools to cope with geotagging and the spatial analysis of high-volume flows of packets.
We conduct research in various areas, including data management, data quality, database systems, statistics, privacy, spatial databases, networking, and more.
Tamraparni Dasu is a subject matter expert in data quality, stream mining, and statistics. Yaron Kanza is a subject matter expert in spatial databases, spatial applications, graph databases, data integration, and management of data on the World-Wide Web. Divesh Srivastava is a subject matter expert in data management, database systems, data integration, data quality, data privacy, data streams and more.
Tamraparni Dasu is a member of the Database Research Department at AT&T Labs-Research. She received her Ph.D. from the University of Rochester, with a Masters in Mathematics from Indian Institute of Technology, New Delhi. She has co-authored the first technical book on data quality, “Exploratory Data Mining and Data Cleaning, John Wiley & Sons, 2003.” She is an associate editor of the ACM Transactions on Data and Information Quality. Her research interests include nonparametric statistics, data mining and statistical approaches to data streams and data quality. She is also interested in literary translation and writing fiction.
Yaron Kanza is a member of the Database Research Department at AT&T Labs-Research. He received his Ph.D. from the Hebrew University of Jerusalem. After completing his Ph.D. he was a postdoctoral fellow at the University of Toronto. Before joining AT&T he was a faculty member at the Technion – Israel Institute of Technology, and for two years he was a visiting assistant professor at Cornell Tech. He is an associate editor of the ACM Transactions on Spatial Applications and Systems.
Divesh Srivastava is the head of the Database Research Department at AT&T Labs-Research. He received his Ph.D. from the University of Wisconsin, Madison, and his B.Tech from the Indian Institute of Technology, Bombay. He is a Fellow of the ACM, the Vice President of the VLDB Endowment, and the managing editor of the Proceedings of the VLDB Endowment. He has presented keynote talks at several conferences. His research interests and publications span a variety of topics in data management.