Message from the DMSN 2007 Organizing Committee

Sensor networks enable an unprecedented level of access to the physical world, and hold tremendous potential to revolutionize many application domains. Research on sensor networks spans many areas of computer science, and there are now major conferences, e.g., IPSN and SenSys, devoted to sensor networks. However, there is no exclusive forum for discussion on early and innovative work on data management in sensor networks. The International Workshop on Data Management for Sensor Networks (DMSN), inaugurated in 2004, aims to fill this significant gap in the database and sensor network communities. Building on the successes of the three previous DMSN workshops (2004–6), DMSN 2007 brings together researchers working on all aspects of sensor data management: from data processing in networks of remote, wireless, resource-constrained sensors to managing heterogeneous, noisy, and sometimes sensitive sensor data in databases. The resource-constrained, lossy, noisy, distributed, and remote nature of sensor networks means that traditional database techniques often cannot be applied without significant re-tooling. Challenges associated with acquiring and processing large-scale, heterogeneous sets of live sensor data also call for novel data management techniques. Finally, in many applications, collecting sensor data raises important privacy and security concerns that require new protection and anonymization techniques. As the field of sensor networks continues to develop, we have expanded the scope of DMSN 2007 from previous workshops in the series, by encouraging contributions on a broader sets of topics, including: database languages for sensor tasking; distributed sensor data storage and indexing; data replication and consistency in noisy and lossy environments; energy-efficient data acquisition and dissemination; in-network query processing; networking support for data processing; query optimization and deployment planning in sensor networks; database techniques for managing loss, uncertainty, noise, and ambiguity; model-based sensor data processing; challenges and techniques for new types of sensor data, e.g., RFID, images and videos, data from scientific and medical instruments ; personal, ubiquitous applications of sensor-based infrastructures; integration of sensor data of different modalities and from different sources; integration of sensor data in traditional databases and streaming systems; techniques for secure sensor data collection and processing; and privacy protection techniques for sensor data. As a response to the Call for Papers this year, we received 15 full paper submissions. During the review process, each paper was reviewed by three or four members of the program committee or external reviewers and was also carefully discussed, resulting in the acceptance of 7 papers. We would like to …