Proceeedings of the 1st international workshop on Data management for sensor networks: in conjunction with VLDB 2004

The past few years have seen substantial amounts of computer science research on sensor networks. Other subfields have had a number of workshops on the topic (e.g., the Workshop on Wireless Sensor Networks and Applications (WSNA) in 2002 and 2003 and the Sensor Networks Protocols and Applications (SNPA) Workshop in 2002 and 2003, both of which are systems/networking focused). Furthermore, there are now at least two major conferences -- the Conference on Information Processing in Sensor Networks (IPSN), started in 2002, and the ACM Conference on Sensor Systems (SenSys), started in 2003. These conferences have published a small number of database papers, but there is no forum for discussion on early and innovative work on data management in sensor networks.We believe that the Workshop on Data Management for Sensor Networks (DMSN'04) fills a significant gap in the database community by bringing interested researchers together to identify research challenges and opportunities. Specifically, the workshop focuses on data processing and management in networks of remote, wireless, battery-powered sensing devices (sensor networks). The power-constrained, lossy, noisy, distributed, and remote nature of such networks means that traditional data management techniques often cannot be applied without significant re-tooling. Furthermore, new challenges associated with acquisition and processing of live sensor data mean that completely new database techniques must also be developed.The workshop represents a wide range of topics, including: data replication and consistency in noisy and lossy environments, database languages for sensor tasking, distributed data storage and indexing, energyefficient data acquisition and dissemination, in-network query processing, integration of sensor network data into traditional and streaming data management systems, networking support for data processing, techniques for managing loss, uncertainty, and noise, query optimization, and privacy protection for sensory data.As a response to the Call for Papers, the DMSN'04 workshop received 38 abstracts, of which 25 materialized as full papers by the submission deadline. During the review process, each paper was reviewed by at least three PC members or external reviewers, resulting in the acceptance of 15 papers.