2006 Proceeding- General Chairs:
- Alexandros Labrinidis,
- Samuel R. Madden
The past few years have seen substantial amounts of computer science research on sensor networks as they have the potential to bring an unprecedented level of access to the physical world. Other subfields of Computer Science have had a number of workshops on the topic. Also, there are now at least two major conferences --- the Conference on Information Processing in Sensor Networks (IPSN), started in 2002 (the 2006 IPSN was held in April), and the ACM Conference on Sensor Systems (SenSys), started in 2003 (the 2006 SenSys will be held in November). These conferences have published a small number of database papers, but there is no exclusive forum for discussion on early and innovative work on data management in sensor networks.
We believe that the DMSN 2006 workshop, building on the successes of the DMSN 2004 and DMSN 2005 workshops, fills a significant gap in the database and sensor network communities, by bringing together interested researchers and practitioners from different fields to identify interesting challenges and opportunities. Specifically, the workshop focuses on the challenges of 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 DMSN workshop encompasses a wide range of topics which include: data replication and consistency in sensor network environments, database languages for sensor tasking, distributed data storage and indexing, energy-efficient 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.
Proceeding Downloads
Processing proximity queries in sensor networks
Sensor networks are often used to perform monitoring tasks, such as in animal or vehicle tracking and in surveillance of enemy forces in military applications. In this paper we introduce the concept of proximity queries that allow us to report ...
Impact of multi-query optimization in sensor networks
In this paper, we study the problem of processing multiple queries in a wireless sensor network. We focus on multi-query optimization at the base station level to minimize the number of radio messages in the sensor network. We adopt a cost-based ...
MeT: a real world oriented metadata management system for semantic sensor networks
A semantic sensor network describes the physical world using the metadata obtained from a sensor network. In this paper, we present our design and implementation of MeT, a real world oriented metadata management system for semantic sensor networks. MeT ...
Network scheduling for data archiving applications in sensor networks
Since data archiving in sensor networks is a communication intensive application, a careful power management of communication is of critical importance for such networks. An example is FPS, an adaptive power scheduling algorithm that combines slotted ...
Transactional issues in sensor data management
This paper presents a novel research direction in the field of sensor data management. It concerns transactional support in heterogeneous large scale sensor systems. Besides well-known continuous queries on sensor data, system management queries should ...
Efficient handling of sensor failures
Sensors provide unprecedented access to a wealth of information from the physical environment in real-time. However, they suffer from a variety of resource limitations, most importantly power consumption and communication bandwidth. Additionally, ...
Quality of service in stateful information filters
Information Filters play an important role in processing streams of events, both for filtering as well as routing events based on their content. Stateful information filters like AGILE [15], Cayuga [13] and SASE [24] have gained a significant amount of ...
Intelligent system monitoring on large clusters
Modern data centers have a large number of components that must be monitored, including servers, switches/routers, and environmental control systems. This paper describes InteMon, a prototype monitoring and mining system for data centers. It uses the ...
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Acceptance Rates
| Year | Submitted | Accepted | Rate |
|---|---|---|---|
| DMSN '09 | 16 | 6 | 38% |
| Overall | 16 | 6 | 38% |