Collaborative Storage Management In Sensor Networks

In this paper, we consider a class of sensor networks where the data is not required in real-time by an observer; for example, a sensor network monitoring a scientific phenomenon for later play back and analysis. In such networks, the data must be stored in the network. Thus, in addition to battery power, storage is a primary resource: the useful lifetime of the network is constrained by its ability to store the generated data samples. We explore the use of collaborative storage technique to efficiently manage data in storage constrained sensor networks. The proposed collaborative storage technique takes advantage of spatial correlation among the data collected by nearby sensors to significantly reduce the size of the data near the data sources. We show that the proposed approach provides significant savings in the size of the stored data vs. local buffering, allowing the network to run for a longer time without running out of storage space and reducing the amount of data that will eventually be relayed to the observer. In addition, collaborative storage performs load balancing of the available storage space if data generation rates are not uniform across sensors (as would be the case in an event driven sensor network), or if the available storage varies across the network.Comment: 13 pages, 7 figure

A File System Abstraction for Sense and Respond Systems

The heterogeneity and resource constraints of sense-and-respond systems pose significant challenges to system and application development. In this paper, we present a flexible, intuitive file system abstraction for organizing and managing sense-and-respond systems based on the Plan 9 design principles. A key feature of this abstraction is the ability to support multiple views of the system via filesystem namespaces. Constructed logical views present an application-specific representation of the network, thus enabling high-level programming of the network. Concurrently, structural views of the network enable resource-efficient planning and execution of tasks. We present and motivate the design using several examples, outline research challenges and our research plan to address them, and describe the current state of implementation.Comment: 6 pages, 3 figures Workshop on End-to-End, Sense-and-Respond Systems, Applications, and Services In conjunction with MobiSys '0

Monitoring wild animal communities with arrays of motion sensitive camera traps

Studying animal movement and distribution is of critical importance to addressing environmental challenges including invasive species, infectious diseases, climate and land-use change. Motion sensitive camera traps offer a visual sensor to record the presence of a broad range of species providing location -specific information on movement and behavior. Modern digital camera traps that record video present new analytical opportunities, but also new data management challenges. This paper describes our experience with a terrestrial animal monitoring system at Barro Colorado Island, Panama. Our camera network captured the spatio-temporal dynamics of terrestrial bird and mammal activity at the site - data relevant to immediate science questions, and long-term conservation issues. We believe that the experience gained and lessons learned during our year long deployment and testing of the camera traps as well as the developed solutions are applicable to broader sensor network applications and are valuable for the advancement of the sensor network research. We suggest that the continued development of these hardware, software, and analytical tools, in concert, offer an exciting sensor-network solution to monitoring of animal populations which could realistically scale over larger areas and time spans

Towards A Holistic Approach for Protocol Development in Sensor Networks BY

Technological advances in VLSI, MEMS, and wireless communication have ushered in a new age of miniature, low cost, low-energy, micro-sensors. Networks of such devices, called Wireless Sensor Networks (WSNs), hold the promise of revolutionizing sensing across a range of civil, scientific, military and industrial applications. The potentially high impact of this technology and the complex challenges posed by it have spurred intense interest in the research, military and commercial communities. However, sensors often have limited energy, computational ability, and storage capacity. Therefore protocols that manage the different aspects of the sensors ’ operation in terms of collecting and processing data, as well as support services such as localization and synchronization have to be developed and must work efficiently within the constraints of the limited available resources — this is an extremely challenging task. The first contributions of my research are in developing application-specific, light-weight, energy efficient protocols for various critical sensor subsystems and services including: information dissemination, storage management, and localization. Based on the experiences with these diverse applications, subsystems and services, we represent the basic sensor network design goal a