Preprocessing in a Tiered Sensor Network for Habitat Monitoring
- PDF / 2,050,103 Bytes
- 10 Pages / 600 x 792 pts Page_size
- 89 Downloads / 165 Views
Preprocessing in a Tiered Sensor Network for Habitat Monitoring Hanbiao Wang Computer Science Department, University of California, Los Angeles (UCLA), Los Angeles, CA 90095-1596, USA Email: [email protected]
Deborah Estrin Computer Science Department, University of California, Los Angeles (UCLA), Los Angeles, CA 90095-1596, USA Email: [email protected]
Lewis Girod Computer Science Department, University of California, Los Angeles (UCLA), Los Angeles, CA 90095-1596, USA Email: [email protected] Received 1 February 2002 and in revised form 6 October 2002 We investigate task decomposition and collaboration in a two-tiered sensor network for habitat monitoring. The system recognizes and localizes a specified type of birdcalls. The system has a few powerful macronodes in the first tier, and many less powerful micronodes in the second tier. Each macronode combines data collected by multiple micronodes for target classification and localization. We describe two types of lightweight preprocessing which significantly reduce data transmission from micronodes to macronodes. Micronodes classify events according to their cross-zero rates and discard irrelevant events. Data about events of interest is reduced and compressed before being transmitted to macronodes for target localization. Preliminary experiments illustrate the effectiveness of event filtering and data reduction at micronodes. Keywords and phrases: sensor network, collaborative signal processing, tiered architecture, classification, data reduction, data compression.
1. INTRODUCTION Recent advances in wireless network, low-power circuit design, and micro electromechanical systems (MEMS) will enable pervasive sensing and will revolutionize the way in which we understand the physical world [1]. Extensive work has been done to address many aspects of wireless sensor network design, including low-power schemes [2, 3, 4], selfconfiguration [5], localization [6, 7, 8, 9, 10, 11], time synchronization [12, 13], data dissemination [14, 15, 16], and query processing [17]. This paper builds upon earlier work to address task decomposition and collaboration among nodes. Although hardware for sensor network nodes will become smaller, cheaper, more powerful, and more energyefficient, technological advances will never obviate the need to make trade-offs. Cerpa et al [18]. described a tiered hardware platform for habitat monitoring applications. Smaller, less capable nodes are used to exploit spatial diversity, while more powerful nodes combine and process the micronode sensing data.
Although details of task decomposition and collaboration clearly depend on the specific characteristics of applications, we hope to identify some common principles that can be applied to tiered sensor networks across various applications. We use birdcall recognition and localization as a case study of task decomposition and collaboration. In this context, we demonstrate two types of micronode preprocessing. Distributed detection algorithms and beamforming algorithms will not be discussed in detail in
Data Loading...
