Habitat Monitoring: Application Driver for Wireless Communications Technology∗

Habitat Monitoring: Application Driver for Wireless Communications Technology∗ Alberto Cerpa, Jeremy Elson, Michael Hamilton Jerry Zhao † James San Jacinto Mountains Reserve USC Information Sciences Institute Deborah Estrin , Lewis Girod Box 1775 4676 Admiralty Way UCLA Computer Science Department Idyllwild, California 92549 Marina del Rey, California 90292 Los Angeles, California 90095-1596 [email protected] [email protected] {cerpa,jelson,destrin,girod}@ lecs.cs.ucla.edu ABSTRACT micro-sensors and low-power wireless communications will en- As new fabrication and integration technologies reduce the cost able the deployment of densely distributed sensor/actuator net- and size of micro-sensors and wireless interfaces, it becomes works for a wide range of biological, earth and environmental feasible to deploy densely distributed wireless networks of sen- monitoring applications in marine, soil, and atmospheric con- sors and actuators. These systems promise to revolutionize bio- texts. This technology has particular relevance in many Latin logical, earth, and environmental monitoring applications, pro- American countries because of its applicability to environmental viding data at granularities unrealizable by other means. In monitoring of the diverse and unique ecosystems. addition to the challenges of miniaturization, new system ar- chitectures and new network algorithms must be developed to To achieve scalability, robustness, and long-lived operation, sen- transform the vast quantity of raw sensor data into a manage- sor nodes themselves will execute significant signal processing, able stream of high-level data. To address this, we propose a correlation, and network self-configuration inside the network. tiered system architecture in which data collected at numerous, In this way these systems will emerge as the largest distributed inexpensive sensor nodes is filtered by local processing on its systems ever deployed. These requirements raise fascinating way through to larger, more capable and more expensive nodes. challenges for Information Technology and communication research, as well as for their application domains. One of the novel We briefly describe Habitat monitoring as our motivating appli- issues for network design is the shift from manipulation and cation and introduce initial system building blocks designed to presentation of symbolic and numeric data to the interaction support this application. The remainder of the paper presents with the dynamic physical world through sensors and actuators. details of our experimental platform. This raises the need for good physical models, which requires extensive data analysis of monitored data. A second challenge Keywords: low-power wireless, sensor networks, testbeds, ap- arises from the greatly increased level of environmental dynam- plications ics. While all good distributed systems are designed with re- liability in mind, these new target applications present a level of ongoing dynamics that far exceeds the norm. Perhaps the 1. INTRODUCTION most pervasive technical challenge arises from the energy con- During the last decade, networking technologies have revolu- straints imposed by unattended systems. These systems must tionized the ways individuals and organizations exchange infor- be long-lived and vigilant and operate unattended. Unlike tra- mation and coordinate their activities. In this decade we will ditional Internet systems the energy constraints on un-tethered witness another revolution; this time one that involves obser- nodes present enormous design challenges. Finally, as with the vation and control of the physical world. The availability of Internet, there are scaling challenges. However, given the other ∗ characteristics of the problem space, the traditional techniques To appear in the Proceedings of the First ACM SIGCOMM are not directly applicable, and alternative techniques must be Workshop on Data Communications in Latin America and the Caribbean, 3-5 April, 2001, San Jose, Costa Rica. Also pub- developed. lished as UCLA Computer Science Technical Report 200023, December 2000. This paper focuses on a particular application of embedded †Correspondence author. wireless sensing technology. The habitat sensing array for biocomplexity mapping emphasizes the need for continual auto- matic self-configuration of the network to adapt to environmental dynamics, and the use of coordinated actuation in the form of programmed triggering of sensing and actuation to enable identification, recording and analysis of interesting events. We introduce the key architectural principle for constructing long-lived wireless sensor networks, adaptive self-configuration, and then describe its applicability to Habitat monitoring. In the subsequent section we describe our tiered architecture, time 3. HABITAT SENSING ARRAY FOR synchronization techniques, and experimental platform devel- BIOCOMPLEXITY MAPPING oped to support this and other applications. The challenge of understanding biocomplexity in the environ- ment requires sophisticated and creative approaches that inte- 2. ADAPTIVE SELF-CONFIGURING grate information across temporal and spatial scales, consider SYSTEMS multiple levels of organization and cross-conceptual boundaries The sheer number of distributed elements in these systems pre- [Walker-Steffen97, Gell-Mann95]. Long-term data-collection for cludes dependence on manual configuration. Furthermore, the systematic and ecological field studies and continuous environ- environmental dynamics to which these elements must adapt mental monitoring are the domain of Biological Field Stations, prevents design-time pre-configuration of these systems. Thus, and offer opportunities to establish cross-cutting and integrated realistic deployments of these unattended networks must self- investigations that facilitate studies of biocomplexity [Michener- reconfigure in response to node failure or incremental addition of et.al.98, Lohr-et.al.95]. Over the past two decades we have seen nodes, and must adapt to changing environmental conditions. If extraordinary developments in the field of remote sensing and we are to exploit the power of densely distributed sensing, these automated data collection, resulting in dramatic increases in techniques for adaptation and self-configuration must scale to spatial, spectral and temporal resolution at a geometrically de- the anticipated sizes of these deployments. In recent years, clining cost per unit area [Colwell98]. Multi-purpose data anal- some work has begun to allow networks of wireless nodes to dis- ysis and visualization software provides tools to study large and cover their neighbors, acquire synchronism, and form efficient complex data sets. The Internet facilitates global data access, routes [Pottie-Kaiser00]. However, this nascent research has distributed data processing, collaborative studies, virtual prox- not yet addressed many fundamental issues in adaptively self- imity and tele-robotic operation. configuring the more complex sensing and actuation systems described here, particularly those arising from deploying embed- Remote sensing from satellite and airborne sensors has proved ded systems in real-world, environmentally-challenging contexts to be a tremendous tool for studying “large” biodiversity (e.g. [Estrin-et.al.99] spatial complexity of dominant plant species). While many sci- entists and land managers attempt to study biodiversity using Driven by our experimental domains, we are using this experi- top down remote sensing tools, the fact is that the vast ma- mental platform to develop techniques for self-configuration: jority of the biodiversity, and resulting biocomplexity, within an ecosystem exists at very small scales, and is not readily ob- servable with even the best airborne and satellite based sensors • Integrated techniques for self-assembly and self-healing in [Keitt-Milne97]. To get down to where the complexity is, so to these deeply distributed systems. These methods should speak, sensing and monitoring needs to become ground based enable self-configuration—both at the lower-level commu- [Hamilton92, Hamilton00]. Breakthroughs in VLSI digital sig- nication layers in addition to higher levels such as dis- nal processing, miniature sensors, low-power micro-controllers tributed name spaces. and wireless digital networks will make possible the develop- ment of cheap and nearly ubiquitous ground-based monitoring • Simple localized algorithms that effect coordinated data systems for outdoor field. Fresh opportunities afforded by these collection and processing to achieve measurement aggrega- technologies allow us to rethink how Biological Field Stations tion or higher-level alert generation [Abelson99]. Prelimi- can participate in the global effort to answer the big questions nary research indicates that a particular paradigm for net- posed by biocomplexity. work organization, directed diffusion [Intanago-et.al.00], can efficiently achieve such coordination and resource allo- Observation techniques involving cameras and microphones are cation needs, but considerable experimentation and mod- in increasingly widespread use, however they involve small num- eling work is still required. bers of devices and require continuous human observation, greatly constraining their capabilities in natural environments. Unat- • Protocol and system level techniques that enable energy- tended, heterogeneous sensors/actuators will enable a vast range efficiency beyond what is feasible with low-power compo- of new habitat studies via continuous monitoring

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