Robert Szewczyk

Wireless sensor networks for habitat monitoring

We provide an in-depth study of applying wireless sensor networks to real-world habitat monitoring. A set of system design requirements are developed that cover the hardware design of the nodes, the design of the sensor network, and the capabilities for remote data access and management. A system architecture is proposed to address these requirements for habitat monitoring in general, and an instance of the architecture for monitoring seabird nesting environment and behavior is presented. The currently deployed network consists of 32 nodes on a small island off the coast of Maine streaming useful live data onto the web. The application-driven design exercise serves to identify important areas of further work in data sampling, communications, network retasking, and health monitoring.

System architecture directions for networked sensors

Technological progress in integrated, low-power, CMOS communication devices and sensors makes a rich design space of networked sensors viable. They can be deeply embedded in the physical world and spread throughout our environment like smart dust. The missing elements are an overall system architecture and a methodology for systematic advance. To this end, we identify key requirements, develop a small device that is representative of the class, design a tiny event-driven operating system, and show that it provides support for efficient modularity and concurrency-intensive operation. Our operating system fits in 178 bytes of memory, propagates events in the time it takes to copy 1.25 bytes of memory, context switches in the time it takes to copy 6 bytes of memory and supports two level scheduling. The analysis lays a groundwork for future architectural advances.

SPINS: security protocols for sensor networks

Wireless sensor networks will be widely deployed in the near future. While much research has focused on making these networks feasible and useful, security has received little attention. We present a suite of security protocols optimized for sensor networks: SPINS. SPINS has two secure building blocks: SNEP and μTESLA. SNEP includes: data confidentiality, two-party data authentication, and evidence of data freshness. μTESLA provides authenticated broadcast for severely resource-constrained environments. We implemented the above protocols, and show that they are practical even on minimal hardware: the performance of the protocol suite easily matches the data rate of our network. Additionally, we demonstrate that the suite can be used for building higher level protocols.

TinyOS: An Operating System for Sensor Networks

We present TinyOS, a flexible, application-specific operating system for sensor networks, which form a core component of ambient intelligence systems. Sensor networks consist of (potentially) thousands of tiny, low-power nodes, each of which execute concurrent, reactive programs that must operate with severe memory and power constraints. The sensor network challenges of limited resources, event-centric concurrent applications, and low-power operation drive the design of TinyOS. Our solution combines flexible, fine-grain components with an execution model that supports complex yet safe concurrent operations. TinyOS meets these challenges well and has become the platform of choice for sensor network research; it is in use by over a hundred groups worldwide, and supports a broad range of applications and research topics. We provide a qualitative and quantitative evaluation of the system, showing that it supports complex, concurrent programs with very low memory requirements (many applications fit within 16KB of memory, and the core OS is 400 bytes) and efficient, low-power operation.We present our experiences with TinyOS as a platform for sensor network innovation and applications.

An analysis of a large scale habitat monitoring application

Habitat and environmental monitoring is a driving application for wireless sensor networks. We present an analysis of data from a second generation sensor networks deployed during the summer and autumn of 2003. During a 4 month deployment, these networks, consisting of 150 devices, produced unique datasets for both systems and biological analysis. This paper focuses on nodal and network performance, with an emphasis on lifetime, reliability, and the the static and dynamic aspects of single and multi-hop networks. We compare the results collected to expectations set during the design phase: we were able to accurately predict lifetime of the single-hop network, but we underestimated the impact of multi-hop traffic overhearing and the nuances of power source selection. While initial packet loss data was commensurate with lab experiments, over the duration of the deployment, reliability of the backend infrastructure and the transit network had a dominant impact on overall network performance. Finally, we evaluate the physical design of the sensor node based on deployment experience and a <i>post mortem</i> analysis. The results shed light on a number of design issues from network deployment, through selection of power sources to optimizations of routing decisions.

Habitat monitoring with sensor networks

These networks deliver to ecologists data on localized environmental conditions at the scale of individual organisms to help settle large-scale land-use issues affecting animals, plants, and people.

Supporting aggregate queries over ad-hoc wireless sensor networks

We show how the database communitys notion of a generic query interface for data aggregation can be applied to ad-hoc networks of sensor devices. As has been noted in the sensor network literature, aggregation is important as a data reduction tool; networking approaches, however, have focused on application specific solutions, whereas our in-network aggregation approach is driven by a general purpose, SQL-style interface that can execute queries over any type of sensor data while providing opportunities for significant optimization. We present a variety of techniques to improve the reliability and performance of our solution. We also show how grouped aggregates can be efficiently computed and offer a comparison to related systems and database projects.

Lessons from a Sensor Network Expedition

Habitat monitoring is an important driving application for wireless sensor networks (WSNs). Although researchers anticipate some challenges arising in the real-world deployments of sensor networks, a number of problems can be discovered only through experience. This paper evaluates a sensor network system described in an earlier work and presents a set of experiences from a four month long deployment on a remote island off the coast of Maine. We present an in-depth analysis of the environmental and node health data. The close integration of WSNs with their environment provides biological data at densities previous impossible; however, we show that the sensor data is also useful for predicting system operation and network failures. Based on over one million data and health readings, we analyze the node and network design and develop network reliability profiles and failure models.

Analysis of wireless sensor networks for habitat monitoring

We provide an in-depth study of applying wireless sensor networks (WSNs) to real-world habitat monitoring. A set of system design requirements were developed that cover the hardware design of the nodes, the sensor network software, protective enclosures, and system architecture to meet the requirements of biologists. In the summer of 2002, 43 nodes were deployed on a small island off the coast of Maine streaming useful live data onto the web. Although researchers anticipate some challenges arising in real-world deployments of WSNs, many problems can only be discovered through experience. We present a set of experiences from a four month long deployment on a remote island. We analyze the environmental and node health data to evaluate system performance. The close integration of WSNs with their environment provides environmental data at densities previously impossible. We show that the sensor data is also useful for predicting system operation and network failures. Based on over one million data readings, we analyze the node and network design and develop network reliability profiles and failure models.

A Network-Centric Approach to Embedded Software for Tiny Devices

The ability to incorporate low-power, wireless communication into embedded devices gives rise to a newgenre of embedded software that is distributed, dynamic, and adaptive. This paper describes the network-centric approach to designing software for highly constrained devices embodied in TinyOS. It develops a tiny Active Message communication model and shows how it is used to build non-blocking applications and higher level networking capabilities, such as multihop ad hoc routing. It shows how the TinyOS event-driven approach is used to tackle challenges in implementing the communication model with very limited storage and the radio channel modulated directly in software in an energy efficient manner. The open, component-based design allows many novel relationships between system and application.