Jeremy Elson

Fine-grained network time synchronization using reference broadcasts

Recent advances in miniaturization and low-cost, low-power design have led to active research in large-scale networks of small, wireless, low-power sensors and actuators. Time synchronization is critical in sensor networks for diverse purposes including sensor data fusion, coordinated actuation, and power-efficient duty cycling. Though the clock accuracy and precision requirements are often stricter than in traditional distributed systems, strict energy constraints limit the resources available to meet these goals.We present Reference-Broadcast Synchronization, a scheme in which nodes send reference beacons to their neighbors using physical-layer broadcasts. A reference broadcast does not contain an explicit timestamp; instead, receivers use its arrival time as a point of reference for comparing their clocks. In this paper, we use measurements from two wireless implementations to show that removing the senders nondeterminism from the critical path in this way produces high-precision clock agreement (1.85 ± 1.28μsec, using off-the-shelf 802.11 wireless Ethernet), while using minimal energy. We also describe a novel algorithm that uses this same broadcast property to federate clocks across broadcast domains with a slow decay in precision (3.68 ± 2.57μsec after 4 hops). RBS can be used without external references, forming a precise relative timescale, or can maintain microsecond-level synchronization to an external timescale such as UTC. We show a significant improvement over the Network Time Protocol (NTP) under similar conditions.

Habitat monitoring: application driver for wireless communications technology

As new fabrication and integration technologies reduce the cost and size of micro-sensors and wireless interfaces, it becomes feasible to deploy densely distributed wireless networks of sensors and actuators. These systems promise to revolutionize biological, earth, and environmental monitoring applications, providing data at granularities unrealizable by other means. In addition to the challenges of miniaturization, new system architectures and new network algorithms must be developed to transform the vast quantity of raw sensor data into a manageable stream of high-level data. To address this, we propose a tiered system architecture in which data collected at numerous, inexpensive sensor nodes is filtered by local processing on its way through to larger, more capable and more expensive nodes.We briefly describe Habitat monitoring as our motivating application and introduce initial system building blocks designed to support this application. The remainder of the paper presents details of our experimental platform.

Wireless sensor networks: a new regime for time synchronization

Wireless sensor networks (WSNs) consist of large populations of wirelessly connected nodes, capable of computation, communication, and sensing. Sensor nodes cooperate in order to merge individual sensor readings into a high-level sensing result, such as integrating a time series of position measurements into a velocity estimate. The physical time of sensor readings is a key element in this process called data fusion. Hence, time synchronization is a crucial component of WSNs. We argue that time synchronization schemes developed for traditional networks such as NTP [23] are ill-suited for WSNs and suggest more appropriate approaches.

Time synchronization for wireless sensor networks

Recent advances in miniaturization and low-cost, low-power design have led to active research in large-scale networks of small, wireless, low-power sensors and actuators. Time synchronization is a critical piece of infrastructure in any distributed system, but wireless sensor networks make particularly extensive use of synchronized time. Almost any form of sensor data fusion or coordinated actuation requires synchronized physical time for reasoning about events in the physical world. However, while the clock accuracy and precision requirements are often stricter in sensor networks than in traditional distributed systems, energy and channel constraints limit the resources available to meet these goals. nNew approaches to time synchronization can better support the broad range of application requirements seen in sensor networks, while meeting the unique resource constraints found in such systems. We first describe the design principles we have found useful in this problem space: tiered and multi-modal architectures are a better fit than a single solution forced to solve all problems; tunable methods allow synchronization to be more finely tailored to problem at hand; peer-to-peer synchronization eliminates the problems associated with maintaining a global timescale. We propose a new service model for time synchronization that provides a much more natural expression of these techniques: explicit timestamp conversions . nWe describe the implementation and characterization of several synchronization methods that exemplify our design principles. Reference-Broadcast Synchronization achieves high precision at low energy cost by leveraging the broadcast property inherent to wireless communication. A novel multi-hop algorithm allows RBS timescales to be federated across broadcast domains. Post-Facto Synchronization can make systems significantly more efficient by relaxing the traditional constraint that clocks must be kept in continuous synchrony. nFinally, we describe our experience in applying our new methods to the implementation of a number of research and commercial sensor network applications.

Locating tiny sensors in time and space: a case study

As the cost of embedded sensors and actuators drops, new applications will arise that exploit high density networks of small devices capable of a variety of sensing tasks. Although individual devices may have limited functionality, the true value of the system comes from the emergent behavior that arises when data from many places in the system is combined. This type of data fusion has a number of requirements, but two of the most important are: 1) synchronized time, precise enough to resolve movement in the sensed phenomenon (e.g., sound); and 2) known geographic locations, on a similar scale to the sensors size and deployment density. However, the installation cost of a localization system with sufficient granularity is considerable, because of the large amount of effort required to deploy such a system and make all the measurements required to tune it. In this paper, we describe a system based on COTS components that incorporates our novel time synchronization and acoustic ranging techniques. The result is a low-cost, readily available platform for distributed, coherent signal processing.

A system for simulation, emulation, and deployment of heterogeneous sensor networks

Recently deployed Wireless Sensor Network systems (WSNs) are increasingly following <i>heterogeneous</i> designs, incorporating a mixture of elements with widely varying capabilities. The development and deployment of WSNs rides heavily on the availability of simulation, emulation, visualization and analysis support. In this work, we develop tools specifically to support <i>heterogeneous</i> systems, as well as to support the measurement and visualization of <i>operational</i> systems that is critical to addressing the inevitable problems that crop up in deployment. Our system differs from related systems in three key ways: in its ability to simulate and emulate <i>heterogeneous</i> systems in their entirety, in its extensive support for integration and interoperability between motes and microservers, and in its unified set of tools that capture, view, and analyze real time debugging information from simulations, emulations, and deployments.

Coherent acoustic array processing and localization on wireless sensor networks

Advances in microelectronics, array processing, and wireless networking have motivated the analysis and design of low-cost integrated sensing, computing, and communicating nodes capable of performing various demanding collaborative space–time processing tasks. In this paper, we consider the problem of coherent acoustic sensor array processing and localization on distributed wireless sensor networks. We first introduce some basic concepts of beamforming and localization for wide-band acoustic sources. A review of various known localization algorithms based on time-delay followed by least-squares estimations as well as the maximum–likelihood method is given. Issues related to practical implementation of coherent array processing, including the need for fine-grain time synchronization, are discussed. Then we describe the implementation of a Linux-based wireless networked acoustic sensor array testbed, utilizing commercially available iPAQs with built-in microphones, codecs, and microprocessors, plus wireless Ethernet cards, to perform acoustic source localization. Various field-measured results using two localization algorithms show the effectiveness of the proposed testbed. An extensive list of references related to this work is also included.

Target classification and localization in habitat monitoring

We are developing an acoustic habitat-monitoring sensor network that recognizes and locates specific animal calls in real time. We investigate the system requirements of such a real-time acoustic monitoring network. We propose a system architecture and a set of lightweight collaborative signal processing algorithms that achieve real-time behavior while minimizing inter-node communication to extend the system lifetime. In particular, the target classification is based on spectrogram pattern matching while the target localization is based on beamforming using time difference of arrival (TDOA). We describe our preliminary implementation on a commercial off the shelf (COTS) testbed and present its performance based on testbed measurements.

Sensor networks: a bridge to the physical world

Wireless sensor networks are a new class of distributed systems that are an integral part of the physical space they inhabit. Unlike most computers, which work primarily with data created by humans, sensor networks reason about the state of the world that embodies them. This bridge to the physical world has captured the attention and imagination of many researchers, encompassing a broad spectrum of ideas, from environmental protection to military applications. In this chapter, we will explore some of this new technologys potential and innovations that are making it a reality.

Random, Ephemeral Transaction Identifiers in dynamic sensor networks

Recent advances in miniaturization and low-cost, low-power design have led to active research in large-scale, highly distributed systems of small, wireless, low-power unattended sensors and actuators. We explore the use of Random, Ephemeral TRansaction Identifiers (RETRI) in such systems, and contrast it with the typical design philosophy of using static identifiers in roles such as node addressing or efficient data naming. Instead of using statically assigned identifiers that are guaranteed to be unique, nodes randomly select probabilistically unique identifiers for each new transaction. We show how this randomized scheme can significantly improve the systems energy efficiency in contexts where that efficiency is paramount, such as energy-constrained wireless sensor networks. Benefits are realized if the typical data size is small compared to the size of an identifier, and the number of transactions seen by an individual node is small compared to the number of nodes that exist in the entire system. Our scheme is designed to scale well: identifier sizes grow with a systems density not its overall size. We quantify these benefits using an analytic model that predicts our schemes efficiency. We also describe an implementation as applied to packet fragmentation and an experiment that validates our model.