Deploying a Wireless Sensor Network on an Active Volcano (0)

by G Werner-Allen, K Lorincz, M Welsh, O Marcillo, J Johnson, M Ruiz, J Lees
Venue:IEEE Internet Computing
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Fidelity and yield in a volcano monitoring sensor network

by Geoff Werner-allen, Konrad Lorincz, Jeff Johnson, Jonathan Lees, Matt Welsh - In Proc. 7th USENIX Symposium on Operating Systems Design and Implementation (OSDI 2006 , 2006
"... We present a science-centric evaluation of a 19-day sensor network deployment at Reventador, an active volcano in Ecuador. Each of the 16 sensors continuously sampled seismic and acoustic data at 100 Hz. Nodes used an event-detection algorithm to trigger on interesting volcanic activity and initiate ..."
Abstract - Cited by 276 (11 self) - Add to MetaCart
We present a science-centric evaluation of a 19-day sensor network deployment at Reventador, an active volcano in Ecuador. Each of the 16 sensors continuously sampled seismic and acoustic data at 100 Hz. Nodes used an event-detection algorithm to trigger on interesting volcanic activity and initiate reliable data transfer to the base station. During the deployment, the network recorded 229 earthquakes, eruptions, and other seismoacoustic events. The science requirements of reliable data collection, accurate event detection, and high timing precision drive sensor networks in new directions for geophysical monitoring. The main contribution of this paper is an evaluation of the sensor network as a scientific instrument, holding it to the standards of existing instrumentation in terms of data fidelity (the quality and accuracy of the recorded signals) and yield (the quantity of the captured data). We describe an approach to time rectification of the acquired signals that can recover accurate timing despite failures of the underlying time synchronization protocol. In addition, we perform a detailed study of the sensor network’s data using a direct comparison to a standalone data logger, as well as an investigation of seismic and acoustic wave arrival times across the network. 1
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Energy conservation in wireless sensor networks: A survey

by Giuseppe Anastasi, Marco Conti, Mario Di Francesco, Andrea Passarella
"... In the last years, wireless sensor networks (WSNs) have gained increasing attention from both the research community and actual users. As sensor nodes are generally battery-powered devices, the critical aspects to face concern how to reduce the energy consumption of nodes, so that the network lifeti ..."
Abstract - Cited by 227 (11 self) - Add to MetaCart
In the last years, wireless sensor networks (WSNs) have gained increasing attention from both the research community and actual users. As sensor nodes are generally battery-powered devices, the critical aspects to face concern how to reduce the energy consumption of nodes, so that the network lifetime can be extended to reasonable times. In this paper we first break down the energy consumption for the components of a typical sensor node, and discuss the main directions to energy conservation in WSNs. Then, we present a systematic and comprehensive taxonomy of the energy conservation schemes, which are subsequently discussed in depth. Special attention has been devoted to promising solutions which have not yet obtained a wide attention in the literature, such as techniques for energy efficient data acquisition. Finally we conclude the paper with insights for research directions about energy conservation in WSNs.

Atpc: Adaptive transmission power control for wireless sensor networks

by Shan Lin, Jingbin Zhang, Gang Zhou, Lin Gu, Tian He, John A. Stankovic - In Proceedings of the Fourth International Conference on Embedded Networked Sensor Systems (SenSys , 2006
"... Extensive empirical studies presented in this paper confirm that the quality of radio communication between low power sensor devices varies significantly with time and environment. This phenomenon indicates that the previous topology control solutions, which use static transmission power, transmissi ..."
Abstract - Cited by 146 (10 self) - Add to MetaCart
Extensive empirical studies presented in this paper confirm that the quality of radio communication between low power sensor devices varies significantly with time and environment. This phenomenon indicates that the previous topology control solutions, which use static transmission power, transmission range, and link quality, might not be effective in the physical world. To address this issue, online transmission power control that adapts to external changes is necessary. This paper presents ATPC, a lightweight algorithm of Adaptive Transmission Power Control for wireless sensor networks. In ATPC, each node builds a model for each of its neighbors, describing the correlation between transmission power and link quality. With this model, we employ a feedback-based transmission power control algorithm to dynamically maintain individual link quality over time. The intellectual contribution of this work lies in a novel pairwise transmission power control, which is significantly different from existing node-level or network-level power control methods. Also different from most existing simulation work, the ATPC design is guided by extensive field experiments of link quality dynamics at various locations and over a long period of time. The results from the real-world experiments demonstrate that 1) with pairwise adjustment, ATPC achieves more energy savings with a finer tuning capability and 2) with online control, ATPC is robust even with environmental changes over time.
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Energy harvesting sensor nodes: Survey and implications

by Sujesha Sudevalayam, Purushottam Kulkarni - Department of Computer Science and Engineering , 2008
"... Sensor networks with battery-powered nodes can seldom simultaneously meet the design goals of lifetime, cost, sensing reliability and sensing and transmission coverage. Energy-harvesting, converting ambient energy to electrical energy, has emerged as an alternative to power sensor nodes. By exploiti ..."
Abstract - Cited by 125 (0 self) - Add to MetaCart
Sensor networks with battery-powered nodes can seldom simultaneously meet the design goals of lifetime, cost, sensing reliability and sensing and transmission coverage. Energy-harvesting, converting ambient energy to electrical energy, has emerged as an alternative to power sensor nodes. By exploiting recharge opportunities and tuning performance parameters based on current and expected energy levels, energy harvesting sensor nodes have the potential to address the conflicting design goals of lifetime and performance. This paper surveys various aspects of energy harvesting sensor systems — architecture, energy sources and storage technologies and examples of harvesting-based nodes and applications. The study also discusses the implications of recharge opportunities on sensor node operation and design of sensor network solutions. 1
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LUSTER: Wireless Sensor Network for Environmental Research

by L. Selavo, A. Wood, Q. Cao, T. Sookoor, H. Liu, A. Srinivasan, Y. Wu, W. Kang, J. Stankovic, D. Young, J. Porter
"... Environmental wireless sensor network (EWSN) systems are deployed in potentially harsh and remote environments where inevitable node and communication failures must be tolerated. LUSTER—Light Under Shrub Thicket for Environmental Research—is a system that meets the challenges of EWSNs using a hierar ..."
Abstract - Cited by 77 (8 self) - Add to MetaCart
Environmental wireless sensor network (EWSN) systems are deployed in potentially harsh and remote environments where inevitable node and communication failures must be tolerated. LUSTER—Light Under Shrub Thicket for Environmental Research—is a system that meets the challenges of EWSNs using a hierarchical architecture that includes distributed reliable storage, delay-tolerant networking, and deployment time validation techniques. In LUSTER, a fleet of sensors coordinate communications using LiteTDMA, a low-power cluster-based MAC protocol. They measure the complex light environment in thickets and are open to additional ecological parameters, such as temperature and CO2. LUSTER has been deployed and evaluated in laboratory, forested, and barrier island environments. It includes new sensor hardware designs: (a) “SolarDust, ” a hybrid multichannel energy harvesting and sensing device; (b) “Medusa,” a spatially reconfigurable light sensor; (c) a removable SD card storage node; and, (d) in-situ user interface tool for deployment time validation.
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The Hitchhiker's Guide to Successful Wireless Sensor Network Deployments

by Guillermo Barrenetxea, François Ingelrest, Gunnar Schaefer, Martin Vetterli - in Proceedings of ACM SenSys , 2008
"... The successful deployment of a wireless sensor network is a difficult task, littered with traps and pitfalls. Even a functional network does not guarantee gathering meaningful data. In SensorScope, with its multiple campaigns in various environments (e.g., urban, high-mountain), we have acquired muc ..."
Abstract - Cited by 72 (1 self) - Add to MetaCart
The successful deployment of a wireless sensor network is a difficult task, littered with traps and pitfalls. Even a functional network does not guarantee gathering meaningful data. In SensorScope, with its multiple campaigns in various environments (e.g., urban, high-mountain), we have acquired much knowledge in planning, conducting, and managing real-world sensor network deployments. In this paper, we share our experience by stepping through the entire process, from the preparatory hard- and software development to the actual field deployment. Illustrated by numerous reallife examples, excerpted from our own experience, we point out many potential problems along this way and their possible solutions. We also indicate the importance of a close interaction with the end-user community in planning and running the network, and finally exploiting the data. Categories and Subject Descriptors
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Computational Intelligence in Wireless Sensor Networks: A Survey

by Raghavendra V. Kulkarni, Anna Förster, Ganesh Kumar Venayagamoorthy - IEEE COMMUNICATIONS SURVEYS & TUTORIALS , 2011
"... Wireless sensor networks (WSNs) are networks of distributed autonomous devices that can sense or monitor physical or environmental conditions cooperatively. WSNs face many challenges, mainly caused by communication failures, storage and computational constraints and limited power supply. Paradigms o ..."
Abstract - Cited by 41 (0 self) - Add to MetaCart
Wireless sensor networks (WSNs) are networks of distributed autonomous devices that can sense or monitor physical or environmental conditions cooperatively. WSNs face many challenges, mainly caused by communication failures, storage and computational constraints and limited power supply. Paradigms of computational intelligence (CI) have been successfully used in recent years to address various challenges such as data aggregation and fusion, energy aware routing, task scheduling, security, optimal deployment and localization. CI provides adaptive mechanisms that exhibit intelligent behavior in complex and dynamic environments like WSNs. CI brings about flexibility, autonomous behavior, and robustness against topology changes, communication failures and scenario changes. However, WSN developers are usually not or not completely aware of the potential CI algorithms offer. On the other side, CI researchers are not familiar with all real problems and subtle requirements of WSNs. This mismatch makes collaboration and development difficult. This paper intends to close this gap and foster collaboration by offering a detailed introduction to WSNs and their properties. An extensive survey of CI applications to various problems in WSNs from various research areas and publication venues is presented in the paper. Besides, a discussion on advantages and disadvantages of CI algorithms over traditional WSN solutions is offered. In addition, a general evaluation of CI algorithms is presented, which will serve as a guide for using CI algorithms for WSNs.

NodeMD: Diagnosing Node-Level Faults in Remote Wireless Sensor Systems

by Veljko Krunic, Eric Trumpler, Richard Han , 2007
"... Software failures in wireless sensor systems are notoriously difficult to debug. Resource constraints in wireless deployments substantially restrict visibility into the root causes of node-level system and application faults. At the same time, the high costs of deployment of wireless sensor systems ..."
Abstract - Cited by 38 (0 self) - Add to MetaCart
Software failures in wireless sensor systems are notoriously difficult to debug. Resource constraints in wireless deployments substantially restrict visibility into the root causes of node-level system and application faults. At the same time, the high costs of deployment of wireless sensor systems often far exceed the cumulative costs of all other sensor hardware, so that software failures that completely disable a node are prohibitively expensive to repair in real world applications, e.g. by on-site visits to replace or reset nodes. We describe NodeMD, a deployment management system that successfully implements lightweight run-time detection, logging, and notification of software faults on wireless mote-class devices. NodeMD introduces a debug mode that catches a failure before it completely disables a node and drops the node into a stable state that enables further diagnosis and correction, thus avoiding on-site redeployment. We analyze the performance of NodeMD on a real world application of wireless sensor systems.

Wireless sensor networks for battlefield surveillance

by Tatiana Bokareva, Wen Hu, Salil Kanhere, Branko Ristic, Travis Bessell, Mark Rutten, Sanjay Jha - in Proc. of the Land Warfare Conference , 2006
"... In this position paper, we investigate the use of wireless sensor network (WSN) technology for ground surveillance. The goal of our project is to develop a prototype of WSN for outdoor deployment. We aim to design a system, which can detect and classify multiple targets (e.g., vehicles and troop mov ..."
Abstract - Cited by 36 (0 self) - Add to MetaCart
In this position paper, we investigate the use of wireless sensor network (WSN) technology for ground surveillance. The goal of our project is to develop a prototype of WSN for outdoor deployment. We aim to design a system, which can detect and classify multiple targets (e.g., vehicles and troop movements), using inexpensive off-the-shelf wireless sensor devices, capable of sensing acoustic and magnetic signals generated by different target objects. In order to archive our goals, we intend to design a system, which is capable of automatic selforganization and calibration. Such a system would need to be capable of performing detection and tracking of targets as well as sending the real time enemy mobility information to a command centre. Real-time tacking with WSN is extremely challenging since it requires high system robustness, real time decision making, high frequency sampling, multi-modality of sensing, complex signal processing and data fusion, distributed coordination and wide area coverage. We propose a Hybrid Sensor Network architecture (HSN), tailored specifically to meet these challenges. We investigate data fusion technologies such as particle filters, to handle both environmental and sensing noises of inexpensive sensors.

The design and evaluation of a mobile sensor/actuator network for autonomous animal control

by Tim Wark, Chris Crossman, Wen Hu, Ying Guo, Philip Valencia, Pavan Sikka, Peter Corke, Caroline Lee, John Henshall, Kishore Prayaga, Matt Reed§ Andrew - In ACM/IEEE International Conference on Information Processing in Sensor Networks (SPOTS Track , 2007
"... This paper investigates a mobile, wireless sensor/actuator network application for use in the cattle breeding industry. Our goal is to prevent fighting between bulls in on-farm breeding paddocks by autonomously applying appropriate stimuli when one bull approaches another bull. This is an important ..."
Abstract - Cited by 30 (3 self) - Add to MetaCart
This paper investigates a mobile, wireless sensor/actuator network application for use in the cattle breeding industry. Our goal is to prevent fighting between bulls in on-farm breeding paddocks by autonomously applying appropriate stimuli when one bull approaches another bull. This is an important application because fighting between high-value animals such as bulls during breeding seasons causes significant financial loss to producers. Furthermore, there are significant challenges in this type of application be-cause it requires dynamic animal state estimation, real-time actuation and efficient mobile wireless transmissions. We designed and implemented an animal state estimation algorithm based on a state-machine mechanism for each an-imal. Autonomous actuation is performed based on the esti-mated states of an animal relative to other animals. A sim-ple, yet effective, wireless communication model has been proposed and implemented to achieve high delivery rates in mobile environments. We evaluated the performance of our design by both simulations and field experiments, which demonstrated the effectiveness of our autonomous animal control system.