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Model-based monitoring for early warning flood detection
- in Proc. conf. 6th ACM conf. on Embedded network sensor systems (SenSys
, 2008
"... Predictive environmental sensor networks provide complex engineering and systems challenges. These systems must withstand the event of interest, remain functional over long time periods when no events occur, cover large geographical regions of interest to the event, and support the variety of sensor ..."
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Cited by 29 (2 self)
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Predictive environmental sensor networks provide complex engineering and systems challenges. These systems must withstand the event of interest, remain functional over long time periods when no events occur, cover large geographical regions of interest to the event, and support the variety of sensor types needed to detect the phenomenon. Prediction of the phenomenon on the network complicates the system further, requiring additional computation on the microcontrollers and utilizing prediction models that are not typically designed for sensor networks. This paper describes a system architecture and deployment to meet the design requirements and to allow model-driven control, thereby optimizing the prediction capability of the system. We explore the application of river flood prediction using this architecture, describing our work on a centralized form of the prediction model, network implementation, component testing and infrastructure development in Honduras, deployment on a river in Massachusetts, and results of the field experiments. Our system uses only a small number of nodes to cover basins of 1000-10000 km 2 using an unique heterogeneous communication structure to provide real-time sensed data, incorporating self-monitoring for failure, and adapting measurement schedules to capture events of interest.
Passive Inspection of Sensor Networks
- In DCOSS 2007
"... Abstract. Deployment of sensor networks in real-world settings is a labor-intensive and cumbersome task: environmental influences often trigger problems that are difficult to track down due to limited visibility of the network state. In this paper we present a framework for passive inspection (i.e., ..."
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Cited by 20 (4 self)
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Abstract. Deployment of sensor networks in real-world settings is a labor-intensive and cumbersome task: environmental influences often trigger problems that are difficult to track down due to limited visibility of the network state. In this paper we present a framework for passive inspection (i.e., no instrumentation of sensor nodes required) of deployed sensor networks and show how this framework can be used to inspect data gathering applications. The basic approach is to temporarily install a distributed network sniffer alongside the inspected sensor network, with overheard messages being analyzed by a data stream processor and network state being displayed in a graphical user interface. Our tool can be flexibly applied to different sensor network operating systems and protocol stacks, and can deal well with incomplete information. 1
Deployment of Sensor Networks: Problems and Passive Inspection
"... Deployment of sensor networks is concerned with setting up an operational wireless sensor network in a real-world setting. Unfortunately, deployment is a labor-intensive and cumbersome task as environmental influences often degrade performance or trigger bugs in the sensor network that could not be ..."
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Cited by 10 (0 self)
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Deployment of sensor networks is concerned with setting up an operational wireless sensor network in a real-world setting. Unfortunately, deployment is a labor-intensive and cumbersome task as environmental influences often degrade performance or trigger bugs in the sensor network that could not be observed during lab tests. In this paper, we, firstly, study existing sensor networks to identify and classify typical problems that have been encountered during deployment. Secondly, we investigate whether and how the existence of these problems can be detected by means of passive inspection, where messages exchanged in the sensor network are overheard and analyzed such that modification of the sensor network is not required. We, thirdly, show how passive inspection can be implemented in a practical tool.
1 Design of Early Warning Flood Detection Systems for Developing Countries
"... Abstract — In developing countries, flooding due to natural disasters such as hurricanes and earthquakes results in massive loss of life and property. Warning communities of the incoming flood provides an effective solution to this by giving people sufficient time to evacuate and protect their prope ..."
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Cited by 9 (0 self)
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Abstract — In developing countries, flooding due to natural disasters such as hurricanes and earthquakes results in massive loss of life and property. Warning communities of the incoming flood provides an effective solution to this by giving people sufficient time to evacuate and protect their property. However, the range of early warning system solutions introduces a tangle of conflicting requirements including cost and reliability, and creates several interesting problems from factors as diverse as technological, social, and political. The complexity of these systems and need for autonomy within the context of a developing country while remaining maintainable and accessible by nontechnical personnel provides a challenge not often solved within developed countries, much less the developing. After describing this problem, the paper discusses a proposed solution for the problem, initial experiments in implementing the solution, and lessons learned through that work. Index Terms — sensor network, early warning system, flood, honduras I.
Demo abstract: Passive inspection of deployed sensor networks with snif
- In Koen Langendoen and Thiemo Voigt, editors, 4th European Conference on Wireless Sensor Networks (EWSN
, 2007
"... Abstract — We demonstrate a tool that allows inspection and debugging of deployed wireless sensor networks (WSN) by analyzing overheard radio messages. This tool can identify common problems such as node crashes, reboots, routing problems, and network partitions without instrumentation of sensor nod ..."
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Cited by 4 (2 self)
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Abstract — We demonstrate a tool that allows inspection and debugging of deployed wireless sensor networks (WSN) by analyzing overheard radio messages. This tool can identify common problems such as node crashes, reboots, routing problems, and network partitions without instrumentation of sensor nodes. Existing approaches to identify performance problems and bugs in deployed WSN such as Sympathy [5] require to add logging and debugging code to the application running on the sensor nodes, with monitoring traffic being sent in-band with the sensor network data to the sink. These approaches result in significantly increased resource consumption in the WSN and bugs in the sensor network may also affect the monitoring mechanism. The presented tool is an implementation of our Sensor Network Inspection Framework (SNIF) [6], which consists of hardware to
EcoPlex: Empowering compact wireless sensor platforms via roaming and interoperability support
- in Proc. 6th Annu. Int. Conf. Mobile Ubiq. Syst
, 2009
"... Abstract—EcoPlex is an infrastructure that enables simple wireless platforms to participate seamlessly in a feature-rich, wireless ad hoc network. EcoPlex consists of gateways that are responsible for handoff support for mobility and high data rate without burdening the simple nodes to implement mul ..."
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Cited by 3 (2 self)
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Abstract—EcoPlex is an infrastructure that enables simple wireless platforms to participate seamlessly in a feature-rich, wireless ad hoc network. EcoPlex consists of gateways that are responsible for handoff support for mobility and high data rate without burdening the simple nodes to implement multi-hop protocols. The gateways also create virtual identities for simpler nodes to enable their participation in the feature-rich network without adding complexity to them. We demonstrate the feasibility of this idea with the ultra-compact wireless sensor platform called Eco to participate as virtual nodes in a fully general ZigBee network. Experimental results show EcoPlex to be efficient and scalable. The enhanced mobility and interoperability are added to the Eco platform at the infrastructure level, all with minimal node complexity. I.
Application-Informed Radio Duty-CyclinginaRe-TaskableMulti-UserSensing System
- InIPSN’09,2009
"... As sensor networks mature, there will be an increasing need for re-usable, dynamically taskable software systems that support multiple concurrent applications. In this paper, we consider the problem of energy management in such systems, taking Tenet as a case study. Our work considers energy managem ..."
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Cited by 2 (1 self)
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As sensor networks mature, there will be an increasing need for re-usable, dynamically taskable software systems that support multiple concurrent applications. In this paper, we consider the problem of energy management in such systems, taking Tenet as a case study. Our work considers energy management under three new constraints: dynamic multi-hop routing and tasking, multiple concurrent applications, and reliable end-toend data delivery. We present AEM, an energy management system that satisfies these constraints. AEM statically analyzes and infers the traffic profile for the application and accordingly tunes the duty-cycling protocol to provide the best trade-off in latency and data delivery performance. Furthermore, unlike other duty-cycling protocols with pre-computed or fixed transmission and reception time slots, AEM uses elastic schedules that allows it to adapt to dynamics while enabling bounded latency of event detection. Our experiments show that AEM achieves 1-3 % duty-cycles, while allowing concurrent applications to transmit 100 % of the sensor data in a multi-hop 40-node network testbed.
ABSTRACT SNIF: A Comprehensive Tool for Passive Inspection of Sensor Networks
"... Deployment of sensor networks in real-world settings is a laborintensive and cumbersome task: environmental influences often trigger problems that are difficult to track down due to limited visibility of the network state. In this extended abstract, we summarize our ongoing efforts to develop a tool ..."
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Deployment of sensor networks in real-world settings is a laborintensive and cumbersome task: environmental influences often trigger problems that are difficult to track down due to limited visibility of the network state. In this extended abstract, we summarize our ongoing efforts to develop a tool for passive inspection of sensor networks, where the network state can be inferred without instrumentation of sensor nodes. We also discuss next steps to make this tool applicable to a larger class of applications. 1.
JSense- Prototyping Sensor-Based, Location-Aware Applications in Java
"... Abstract. Creating applications based on data from individual sensor nodes is typically a two-tiered process: Firstly, a (potentially large) number of sensor nodes is deployed in order to gather comprehensive datasets. After analyzing the collected data, algorithms are then installed on the individu ..."
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Abstract. Creating applications based on data from individual sensor nodes is typically a two-tiered process: Firstly, a (potentially large) number of sensor nodes is deployed in order to gather comprehensive datasets. After analyzing the collected data, algorithms are then installed on the individual nodes and iteratively fine-tuned using a collect-and-analyze procedure. This approach is not only time consuming, but also prone to errors: the two separate steps of data collection and data analysis complicate algorithm development; the absence of programming abstractions in embedded systems programming languages often introduces hard-todetect runtime errors; and the lack of modern integrated development environments (IDEs) does not allow for quick trial-and-error prototyping. To mitigate those effects, we have developed JSense – a hardware abstraction layer for modern sensor nodes that allows for Java-based access to all sensor and actuator controls. It supports an IDE-based centralized development cycle with real-time debugging of a particular sensor environment, as well as the use of not-yet-available sensor and actuator hardware on each node, such as positioning information. Using JSense, designers of sensor-based environments can quickly try out a combination of situations and observe in real-time the data collection processes of their nodes, while programmers are able to prototype applications in their favorite Java-IDE in a hardware independent fashion, even taking into account not-yet-deployed node hardware. 1
