Next-generation prototyping of sensor networks

Beutel, Jan; Dyer, Matthias; Hinz, Martin; Meier, Lennart; Ringwald, Matthias

doi:10.1145/1031495.1031541

Cited by 40 publications

(17 citation statements)

References 6 publications

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“…Emulab, Mirage, and Kansei use serial interfaces; and Twist and MoteLab use USB interfaces, in order to access sensor nodes. In [18], it has been argued that such wired connections do not allow for large-scale WSNs deployment. Deployment Support for sensor Networks (DSN) [18], is a secondary wireless multi-hop network that has been introduced as a backbone solution for WSN testbeds.…”

Section: General-purpose Testbedsmentioning

confidence: 99%

“…In [18], it has been argued that such wired connections do not allow for large-scale WSNs deployment. Deployment Support for sensor Networks (DSN) [18], is a secondary wireless multi-hop network that has been introduced as a backbone solution for WSN testbeds. The backbone is used to retrieve data (packet-statistics) from the sensor nodes and to control them by sending direct commands.…”

Section: General-purpose Testbedsmentioning

confidence: 99%

“…Each DSNnode is attached to a sensor node. In their implementation of DSN, the authors in [18] have chosen Bluetooth as a wireless transport layer and BTnode as a platform for DSN-nodes. Further, they provided modules for data forwarding and topology control to optimize the connectivity and the reliability of the backbone DSN network.…”

Section: General-purpose Testbedsmentioning

confidence: 99%

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RadiaLE: A framework for designing and assessing link quality estimators in wireless sensor networks

et al. 2011

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a b s t r a c tStringent cost and energy constraints impose the use of low-cost and low-power radio transceivers in large-scale wireless sensor networks (WSNs). This fact, together with the harsh characteristics of the physical environment, requires a rigorous WSN design. Mechanisms for WSN deployment and topology control, MAC and routing, resource and mobility management, greatly depend on reliable link quality estimators (LQEs). This paper describes the RadiaLE framework, which enables the experimental assessment, design and optimization of LQEs. RadiaLE comprises (i) the hardware components of the WSN testbed and (ii) a software tool for setting-up and controlling the experiments, automating link measurements gathering through packets-statistics collection, and analyzing the collected data, allowing for LQEs evaluation. We also propose a methodology that allows (i) to properly set different types of links and different types of traffic, (ii) to collect rich link measurements, and (iii) to validate LQEs using a holistic and unified approach. To demonstrate the validity and usefulness of RadiaLE, we present two case studies: the characterization of low-power links and a comparison between six representative LQEs. We also extend the second study for evaluating the accuracy of the TOSSIM 2 channel model.

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Section: General-purpose Testbedsmentioning

confidence: 99%

Section: General-purpose Testbedsmentioning

confidence: 99%

Section: General-purpose Testbedsmentioning

confidence: 99%

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RadiaLE: A framework for designing and assessing link quality estimators in wireless sensor networks

et al. 2011

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“…A number of frameworks exist in the literature for monitoring, diagnosing and sometimes predicting possible faults within deployed networks. The nodes performing monitoring tasks can form part of the network, e.g., Sympathy [2], or they can belong to a dedicated and separate infrastructure or Deployment Support Network (DSN) [3] [4].…”

Section: B Monitoringmentioning

confidence: 99%

Integrity-Checking Framework: An In-situ Testing and Validation Framework for Wireless Sensor and Actuator Networks

Pennington

Bauge

Murray

2009

2009 Third International Conference on Sensor Technologies and Applications

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Abstract-Wireless sensor and actuator network applications require several levels of testing during their development.Although software algorithms can be tested through simulations and syntax checking, it is difficult to predict or test for problems that may occur once the wireless sensor and actuator has been deployed. The requirement for testing is not however limited to the development phase. During the lifecycle of the system, faults, upgrades, retasking, etc. lead to further needs for system validation.In this paper we review the state-of-the-art techniques for testing wireless sensor and actuator applications and propose the Integrity-Checking Framework. The framework provides in-situ full lifecycle testing and validation of wireless sensor and actuator applications by performing an "Integrity Check", during which the sensor inputs and actuator responses are emulated within the physical wireless sensor and actuator. This enables application-level testing by feeding controlled information to the sensor inputs, while data processing, communication, aggregation and decision making continue as normal across the physical wireless sensor and actuator.

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“…The BTnode (see Figure 1) is a versatile, lightweight, autonomous platform based on a Bluetooth radio, a second independent low-power radio and a microcontroller [12]. The device is designed for fast prototyping [11] of ad-hoc and wireless sensor network applications and is well suited to investigate different protocols, operation parameter tradeoffs and radio alternatives.…”

Section: Bluetooth and The Btnode Platformmentioning

confidence: 99%

Power Management for Bluetooth Sensor Networks

Negri

Thiele

2006

Lecture Notes in Computer Science

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Abstract. Low power is a primary concern in the field of wireless sensor networks. Bluetooth has often been labeled as an inappropriate technology in this field due to its high power consumption. However, most Bluetooth studies employ rather over-simplified, fully theoretical, or inadequate power models. We present a power model of Bluetooth including scatternet configurations and low-power sniff mode and validate it experimentally on a real Bluetooth module. Based on this model, we introduce a power optimization framework employing MILP (Mixed-Integer Linear Programming) techniques, and devise optimal power management policies in the presence of end-to-end delay constraints. Our optimizations, if backed by power-aggressive hardware implementations, can make Bluetooth viable for a wider range of sensor networks.

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Next-generation prototyping of sensor networks

Cited by 40 publications

References 6 publications

RadiaLE: A framework for designing and assessing link quality estimators in wireless sensor networks

RadiaLE: A framework for designing and assessing link quality estimators in wireless sensor networks

Integrity-Checking Framework: An In-situ Testing and Validation Framework for Wireless Sensor and Actuator Networks

Power Management for Bluetooth Sensor Networks

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