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Results 11 - 20
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107
Prius: Generic Hybrid Trace Compression for Wireless Sensor Networks
"... Several diagnostic tracing techniques (e.g., event, power, and control-flow tracing) have been proposed for run-time debugging and postmortem analysis of wireless sensor networks (WSNs). Traces generated by such techniques can become large, defying the harsh resource constraints of WSNs. Compression ..."
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Cited by 4 (2 self)
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Several diagnostic tracing techniques (e.g., event, power, and control-flow tracing) have been proposed for run-time debugging and postmortem analysis of wireless sensor networks (WSNs). Traces generated by such techniques can become large, defying the harsh resource constraints of WSNs
Reordering for Better Compressibility: Efficient Spatial Sampling in Wireless Sensor Networks
"... Abstract—Compressed Sensing (CS) is a novel sampling paradigm that tries to take data-compression concepts down to the sampling layer of a sensory system. It states that discrete compressible signals are recoverable from sub-sampled data, when the data vector is acquired by a special linear transfor ..."
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Cited by 1 (0 self)
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transform of the original discrete signal vector. Distributed sampling problems especially in Wireless Sensor Networks (WSN) are good candidates to apply CS and increase sensing efficiency without sacrificing accuracy. In this paper, we discuss how to reorder the samples of a discrete spatial signal vector
Compressive Data Persistence in Large-Scale Wireless Sensor Networks
"... This paper considers a large-scale wireless sensor network where sensor readings are occasionally collected by a mobile sink, and sensor nodes are responsible for temporarily storing their own readings in an energy-efficient and storage-efficient way. Existing data persistence schemes based on eras ..."
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This paper considers a large-scale wireless sensor network where sensor readings are occasionally collected by a mobile sink, and sensor nodes are responsible for temporarily storing their own readings in an energy-efficient and storage-efficient way. Existing data persistence schemes based
Path Reconstruction in Dynamic Wireless Sensor Networks Using Compressive Sensing
"... This paper presents CSPR, a compressive sensing based approach for path reconstruction in wireless sensor networks. By viewing the whole network as a path representation space, an arbitrary routing path can be represented by a path vector in the space. As path length is usually much smaller than the ..."
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This paper presents CSPR, a compressive sensing based approach for path reconstruction in wireless sensor networks. By viewing the whole network as a path representation space, an arbitrary routing path can be represented by a path vector in the space. As path length is usually much smaller than
Distributed on-Demand Address Assignment in Wireless Sensor Networks
- IEEE SIGNAL PROCESSING
, 2002
"... Sensor networks consist of autonomous wireless sensor nodes that are networked together in an ad-hoc fashion. The tiny nodes are equipped with substantial processing capabilities, enabling them to combine and compress their sensor data. The aim is to limit the amount of network traffic, and as such ..."
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Cited by 32 (0 self)
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Sensor networks consist of autonomous wireless sensor nodes that are networked together in an ad-hoc fashion. The tiny nodes are equipped with substantial processing capabilities, enabling them to combine and compress their sensor data. The aim is to limit the amount of network traffic
RBMulticast: Receiver Based Multicast for Wireless Sensor Networks
"... Abstract—Multicast routing protocols typically rely on the a-priori creation of a multicast tree (or mesh), which requires the individual nodes to maintain state information. In sensor networks where traffic is bursty, with long periods of silence between the bursts of data, this multicast state mai ..."
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Cited by 8 (1 self)
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Abstract—Multicast routing protocols typically rely on the a-priori creation of a multicast tree (or mesh), which requires the individual nodes to maintain state information. In sensor networks where traffic is bursty, with long periods of silence between the bursts of data, this multicast state
Wireless Sensor Networking in Challenging Environments
, 2014
"... This Dissertation is brought to you for free and open access by Washington University Open Scholarship. It has been accepted for inclusion in All Theses and Dissertations (ETDs) by an authorized administrator of Washington University Open Scholarship. For more information, please contact ..."
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This Dissertation is brought to you for free and open access by Washington University Open Scholarship. It has been accepted for inclusion in All Theses and Dissertations (ETDs) by an authorized administrator of Washington University Open Scholarship. For more information, please contact
Article TDMA-Based Dual-Mode Communication for Mobile Wireless Sensor Networks
, 2012
"... sensors ..."
Ensemble Learning Online Filtering in Wireless Sensor Networks
"... Abstract — In many applications, the observed system is assumed to evolve according to a probabilistic state space model. The data likelihood function is, in general, non linear or/and non Gaussian leading to analytically intractable inference. Particle filter is a popular approximate Monte Carlo so ..."
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Cited by 4 (2 self)
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solution based on a particle representation of the filtering distribution. However, power constraints in sensor networks requires an additional approximation (compression) when communicating the particle based representation. In this contribution, we propose an alternative ensemble learning (variational
Dynamic Data Aggregation and Transport in Wireless Sensor Networks
"... Abstract—In wireless sensor networks, in-network aggregation is the process of compressing locally the data gathered by the sensor nodes, so that only the compressed data travel across several hops to their destination. We address the problem of aggregating data generated by sporadic events in rando ..."
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Cited by 4 (1 self)
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Abstract—In wireless sensor networks, in-network aggregation is the process of compressing locally the data gathered by the sensor nodes, so that only the compressed data travel across several hops to their destination. We address the problem of aggregating data generated by sporadic events
Results 11 - 20
of
107
