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A Parallel Simulated Annealing Architecture for Model Updating in Wireless Sensor networks

IEEE SENSORS JOURNAL 2009年第11期9卷 1503-1510页

作者： Zimmerman, Andrew T. Lynch, Jerome P. Univ Michigan Ann Arbor MI 48109 USA

In recent years, wireless sensing technologies have provided a much sought-after alternative to expensive cabled monitoring systems. Wireless sensing networks forego the high data transfer rates associated with cabled sensors in exchange for low-cost and low-power communication between a large number of sensing devices, each of which features embedded data processing capabilities. As such, a new paradigm in large-scale data processing has emerged;one where communication bandwidth is somewhat limited but distributed data processing centers are abundant. By taking advantage of this grid of computational resources, data processing tasks once performed independently by a central processing unit can now be parallelized, automated, and carried out within a wireless sensor network. By utilizing the intelligent organization and self-healing properties of many wireless networks, an extremely scalable multiprocessor computational framework can be developed to perform advanced engineering analyses. In this study, a novel parallelization of the simulated annealing stochastic search algorithm is presented and used to update structural models by comparing model predictions to experimental results. The resulting distributed model updating algorithm is validated within a network of wireless sensors by identifying the mass, stiffness, and damping properties of a three-story steel structure subjected to seismic base motion.

关键词： in-network data processing parallel algorithms structural monitoring wireless sensors

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Fence monitoring - Experimental evaluation of a use case for wireless sensor networks

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4th European Conference on Wireless Sensor networks

作者： Wittenburg, Georg Terfloth, Kirsten Villafuerte, Freddy Lopez Naumowicz, Tomasz Ritter, Hartmut Schiller, Jochen Free Univ Berlin Dept Math & Comp Sci Takustr 9 D-14195 Berlin Germany

ISBN: (纸本)9783540698296

in-network data processing and event detection on resource-constrained devices are widely regarded as distinctive and novel features of wireless sensor networks. The vision is that through cooperation of many sensor nodes the accuracy of event detection can be greatly improved. On the practical side however, little real-world experience exists in how far these goals can be achieved. In this paper, we present the results of a small deployment of sensor nodes attached to a fence with the goal of collaboratively detecting and reporting security relevant incidents, such as a person climbing over the fence. Based on experimental data we discuss in detail the process of in-network event detection both from the conceptual side and by evaluating the results obtained. Reusing the same traces in a simulated network, we also look into the impact of multi-hop event reporting.

关键词： wireless sensor networks in-network data processing event detection experimental evaluation use case fence monitoring

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In-network Training and Distributed Event Detection in Wireless Sensor networks 08

In-network Training and Distributed Event Detection in Wirel...

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6th ACM Conference on Embedded networked Sensor Systems

作者： Wittenburg, Georg Dziengel, Norman Schiller, Jochen Free Univ Berlin Dept Math & Comp Sci D-14195 Berlin Germany

ISBN: (纸本)9781595939906

In order to avoid transmitting raw data to a base station, sensor nodes are trained to cooperatively recognize deployment-specific events based on the data sampled by their sensors. As both training and event detection are performed without the need for central coordination or processing, only information about the detected event needs to be reported.

关键词： Wireless Sensor networks Distributed Event Detection in-network data processing Pattern Recognition

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Agent-Based Structural Health Monitoring System on Single Degree of Freedom Bridge: A Preliminary Study 2

Agent-Based Structural Health Monitoring System on Single De...

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International Conference on Information Technology Systems and Innovation (ICITSI)

作者： Putra, Seno Adi Trilaksono, Bambang Riyanto Harsoyo, Agung Imam, Achmad Bandung Inst Technol Sch Elect Engn & Informat Bandung Indonesia

ISBN: (纸本)9781467366649

Wireless Sensor network (WSN) is small embedded devices deployed in large scale network with sensing, computing, and communicating capability. In the case of bridge structural health monitoring system, WSN has taken important role in physical measurement. This paper describes preliminary study of Agent-oriented paradigm to develop intelligent sensing in single degree of freedom bridge. The objectives of research are finding bridge condition assessment and load rating using dynamic response. Sensor node capability to compute is our consideration to develop intelligent sensing on sensor node in which signal processing with efficient resource consumption are performed. This paper is an entry point for our next research agendas: data preprocessing (in-network data processing) and intelligent agent implemented on sensor nodes.

关键词： Wireless Sensor network structural health monitoring system single degree of freedom bridge bridge condition assessment and load rating intelligent agent in-network data processing

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A System for Distributed Event Detection in Wireless Sensor networks

A System for Distributed Event Detection in Wireless Sensor ...

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9th ACM/IEEE International Conference on Information processing in Sensor networks (IPSN)

作者： Wittenburg, Georg Dziengel, Norman Wartenburger, Christian Schiller, Jochen Free Univ Berlin Dept Math & Comp Sci Takustr 9 D-14195 Berlin Germany

ISBN: (纸本)9781605589886

Event detection is a major issue for applications of wireless sensor networks. In order to detect an event, a sensor network has to identify which application-specific incident has occurred based on the raw data gathered by individual sensor nodes. In this context, an event may be anything from a malfunction of monitored machinery to an intrusion into a restricted area. The goal is to provide high-accuracy event detection at minimal energy cost in order to maximize network lifetime. In this paper, we present a system for collaborative event detection directly on the sensor nodes. The system does not require a base station for centralized coordination or processing, and is fully trainable to recognize different classes of application-specific events. Communication overhead is reduced to a minimum by processing raw data directly on the sensor nodes and only reporting which events have been detected. The detection accuracy is evaluated using a 100-node sensor network deployed as a wireless alarm system on the fence of a real-world construction site.

关键词： wireless sensor network distributed event detection in-network data processing pattern recognition

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Mires++: A Reliable, Energy-aware Clustering Algorithm for Wireless Sensor networks

Mires++: A Reliable, Energy-aware Clustering Algorithm for W...

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13th ACM International Conference on Modeling, Analysis and Simulation of Wireless and Mobile Systems

作者： Nie, Pin Jin, Zhihua Gong, Yi Aalto Univ Sch Sci & Technol Dept Comp Sci & Engn Espoo Finland

ISBN: (纸本)9781450302746

Wireless Sensor networks (WSNs) often contain a large number of nodes. In order to organize nodes efficiently for a long lifespan, clustering algorithm is demanded in WSNs to reduce redundant data transmissions and to save energy. We propose a novel clustering algorithm to create reliable and energy-aware clusters for in-network data processing. The clustering algorithm is a new service on a publish/subscribe middleware called Mires. The goal is to improve load balancing and robustness. Our clustering algorithm considers location information to facilitate boundary control. We conducted simulations to evaluate performance and energy efficiency. We implemented a prototype for feasibility demonstration.

关键词： Wireless Sensor network Clustering Algorithm Middleware Publish/Subcribe Paradigm in-network data processing

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NOA: A Scalable Multi-Parent Clustering Hierarchy for WSNs

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Procedia Computer Science 2012年 10卷 1140-1145页

作者： Johnathan Vee Cree Jose Delgado-Frias Mike Hughes Brion Burghard Kurt Silvers School of Electrical Engineering and Computer Science Washington State University Pullman WA Pacific Northwest National Laboratory Richland WA

NOA is a multi-hop, multi-parent, N-tiered, hierarchical clustering algorithm that provides a scalable, robust and reliable solution for autonomous configuration of large-scale wireless sensor networks. The novel clustering hierarchy's inherent benefits can be utilized by in-network data processing techniques to provide a robust data processing solution capable of reducing the amount of data sent to data sinks. Utilizing a multi-parent framework, NOA reduces the cost of network configuration when compared to current hierarchical beaconing solutions by removing the r-hop fi (where r is the radius of the cluster). NOA instead utilizes common children to distribute information about the hierarchy's topology to siblings. NOA 2 , a two-parent clustering hierarchy solution, and NOA 3 , the three-parent variant, saw up to an 83% and 72% reduction in communication overhead, respectively, when compared to configuring the network using a one-parent hierarchical beaconing solution, as well as 92% and 88% less overhead when compared to two-and three-parent variants of hierarchical beaconing.

关键词： wireless sensor networks multi-parent clustering hierarchy autonomous configuration in-network data processing

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Fence monitoring: experimental evaluation of a use case for wireless sensor networks 07

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Proceedings of the 4th European conference on Wireless sensor networks

作者： Georg Wittenburg Kirsten Terfloth Freddy López Villafuerte Tomasz Naumowicz Hartmut Ritter Jochen Schiller Department of Mathematics and Computer Science Freie Universität Berlin Berlin Germany

ISBN: (纸本)9783540698296

in-network data processing and event detection on resource-constrained devices are widely regarded as distinctive and novel features of wireless sensor networks. The vision is that through cooperation of many sensor nodes the accuracy of event detection can be greatly improved. On the practical side however, little real-world experience exists in how far these goals can be *** this paper, we present the results of a small deployment of sensor nodes attached to a fence with the goal of collaboratively detecting and reporting security relevant incidents, such as a person climbing over the fence. Based on experimental data we discuss in detail the process of innetwork event detection both from the conceptual side and by evaluating the results obtained. Reusing the same traces in a simulated network, we also look into the impact of multi-hop event reporting.

关键词： in-network data processing experimental evaluation event detection wireless sensor networks fence monitoring use case

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Use of Optimization Models for Resource Allocation in Wireless Ad-Hoc and Sensor networks 16

Use of Optimization Models for Resource Allocation in Wirele...

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Proceedings of the 19th ACM International Conference on Modeling, Analysis and Simulation of Wireless and Mobile Systems

作者： Kin K. Leung Imperial College London London United Kingdom

ISBN: (纸本)9781450345026

Optimization models and techniques are often used to achieve efficient allocation of limited network resources to competing demands in communication networks. In this talk, the speaker will give a brief overview of distributed optimization theory, including convex optimization problems for which iterative solution techniques exist and converge. The well-known Transport Control Protocol (TCP) is shown to be equivalent a distributed solution that achieves the optimal allocation of bandwidth in communication networks. As for wireless ad-hoc and sensor networks, each link capacity depends on the transmission power of other links due to co-channel interference. In addition, the quality of multimedia services supported by these networks cannot be represented by a concave function of the amount of allocated bandwidth. These factors unfortunately make the resource allocation problem for the wireless networks become a non-convex optimization problem. New distributed solution techniques will be presented to solve these problems and numerical examples will also be *** talk will also consider the in-network data processing in wireless sensor networks where data are aggregated (fused) along the way they are transferred toward the end user. It will be shown that finding the optimal solution for the distributed processing problem is NP-hard, but for specific parameter settings, the problem can lead to a distributed framework for achieving the optimal tradeoff between communications and computation costs. Future work on integrating data or signal processing techniques with the distributed solution framework will be discussed.

关键词： resource allocation optimization in-network data processing wireless ad-hoc and sensor networks

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Energy-efficient collection of wearable sensor data through predictive sampling

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Smart Health 2021年 21卷

作者： Lalouani, Wassila Younis, Mohamed White-Gittens, Ian Emokpae, Roland N. Emokpae, Lloyd E. CSEE Dept. Univ. of Maryland Baltimore County Baltimore MD United States Harlem Hospital NY 506 Lenox Ave New York 10037 NY United States LASARRUS Clinic and Research Center LLC. Baltimore MD United States

Wearable sensors have emerged as viable and attractive solutions for monitoring the health of people under risk of major problems such as hypertension, heart attacks, and athletes overstressing their bodies. These devices would report on the status of certain body organs to a gateway node over wireless links. A major challenge for effective use of these miniaturized devices is sustaining their operation using a limited energy supply. Therefore, minimizing energy consumption is a crucial design goal. In this paper we propose a novel approach for reducing the volume and frequency of data transmission through data sample prediction. Our methodology is based on applying advanced machine learning techniques to determine when data transmissions are skipped, and by implicitly making the gateway aware of the omitted samples in order to achieve accurate signal reconstruction. The paper also presents a data quantization technique for increased throughput and reduced energy overhead while sustaining desired medical assessment accuracy. Furthermore, a packet formation algorithm is proposed to leverage the available buffering space to improve bandwidth and energy utilization subject to latency constraints. The effectiveness of our approach is validated using publicly available Electrocardiography and Electromyography datasets and is shown not only to outperform conventional data compression methods but can also be applied in conjunction with them. © 2021 Elsevier Inc.

关键词： Body area sensor network Energy optimization in-network data processing Predictive sampling Wearable devices

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