检索结果-内蒙古大学图书馆

in-network data processing Based on Compressed Sensing in WSN: A Survey

WIRELESS PERSONAL COMMUNICATIONS 2017年第2期96卷 2087-2124页

作者： Singh, Vishal Krishna Singh, Vivek Kumar Kumar, Manish Indian Inst Informat Technol Dept Informat Technol Network Secur & Cryptog Lab 4311 Comp Ctr 2 Allahabad 211012 Uttar Pradesh India Indian Inst Informat Technol Dept Informat Technol Comp Ctr 2 Allahabad 211012 Uttar Pradesh India

Energy conservation in resource constrained wireless sensor networks (WSNs) is an important concern. Techniques such as, energy conserving MAC protocols have been proved to be efficient to minimize the energy consumption in such networks. However, techniques based on in-network data compression have dominated recent research works for reducing the network traffic thereby improving the network lifetime. A large number of compression techniques have been proposed in recent years with diverse applications in WSNs. This work presents a comprehensive analysis of various existing in-network data processing techniques based on compressed sensing in WSNs. The essential features, requirements and characteristics of compression algorithms in WSNs, are discussed in detail with a classification of existing algorithms into different categories. A set of parameters are identified for a comparative evaluation of these algorithms to determine the efficacy of such in-network data processing techniques in an environment such as a WSN.

关键词： Compressed sensing Energy conservation in-network data processing network lifetime Wireless sensor networks

来源：评论

学校读者我要写书评

暂无评论

Subjective Logic-Based in-network data processing for Trust Management in Collocated and Distributed Wireless Sensor networks

引用

IEEE SENSORS JOURNAL 2018年第15期18卷 6446-6460页

作者： Firoozi, Farhad Zadorozhny, Vladimir, I Li, Frank Y. Univ Agder Dept Informat & Commun Technol N-4898 Grimstad Norway Univ Pittsburgh Sch Informat Sci Pittsburgh PA 15260 USA

While analyzing an explosive amount of data collected in today's wireless sensor networks (WSNs), the redundant information in the sensed data needs to be handled. in-network data processing is a technique which can eliminate or reduce such redundancy, leading to minimized resource consumption. On the other hand, trust management techniques establish trust relationships among nodes and detect unreliable nodes. In this paper, we propose two novel in-network data processing schemes for trust management in static WSNs. The first scheme targets at networks, where sensor nodes are closely collocated to report the same event. Considering both spatial and temporal correlations, this scheme generates trustworthiness for each sensor node-based solely on the data reported by the sensor. The second scheme is designed for networks, where sensor nodes are randomly distributed to sense ongoing events. This scheme produces node trustworthiness considering the variations in node observations. In addition, we propose an energy saving mode to reduce energy consumption and/or increase the reliability of a network. For trust generation, we employ a subjective logic-based scheme to mitigate trust fluctuations caused by various factors. Extensive simulations based on four scenarios are performed to evaluate the effectiveness of our proposed schemes.

关键词： Wireless sensor networks (WSNs) in-network data processing trust management subjective logic

来源：评论

学校读者我要写书评

暂无评论

A Programmable data Plane to Support in-network data processing in Software-Defined IoT 8

A Programmable Data Plane to Support In-network Data Process...

引用

International Conference on Information and Communication Technology Convergence (ICTC)

作者： Kim, Ki-Wook Min, Sung-Gi Han, Youn-Hee Korea Univ Dept Comp & Radio Commun Engn Seoul South Korea Korea Univ Technol & Educ Sch Comp Sci & Engn Cheonan South Korea

ISBN: (纸本)9781509040322

Making the data plane of a SDN flexible enough to satisfy the various requirements of heterogeneous IoT applications is very desirable for Software Defined IoT (SD-IoT) networking. The network device having programmable data plane provides an ability to add new packet and data processing procedures dynamically to the IoT applications. Previously proposed solutions for adding programmability to the SDN data plane provide extensibility for packet forwarding operations for new protocols, but IoT applications need more flexible programmability for in-network data processing operations e.g. data aggregation of sensing data from thousands of sensor nodes. Moreover, some IoT models such as OMG DDS, oneM2M, and Eclipse SCADA use publish-subscribe model, which is difficult to represent with the operations of existing message-centric data plane models. We introduce a new in-network data processing scheme for SD-IoT data plane. It defines an event-driven data processing model that can express various in-network data processing cases in the SD-IoT environment. It also proposes a language to program the data processing procedures using the model, and presents a flexible data plane structure that can install and execute the programs at runtime. We demonstrated flexibility of the proposing scheme with sample programs for some example SD-IoT cases.

关键词： Software-Defined IoT Programmable data Plane in-network data processing

来源：评论

学校读者我要写书评

暂无评论

in-network data processing Architecture for Energy Efficient Wireless Sensor networks 2

In-Network Data Processing Architecture for Energy Efficient...

引用

2015 IEEE 2nd World Forum on Internet of Things (WF-IoT)

作者： He, Weiwei Yang, Shuang-Hua Yang, Lili Li, Ping Univ Loughborough Dept Comp Sci Loughborough LE11 3TU Leics England Univ Loughborough Sch Business & Econ Loughborough LE11 3TU Leics England Liaoning Shihua Univ Sch Informat & Control Engn Fushun Peoples R China

ISBN: (纸本)9781509003662

In traditional WSNs, the sensor nodes are used only for capturing data, which is analyzed in a centralized base station. This requires a continuous communication but wastes the energy of sensor nodes and results in a reduction of the overall network lifetime. In this paper, we proposed an in-network data processing architecture to improve the energy efficiency and the scalability and the accuracy of sensor networks. We also adapted a data mining algorithm to process data for matching a specific event. The simulations show a reduction in energy consumption and an improvement in data accuracy.

关键词： in-network data processing Wireless Sensor network data compression Event detection

来源：评论

学校读者我要写书评

暂无评论

Time-selective data fusion for in-network processing in ad hoc wireless sensor networks

引用

INTERNATIONAL JOURNAL OF DISTRIBUTED SENSOR networkS 2018年第11期14卷 1-1页

作者： Kaugerand, Jaanus Ehala, Johannes Motus, Leo Preden, Jurgo-Soren Tallinn Univ Technol Res Lab Proact Technol Ehitajate Tee 5 EE-19086 Tallinn Estonia Thinnect Inc Sunnyvale CA USA

This article introduces a time-selective strategy for enhancing temporal consistency of input data for multi-sensor data fusion for in-network data processing in ad hoc wireless sensor networks. Detecting and handling complex time-variable (real-time) situations require methodical consideration of temporal aspects, especially in ad hoc wireless sensor network with distributed asynchronous and autonomous nodes. For example, assigning processing intervals of network nodes, defining validity and simultaneity requirements for data items, determining the size of memory required for buffering the data streams produced by ad hoc nodes and other relevant aspects. The data streams produced periodically and sometimes intermittently by sensor nodes arrive to the fusion nodes with variable delays, which results in sporadic temporal order of inputs. Using data from individual nodes in the order of arrival (i.e. freshest data first) does not, in all cases, yield the optimal results in terms of data temporal consistency and fusion accuracy. We propose time-selective data fusion strategy, which combines temporal alignment, temporal constraints and a method for computing delay of sensor readings, to allow fusion node to select the temporally compatible data from received streams. A real-world experiment (moving vehicles in urban environment) for validation of the strategy demonstrates significant improvement of the accuracy of fusion results.

关键词： Time-selective data fusion in-network data processing data validity data alignment data simultaneity wireless ad hoc sensor networks situation awareness middleware

来源：评论

学校读者我要写书评

暂无评论

Energy-efficient collection of wearable sensor data through predictive sampling

引用

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

来源：评论

学校读者我要写书评

暂无评论

Lightweight, latency-aware routing for data compression in wireless sensor networks with heterogeneous traffics

引用

WIRELESS COMMUNICATIONS & MOBILE COMPUTING 2016年第9期16卷 1035-1049页

作者： Wang, You-Chiun Wei, Chia-Ting Natl Sun Yat Sen Univ Dept Comp Sci & Engn 70 Lienhai Rd Kaohsiung 80424 Taiwan

In many applications and scenarios, sensors have to regularly report what they monitor from the environment and quickly notify the sink node of event occurrence in the sensing field. An in-network data reduction technique, such as data aggregation and data compression, can help diminish the amount of data sent from sensors, which not only saves the network bandwidth but also preserves sensors' energy. However, such technique does not consider packet latency because of the aggregation or compression operation. When some sensors generate regular reports in lower data rates, their packets have to spend longer time to be aggregated or compressed, resulting in higher packet delays. Besides, when events occur, the network could suffer from instant congestion due to the generation of numerous event notifications. Motivated with the aforementioned observations, the paper develops a lightweight, latency-aware routing for data compression (L2DC) scheme to reduce packet latency when applying the compression technique, to reduce the amount of data generated from sensors. L2DC gives event notifications a higher priority over regular reports and eliminates unnecessary notifications to avoid bursty network congestion. In addition, L2DC facilitates the data compression process by allowing each sensor to determine whether to keep packets for compression locally or to send them to a neighbor to be compressed in a distributed manner. Our L2DC scheme can be easily built on most ad hoc and sensor routing protocols because it provides auxiliary redundant packet elimination and relay node selection mechanisms to reduce packet latency. By using the ad hoc on-demand distance vector protocol as the example, simulation results demonstrate the effectiveness of the L2DC scheme. Copyright (C) 2015 John Wiley & Sons, Ltd.

关键词： data aggregation and compression in-network data processing packet delay routing protocol wireless sensor network

来源：评论

学校读者我要写书评

暂无评论

Deployment and evaluation of a fully applicable distributed event detection system in Wireless Sensor networks

引用

AD HOC networkS 2016年第Part2期37卷 160-182页

作者： Dziengel, Norman Seiffert, Martin Ziegert, Marco Adler, Stephan Pfeiffer, Stefan Schiller, Jochen Free Univ Berlin Dept Math & Comp Sci D-14195 Berlin Germany

Versatility and real world applicability are key features of Wireless Sensor networks (WSNs). In order to achieve these benefits we have to face the challenges of high practical relevance during application. We deploy and evaluate the concrete example of a fence monitoring task to reveal how our distributed event detection system is able to perform under real application conditions. The challenge is to bring both opposing aspects-high event detection accuracy and long service life-into one applicable ubiquitous system. If sensor nodes compose parts of events cooperatively, a comprehensive event assessment with low energy demands is possible. We propose a classifier based distributed event detection system consisting of two frameworks. The evaluation framework delivers a classification model and enables the theoretical evaluation of a given training set. The distributed event detection framework subsequently applies the classification model to assess, filter and classify events within the network. We evaluate our system by training and detecting events with our WSN composed of 49 nodes which are integrated in construction site fence elements. We compare four different data application scenarios with varying data processing concepts and varying network sizes to analyze the resulting communication load as well as the system lifetime. We compare the results of our evaluation framework with the results of our application to show that the evaluation framework reflects the real world deployment results in a credible way. We show the full applicability of our approach by comparing the resulting increased event detection accuracy against our previous work. Compared to other information fusion scenarios, our distributed event detection system reduces energy consumption beyond a communication distance of two hops which yields a prolonged lifetime of the network while additionally achieving an improved event detection accuracy. (C) 2015 Elsevier B.V. All rights reserved.

关键词： Wireless sensor network Distributed event detection in-network data processing Pattern recognition Deployment

来源：评论

学校读者我要写书评

暂无评论

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

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

引用

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

来源：评论

学校读者我要写书评

暂无评论

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...

引用

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

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：