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2 edition of distributed framework for correlated data gathering in sensor networks. found in the catalog.

distributed framework for correlated data gathering in sensor networks.

Kevin Yuen

distributed framework for correlated data gathering in sensor networks.

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Published .
Written in English


About the Edition

We consider the problem of correlated data gathering in sensor networks. Existing solutions to this problem are impractical because they have not considered all of the following factors: (i) distributed implementation, (ii) capacity and interference associated with the shared-medium, and (iii) realistic data correlation model. In this thesis, we propose a new distributed framework to achieve minimum energy data gathering, while considering all three mentioned factors. The framework is first constructed with the assumption that the network has a single sink and perfect data correlation. Our work is then extended to where the network has multiple sinks with arbitrary data correlation. For both cases, the problem is first modeled as an optimization formulation. The formulation is then relaxed with Lagrangian dualization and solved with the subgradient algorithm. To evaluate its effectiveness, we have conducted extensive simulations. The results indicate that the algorithm supports asynchronous networks, sink mobility, and duty schedules.

The Physical Object
Pagination87 leaves.
Number of Pages87
ID Numbers
Open LibraryOL19214963M
ISBN 109780494161302

wireless sensor networks. The rest of this book is organized as follows. In Chapter 1, we address the several to model the spatiotemporal correlation in sensor networks and describes in detail as well as employ bandwidth re-use for data gathering and target tracking, researchers have designed one-to-many, many-to-one, one-to-any, or one. Special Issue "Data Collection in Wireless Sensor Networks (WSN) and Internet of Things (IoT)" but it is challenging to adaptively and effectively conduct appropriate switching between the two aforementioned data gathering modes. the data. The histogram-based data clustering (HDC) module groups temporal correlated data into clusters and. In large-scale and dense wireless sensor networks, sensor observations often are correlated and the correlation impacts overall network performance. Another performance limiting factor comes from the non-ideal nature of the wireless links between network nodes.


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distributed framework for correlated data gathering in sensor networks. by Kevin Yuen Download PDF EPUB FB2

CiteSeerX - Document Details (Isaac Councill, Lee Giles, Pradeep Teregowda): We consider the problem of correlated data gathering in sensor networks with multiple sink nodes. The problem has two objectives. First, we would like to find a rate allocation on the correlated sensor nodes such that the data gathered by the sink nodes can reproduce the field of observation.

CiteSeerX - Document Details (Isaac Councill, Lee Giles, Pradeep Teregowda): We consider the problem of correlated data gathering in sensor networks with multiple sink nodes.

The problem has two objectives. First, we would like to find a rate allocation on the correlated sensor nodes, such that the data gathered by the sink nodes can reproduce the field of observation.

framework. The ultimate purpose of this paper is to create a solution to the correlated data gathering problem that is practical for deployment.

More importantly, the framework should be compatible, allowing other energy-saving mechanisms to be built on top of the distributed framework for correlated data gathering in sensor networks.

book to further extend the lifetime of data gathering sensor networks. The author of the paper [16] considered the problem of correlated data gathering in sensor networks with multiple sink nodes and proposed a method with controlled sampling frequency.

However, it. We consider the problem of correlated data gathering in sensor networks with multiple sink nodes. The problem has two objectives. First, we would like to find a rate allocation on the correlated sensor nodes such that the data gathered by the sink nodes can reproduce the field of observation.

Second, we would like to find a transmission structure on the network graph such that the total Cited by: In this paper, we propose a new distributed framework to achieve minimum energy data gathering, while considering these three factors. Based on a localized version of Slepian-Wolf coding, the problem is modeled as an optimization formulation with a distributed : Kevin Yuen, Ben Liang and Baochun Li.

Also a distributed algorithm is proposed in [12] for minimum energy data gathering in sensor networks with multiple sinks using linear programming optimization method.

In this paper, we propose an effective distributed algorithm to solve the minimum energy data gathering (MEDG) problem in sensor networks with multiple sinks. The problem objective is to find a rate Cited by: Abstract We propose in this paper a novel scheme for correlated data gathering in energy- and bandwidth-limited wireless sensor networks based on Distributed Source Coding (DSC).

We develop a special Viterbi Algorithm, denoted as VA-DSC, for decoding of the sensor data encoded Author: HuaGuogang, ChenChang Wen. A distributed framework for correlated data gathering in sensor networks.

IEEE Trans. on Vehicular Technology, 57(1), Jan. Google Scholar Cross Ref. Data Gathering in Correlated Wireless Sensor Networks with Cooperative Transmission: /ch This chapter considers the problem of data gathering in correlated wireless sensor networks with distributed source coding (DSC), and virtual multiple inputAuthor: Laxminarayana S.

Pillutla, Vikram Krishnamurthy. Correlated Data Gathering on Dynamic Network Coding Policy and Opportunistic Routing in Wireless Sensor Network Chong Tan 1,Junni Zou,Min Wang1,Hongkai Xiong2 1Department of Communication Engineering, Shanghai University, Shanghai,P.R.

China 2Department of Electronic Engineering, Shanghai Jiao Tong University, ShanghaiP.R. China Emails: {dudumaotc, zoujn. cation helps the wireless sensor network to have a longer lifetime. The problem of deter-mining a set of active sensor nodes in a correlated data environment for a fully operational wireless sensor network can be formulated as an instance of the connected correlation-dominating set problem.

In this paper, we consider mobile data gathering in wireless sensor networks (WSNs) by using a mobile collector with multiple antennas. By taking into acco A distributed optimal framework for mobile data gathering with concurrent data uploading in wireless sensor networks - Cited by: Advances in sensor technology and computer networks have enabled distributed sensor networks (DSNs) to evolve from small clusters of large sensors to large swarms of micro-sensors, from fixed sensor nodes to mobile nodes, from wired communications to wireless communications, from static network topology to dynamically changing by: Global Correlated Data Gathering in Wireless Sensor Networks with Compressive Sensing and Randomized Gossiping Yifeng Li 1,Junni Zou,Hongkai Xiong2 1Department of Communication Engineering, Shanghai University, Shanghai,P.R.

China 2Department of Electronic Engineering, Shanghai Jiao Tong University, ShanghaiP.R. China Emails: {wind. Wireless sensor networks (WSNs) consist of large numbers of sensor nodes where data from different nodes in a dense region may be highly correlated.

For example, if the data are temperature measurements, the measurements are spatially and temporally correlated across the by: Lifetime Optimization for Wireless Sensor Networks with Correlated Data Gathering Nashat Abughalieh¹, Yann-Aël Le Borgne¹ ², Kris Steenhaut¹ ³, Ann Nowé² ¹Vrije Universiteit Brussel - ETRO ²Vrije Universiteit Brussel - COMO ³Erasmus hogeschool Brussel - IWT Brussels, Belgium Emails: {nabughal, yleborgn, ksteenha, }@ We consider the problem of gathering correlated sensor data by a sink node in a wireless sensor network.

We design efficient distributed protocols to maximize the network lifetime subject to nodal energy constraints. Many existing approaches address the routing layer only, but the routing often interacts with physical-layer power control and MAC-layer link access. A Framework of Joint Mobile Energy Replenishment and Data Gathering in Wireless Rechargeable Sensor Networks Abstract: Recent years have witnessed the rapid development and proliferation of techniques on improving energy efficiency for wireless sensor by: ().

A Distributed Framework for Correlated Data Gathering in Sensor Networks. A Global-Energy-Balancing Real-time Routing in Wireless Sensor Networks; ().

A New Deterministic Data Aggregation Method for Wireless Sensor networks. Signal Process. wireless sensor network can choose among different distributed coding schemes to encode their data. We propose a framework where the network is described as a graph, with sensors repre-senting the nodes, and where communication and processing costs are associated to edge weights and the coding schemes associated to states of operation.

This paper outlines a proposition of a framework optimizing the communication scheme from the physical part of the transmitters to the data gathered at the receiver in a wireless sensor network.

We propose a coding scheme able to take into account the correlation between measurements obtained by Author: Dina Chaal, Asaad Chahboun, Frédéric Lehmann, Abdelouahid Lyhyaoui. This paper presents the first complete design to apply compressive sampling theory to sensor data gathering for largescale wireless sensor networks.

The successful scheme developed in this research is expected to offer fresh frame of mind for research in both compressive sampling applications and large-scale wireless sensor networks.

We consider the scenario in which a [ ]Cited by:   / A distributed compressive sensing technique for data gathering in Wireless Sensor Networks. The 4th International Conference on Emerging Ubiquitous Systems and Pervasive Networks, EUSPN Amsterdam: Elsevier, pp.

(Procedia Computer Science).Cited by: A distributed framework for correlated data gathering in sensor networks[J]. IEEE Transaction on Vehicular Technology,57(1): DOI: /tvtCited by: 2. efficiency of source coding in a sensor network can be potenti ally improved via distributed techniques by leveraging the fact that signals measured by different nodes are correlated.

In this paper, a data gathering protocol for multihop wireless sensor networks with energy harvesting capabilities is studiedFile Size: KB.

With increasing popularity and applicability of wireless sensor networks, the limitations which restrict the lifetime of network are also arising. It is observed that the energy utilized in transmission is more than processing the data in wsn.

So, many approaches are proposed to tackle the problem of power consumption, used while transmission. One of the approaches include the compression of. We propose a novel approach to reducing energy consumption in sensor networks using a distributed adaptive signal processing framework and efficient algori A distributed and adaptive signal processing approach to reducing energy consumption in sensor networks - IEEE Conference Publication.

sensor node sensor node Data Gathering Node query data query data Fig. An example sensor network: a computer acts as the data gathering node, and queries various sensors to collect data compute power, but the constructions introduced in this paper can be easily strengthened given greater compute power at the sensors.

The area of communication and protocol design for Wireless Sensor Networks (WSNs) has been widely researched in the past few years. One of the first studies addressing the problem of efficiently gathering correlated data from a wide network deployment is [1], which highlights the interdependence.

Cross Layer Protocol Suite for Correlated Data Gathering in Wireless Sensor Networks. Publications. S.-J. Park, Y. Zhu, R. Vedantham and R. Sivakumar, "A scalable correlation aware aggregation strategy for wireless sensor networks," in IEEE International Conference on Wireless Internet (WICON), Budapest, Hungary, M.

Sartipi and F. Fekri, "Distributed Source Coding in Wireless Sensor. general where sensor networks are treated as one application and some results can be easily applied to sensor networks as special cases.

In [57], the application of CS for compressed data gathering, distributed compression and source localization has been briefly reviewed under the general topic of CS for communications and Size: 1MB.

Security problem is one of the most popular research fields in wireless sensor networks for both the application requirement and the resource-constrained essence. An effective and lightweight Authentication and Key Management Scheme (AKMS) is proposed in this paper to solve the problem of malicious nodes occurring in the process of networking and to offer a high level of security with low by: 4.

1) Compressive Data Gathering In a Perfect Network: They first evaluate the performance of compressive data gathering when the network is perfect: neither broken links nor outlying sensor readings exist in the network.

Fig The ARE of the three algorithms Fig.4(a) is without the random noise case, (b) is with the random noise case. In this context, we consider two different, but complimentary, schemes for aggregating correlated data in wireless sensor networks that specifically target near and far term correlation respectively.

The two schemes broadly fall under the classification of distributed source coding (DSC) and data gathering. In “Novel Energy-Efficient Data Gathering Scheme Exploiting Spatial-Temporal Correlation for Wireless Sensor Networks,” Y. Zhou et al., from Nanjing University of Posts and Telecommunications, Nanjing, China, propose an energy-efficient data gathering scheme exploiting both spatial and temporal correlations for clustered : Mile K.

Stojcev, Zoran Stamenkovic, Bojan Dimitrijevic. Review Wireless Sensor Networks for Big Data Systems Beom-Su Kim 1, Ki-Il Kim 1,* ID, Babar Shah 2, Francis Chow 3 and Kyong Hoon Kim 4 1 Department of Computer Science and Engineering, Chungnam National University, DaejeonKorea; [email protected] or [email protected] 2 College of Technological Innovation, Zayed University, Abu DhabiUAE; @d by: 3.

The focus of the project is on the design and development of cross-layer solutions to improve the data gathering performance of wireless sensor networks (WSNs) in the presence of correlated sensing information. The scope of the research spans the physical, the link, the routing and the transport layer functionalities, respectively.

Introduction. Data collection is a fundamental application of wireless sensor networks (WSNs). For example, in the environmental monitoring scenario, the physical quantities, such as temperature, humidity and light illumination, etc. are usually sensed and transmitted from sensor nodes to sink nodes through multi-hop routing [].Since the sensor nodes usually have limited computing ability Cited by:.

Integrated Source-Channel Decoding for Correlated Data-Gathering Sensor Networks Sheryl L. Howard found in multi-hop wireless data-gathering sensor networks. I. INTRODUCTION is the development of practical distributed source codes for correlated measurements (see .Research Article Energy-Efficient Data Gathering Scheme Based on Broadcast Transmissions in Wireless Sensor Networks SoobinLee 1 andHowonLee 2 Institute for IT Convergence, KAIST, Yuseong-gu, Daejeon - Republic of Korea Department of Electrical, Electronic and Control Engineering, Hankyong National University, Anseong, Gyeonggi - Republic of.Designing and operating sensor networks, featuring leading researchers and the latest, yet unpublished findings.

Sensor Network Operations introduces mission-oriented sensor networks as distributed dynamic systems of interacting sensing devices, which function as a network to execute complex real-time missions. Rapidly developing and much in demand, these smart systems offer novel solutions to.