Download or read book Resource aware Data Stream Classification in Wireless Sensor Networks written by Ary Mazharuddin Shiddiqi and published by . This book was released on 2009 with total page 144 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Learning from Data Streams written by João Gama and published by Springer Science & Business Media. This book was released on 2007-10-11 with total page 486 pages. Available in PDF, EPUB and Kindle. Book excerpt: Processing data streams has raised new research challenges over the last few years. This book provides the reader with a comprehensive overview of stream data processing, including famous prototype implementations like the Nile system and the TinyOS operating system. Applications in security, the natural sciences, and education are presented. The huge bibliography offers an excellent starting point for further reading and future research.

Download or read book Fast Data Streaming in Resource Constrained Wireless Sensor Networks written by and published by . This book was released on 2008 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: In many emerging applications, data streams are monitored in a network environment. Due to limited communication bandwidth and other resource constraints, a critical and practical demand is to online compress data streams continuously with quality guarantee. Although many data compression and digital signal processing methods have been developed to reduce data volume, their super-linear time and more-than-constant space complexity prevents them from being applied directly on data streams, particularly over resource-constrained sensor networks. In this thesis, we tackle the problem of online quality guaranteed compression of data streams using fast linear approximation (i.e., using line segments to approximate a time series). Technically, we address two versions of the problem which explore quality guarantees in different forms. We develop online algorithms with linear time complexity and constant cost in space. Our algorithms are optimal in the sense that they generate the minimum number of segments that approximate a time series with the required quality guarantee. To meet the resource constraints in sensor networks, we also develop a fast algorithm which creates connecting segments with very simple computation. The low cost nature of our methods leads to a unique edge on the applications of massive and high speed streaming environment, low bandwidth networks, and heavily constrained nodes in computational power (e.g., tiny sensor nodes). We implement and evaluate our methods in the application of an acoustic wireless sensor network.

Download or read book Fast Data Streaming in Resource Constrained Wireless Sensor Networks written by Emad Soroush and published by . This book was released on 2008 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: In many emerging applications, data streams are monitored in a network environment. Due to limited communication bandwidth and other resource constraints, a critical and practical demand is to online compress data streams continuously with quality guarantee. Although many data compression and digital signal processing methods have been developed to reduce data volume, their super-linear time and more-than-constant space complexity prevents them from being applied directly ondata streams, particularly over resource-constrained sensor networks. In this thesis, we tackle the problem of online quality guaranteed compression of data streams using fast linear approximation (i.e., using line segments to approximate a time series). Technically, we address two versions of the problem which explore quality guarantees in different forms. We develop online algorithms with linear time complexity and constant cost in space. Our algorithms are optimal in the sense that they generate the minimum number of segments that approximate a time series with the required quality guarantee. To meet the resource constraints in sensor networks, we also develop a fast algorithm which creates connecting segments with very simple computation. The low cost nature of our methods leads to a unique edge on the applications of massive and high speed streaming environment, low bandwidth networks, and heavily constrained nodes in computational power (e.g., tiny sensor nodes). We implement and evaluate our methods in the application of an acoustic wireless sensor network.

Download or read book A Reliable and Resource Aware Framework for Data Dissemination in Wireless Sensor Networks written by Vasu Jolly and published by . This book was released on 2005 with total page 430 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Big Data Analytics and Knowledge Discovery written by Sanjay Madria and published by Springer. This book was released on 2015-08-09 with total page 419 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the refereed proceedings of the 17th International Conference on Data Warehousing and Knowledge Discovery, DaWaK 2015, held in Valencia, Spain, September 2015. The 31 revised full papers presented were carefully reviewed and selected from 90 submissions. The papers are organized in topical sections similarity measure and clustering; data mining; social computing; heterogeneos networks and data; data warehouses; stream processing; applications of big data analysis; and big data.

Download or read book The Internet of Things written by Ricardo Armentano and published by CRC Press. This book was released on 2017-10-16 with total page 448 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book provides a dual perspective on the Internet of Things and ubiquitous computing, along with their applications in healthcare and smart cities. It also covers other interdisciplinary aspects of the Internet of Things like big data, embedded Systems and wireless Sensor Networks. Detailed coverage of the underlying architecture, framework, and state-of the art methodologies form the core of the book.

Download or read book Algorithms and Protocols for Wireless Sensor Networks written by Azzedine Boukerche and published by John Wiley & Sons. This book was released on 2008-11-03 with total page 566 pages. Available in PDF, EPUB and Kindle. Book excerpt: A one-stop resource for the use of algorithms and protocols in wireless sensor networks From an established international researcher in the field, this edited volume provides readers with comprehensive coverage of the fundamental algorithms and protocols for wireless sensor networks. It identifies the research that needs to be conducted on a number of levels to design and assess the deployment of wireless sensor networks, and provides an in-depth analysis of the development of the next generation of heterogeneous wireless sensor networks. Divided into nineteen succinct chapters, the book covers: mobility management and resource allocation algorithms; communication models; energy and power consumption algorithms; performance modeling and simulation; authentication and reputation mechanisms; algorithms for wireless sensor and mesh networks; and algorithm methods for pervasive and ubiquitous computing; among other topics. Complete with a set of challenging exercises, this book is a valuable resource for electrical engineers, computer engineers, network engineers, and computer science specialists. Useful for instructors and students alike, Algorithms and Protocols for Wireless Sensor Networks is an ideal textbook for advanced undergraduate and graduate courses in computer science, electrical engineering,and network engineering.

Download or read book Learning from Data Streams written by João Gama and published by . This book was released on 2007 with total page 143 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Machine Learning and Data Mining in Pattern Recognition written by Petra Perner and published by Springer. This book was released on 2011-08-12 with total page 624 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the refereed proceedings of the 7th International Conference on Machine Learning and Data Mining in Pattern Recognition, MLDM 2011, held in New York, NY, USA. The 44 revised full papers presented were carefully reviewed and selected from 170 submissions. The papers are organized in topical sections on classification and decision theory, theory of learning, clustering, application in medicine, webmining and information mining; and machine learning and image mining.

Download or read book Advanced Methods for Knowledge Discovery from Complex Data written by Ujjwal Maulik and published by Springer Science & Business Media. This book was released on 2006-05-06 with total page 375 pages. Available in PDF, EPUB and Kindle. Book excerpt: The growth in the amount of data collected and generated has exploded in recent times with the widespread automation of various day-to-day activities, advances in high-level scienti?c and engineering research and the development of e?cient data collection tools. This has given rise to the need for automa- callyanalyzingthedatainordertoextractknowledgefromit,therebymaking the data potentially more useful. Knowledge discovery and data mining (KDD) is the process of identifying valid, novel, potentially useful and ultimately understandable patterns from massive data repositories. It is a multi-disciplinary topic, drawing from s- eral ?elds including expert systems, machine learning, intelligent databases, knowledge acquisition, case-based reasoning, pattern recognition and stat- tics. Many data mining systems have typically evolved around well-organized database systems (e.g., relational databases) containing relevant information. But, more and more, one ?nds relevant information hidden in unstructured text and in other complex forms. Mining in the domains of the world-wide web, bioinformatics, geoscienti?c data, and spatial and temporal applications comprise some illustrative examples in this regard. Discovery of knowledge, or potentially useful patterns, from such complex data often requires the - plication of advanced techniques that are better able to exploit the nature and representation of the data. Such advanced methods include, among o- ers, graph-based and tree-based approaches to relational learning, sequence mining, link-based classi?cation, Bayesian networks, hidden Markov models, neural networks, kernel-based methods, evolutionary algorithms, rough sets and fuzzy logic, and hybrid systems. Many of these methods are developed in the following chapters.

Download or read book Energy Efficient Wireless Sensor Networks written by Vidushi Sharma and published by CRC Press. This book was released on 2017-07-28 with total page 297 pages. Available in PDF, EPUB and Kindle. Book excerpt: The advances in low-power electronic devices integrated with wireless communication capabilities are one of recent areas of research in the field of Wireless Sensor Networks (WSNs). One of the major challenges in WSNs is uniform and least energy dissipation while increasing the lifetime of the network. This is the first book that introduces the energy efficient wireless sensor network techniques and protocols. The text covers the theoretical as well as the practical requirements to conduct and trigger new experiments and project ideas. The advanced techniques will help in industrial problem solving for energy-hungry wireless sensor network applications.

Download or read book Wireless Sensor Networks written by Jun Zheng and published by John Wiley & Sons. This book was released on 2009-10-27 with total page 521 pages. Available in PDF, EPUB and Kindle. Book excerpt: Learn the fundamental concepts, major challenges, and effective solutions in wireless sensor networking This book provides a comprehensive and systematic introduction to the fundamental concepts, major challenges, and effective solutions in wireless sensor networking (WSN). Distinguished from other books, it focuses on the networking aspects of WSNs and covers the most important networking issues, including network architecture design, medium access control, routing and data dissemination, node clustering, node localization, query processing, data aggregation, transport and quality of service, time synchronization, network security, and sensor network standards. With contributions from internationally renowned researchers, Wireless Sensor Networks expertly strikes a balance between fundamental concepts and state-of-the-art technologies, providing readers with unprecedented insights into WSNs from a networking perspective. It is essential reading for a broad audience, including academic researchers, research engineers, and practitioners in industry. It is also suitable as a textbook or supplementary reading for electrical engineering, computer engineering, and computer science courses at the graduate level.

Download or read book Bandwidth aware Distributed Ad hoc Grids in Deployed Wireless Sensor Networks written by E. Rondini and published by . This book was released on 2010 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: Nowadays, cost effective sensor networks can be deployed as a result of a plethora of recent engineering advances in wireless technology, storage miniaturisation, consolidated microprocessor design, and sensing technologies. Whilst sensor systems are becoming relatively cheap to deploy, two issues arise in their typical realisations: (i) the types of low-cost sensors often employed are capable of limited resolution and tend to produce noisy data; (ii) network bandwidths are relatively low and the energetic costs of using the radio to communicate are relatively high. To reduce the transmission of unnecessary data, there is a strong argument for performing local computation. However, this can require greater computational capacity than is available on a single low-power processor. Traditionally, such a problem has been addressed by using load balancing: fragmenting processes into tasks and distributing them amongst the least loaded nodes. However, the act of distributing tasks, and any subsequent communication between them, imposes a geographically defined load on the network. Because of the shared broadcast nature of the radio channels and MAC layers in common use, any communication within an area will be slowed by additional traffic, delaying the computation and reporting that relied on the availability of the network. In this dissertation, we explore the tradeoff between the distribution of computation, needed to enhance the computational abilities of networks of resource-constrained nodes, and the creation of network traffic that results from that distribution. We devise an application-independent distribution paradigm and a set of load distribution algorithms to allow computationally intensive applications to be collaboratively computed on resource-constrained devices. Then, we empirically investigate the effects of network traffic information on the distribution performance. We thus devise bandwidth-aware task offload mechanisms that, combining both nodes computational capabilities and local network conditions, investigate the impacts of making informed offload decisions on system performance. The highly deployment-specific nature of radio communication means that simulations that are capable of producing validated, high-quality, results are extremely hard to construct. Consequently, to produce meaningful results, our experiments have used empirical analysis based on a network of motes located at UCL, running a variety of I/O-bound, CPU-bound and mixed tasks. Using this setup, we have established that even relatively simple load sharing algorithms can improve performance over a range of different artificially generated scenarios, with more or less timely contextual information. In addition, we have taken a realistic application, based on location estimation, and implemented that across the same network with results that support the conclusions drawn from the artificially generated traffic.

Download or read book Energy Aware and Adaptive Routing Protocols in Wireless Sensor Networks written by and published by . This book was released on 2004 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: Recent technological advances have enabled distributed micro-sensing for large scale information gathering through a network of tiny, low power devices or nodes equipped with programmable computing, multiple sensing and communication capabilities. This network of sensor nodes, known as a wireless sensor network, has revolutionized remote monitoring applications because of its ease of deployment, ad hoc connectivity and cost-effectiveness. In this dissertation, we design distributed routing protocols for minimizing energy consumption in a sensor network. There are two main contributions of this work. The first contribution is the design of an energy aware multiple path routing protocol to route heavy data traffic between a source and a destination node in a sensor network. The protocol spreads the routing load between the source and destination nodes over a large number of sensor nodes to minimize disparity in the energy levels of the sensor nodes. We also grade the multiple paths based on their route length to support time critical queries on the shortest available paths. The second contribution is the design of a communication architecture that supports distributed query processing to evaluate spatio-temporal queries within the network. We represent these queries by query trees and distribute query operators to appropriate sensor nodes. As operator execution demands high computation capability, we propose use of a heterogenous sensor network where query operators are assigned to sparsely deployed resource-rich nodes within a dense network of low power sensor nodes. We design an adaptive, decentralized, low communication overhead algorithm to determine an operator placement on the resource-rich nodes in the network to minimize cost of transmitting data in the routing tree constructed to continuously retrieve data from a set of spatially distributed geographical regions to the sink. To the best of our knowledge, this is the first attempt to build an energy aware routing infrastructure to enable in-network processing of spatio-temporal queries. In order to maximize energy savings the proposed multiple path routing protocol can be used to route data between the nodes that form the routing tree.

Download or read book Wireless Sensor Networks written by Kazem Sohraby and published by John Wiley & Sons. This book was released on 2007-04-06 with total page 325 pages. Available in PDF, EPUB and Kindle. Book excerpt: Infrastructure for Homeland Security Environments Wireless Sensor Networks helps readers discover the emerging field of low-cost standards-based sensors that promise a high order of spatial and temporal resolution and accuracy in an ever-increasing universe of applications. It shares the latest advances in science and engineering paving the way towards a large plethora of new applications in such areas as infrastructure protection and security, healthcare, energy, food safety, RFID, ZigBee, and processing. Unlike other books on wireless sensor networks that focus on limited topics in the field, this book is a broad introduction that covers all the major technology, standards, and application topics. It contains everything readers need to know to enter this burgeoning field, including current applications and promising research and development; communication and networking protocols; middleware architecture for wireless sensor networks; and security and management. The straightforward and engaging writing style of this book makes even complex concepts and processes easy to follow and understand. In addition, it offers several features that help readers grasp the material and then apply their knowledge in designing their own wireless sensor network systems: * Examples illustrate how concepts are applied to the development and application of * wireless sensor networks * Detailed case studies set forth all the steps of design and implementation needed to solve real-world problems * Chapter conclusions that serve as an excellent review by stressing the chapter's key concepts * References in each chapter guide readers to in-depth discussions of individual topics This book is ideal for networking designers and engineers who want to fully exploit this new technology and for government employees who are concerned about homeland security. With its examples, it is appropriate for use as a coursebook for upper-level undergraduates and graduate students.

Download or read book Towards a Data Quality aware Framework for Cloud based Sensor Services written by Victor John Lawson and published by . This book was released on 2016 with total page 244 pages. Available in PDF, EPUB and Kindle. Book excerpt: As the Internet of Things (IoT) paradigm gains popularity, the next few years will likely witness 'servitization' of domain sensing functionalities. In this setting, cloud-based eco-systems will exist in which high quality data from large numbers of independently-managed wireless sensor networks are shared or even traded in real-time. Such an eco-system will necessarily have multiple stakeholders such as sensor data providers, domain applications that utilize sensor data (data consumers), and cloud infrastructure providers who may collaborate as well as compete. Information systems that implement sensors as a service incorporate several major challenges. One such challenge is in the design, development, implementation and management of energy efficient dynamic green information systems. A second major challenge is to provide data streams with high data quality (DQ) to the consumer. A third challenge is to reduce the sensor energy usage and maintain energy efficiency of the sensors while providing dynamically adjustable smart sensors. A fourth challenge is to monitor and adjust the inherent tradeoff between the data quality of the data stream and the energy consumption of the sensor. A final challenge is in creating cloud services that handle the issues associated with the variety of mobile sensor devices including high volume flow, device tracking positioning and data control problems. Our work seeks to explore this tradeoff in detail by combining DQ services for the data stream consumer with customizable energy efficient "EE" throttling algorithms for the data feed producers. To address this issue, a multi-tiered cloud-service architecture called TAU-FIVE was designed and implemented. The technical contributions of this framework include data quality and energy efficiency models based on 7 DQ attributes implemented in a 5 tiered distributed system. This equilibrium is likely to impact energy awareness in the IoT as batch device data streams are integrated with the variety of social and professional networks in the Internet of Everything.