Data Management In Pervasive Systems
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Data Management in Pervasive Systems
This book contributes to illustrating the methodological and technological issues of data management in Pervasive Systems by using the DataBenc project as the running case study for a variety of research contributions: sensor data management, user-originated data operation and reasoning, multimedia data management, data analytics and reasoning for event detection and decision making, context modelling and control, automatic data and service tailoring for personalization and recommendation. The book is organized into the following main parts: i) multimedia information management; ii) sensor data streams and storage; iii) social networks as information sources; iv) context awareness and personalization. The case study is used throughout the book as a reference example.
Pervasive Computing
Pervasive Computing: Next Generation Platforms for Intelligent Data Collection presents current advances and state-of-the-art work on methods, techniques, and algorithms designed to support pervasive collection of data under ubiquitous networks of devices able to intelligently collaborate towards common goals. Using numerous illustrative examples and following both theoretical and practical results the authors discuss: a coherent and realistic image of today's architectures, techniques, protocols, components, orchestration, choreography, and developments related to pervasive computing components for intelligently collecting data, resource, and data management issues; the importance of data security and privacy in the era of big data; the benefits of pervasive computing and the development process for scientific and commercial applications and platforms to support them in this field. Pervasive computing has developed technology that allows sensing, computing, and wireless communication to be embedded in everyday objects, from cell phones to running shoes, enabling a range of context-aware applications. Pervasive computing is supported by technology able to acquire and make use of the ubiquitous data sensed or produced by many sensors blended into our environment, designed to make available a wide range of new context-aware applications and systems. While such applications and systems are useful, the time has come to develop the next generation of pervasive computing systems. Future systems will be data oriented and need to support quality data, in terms of accuracy, latency and availability. Pervasive Computing is intended as a platform for the dissemination of research efforts and presentation of advances in the pervasive computing area, and constitutes a flagship driver towards presenting and supporting advanced research in this area. Indexing: The books of this series are submitted to EI-Compendex and SCOPUS - Offers a coherent and realistic image of today's architectures, techniques, protocols, components, orchestration, choreography, and development related to pervasive computing - Explains the state-of-the-art technological solutions necessary for the development of next-generation pervasive data systems, including: components for intelligently collecting data, resource and data management issues, fault tolerance, data security, monitoring and controlling big data, and applications for pervasive context-aware processing - Presents the benefits of pervasive computing, and the development process of scientific and commercial applications and platforms to support them in this field - Provides numerous illustrative examples and follows both theoretical and practical results to serve as a platform for the dissemination of research advances in the pervasive computing area
Wireless Sensor Networks and Applications
Author: Yingshu Li
language: en
Publisher: Springer Science & Business Media
Release Date: 2008-02-10
Wireless sensor networks are being employed in a variety applications ra- ing from medical to military, and from home to industry. The principle aim of this book is to provide a reference tool for the increasing number of scientists who depend upon sensor networks in some way. The book is organized into several sections, each including chapters exploring a speci?c topic. Wireless sensor networks are attracting great attention and there are many research topics yet to be studied. In this book, the topics covered include n- work design and modelling, network management, data management, security and applications. The articles presented in the book are expository, but of a scholarly nature, including the appropriate history background, a review of the state-of-the-art thinking relative to the topic, as well as a discussion of unsolved problems that are of special interest. The target readers of this book include the researchers in computer s- ence, computer engineering, and applied mathematics, as well as students in these subjects. Specialists as well as general readers will ?nd the articles st- ulating and helpful. Book Organization The book is organized into ?ve sections. Section I introduces the design and modelling of sensor networks. Chapter 1, by Iyer, Kulkarni, Mhatre, and Rosenberg, presents a taxonomy of wireless sensor networks, based on their application level objectives, tra–c characteristics and data delivery requi- ments. Popa and Lewis in Chapter 2 describe some algorithms for systematic exploration of unknown environments using a mobile wireless sensor network.