Data Management And Data Analysis Techniques For Wireless Sensor Networks

Data Management and Data Analysis Techniques for Wireless Sensor Networks

Wireless Sensor Networks and Applications

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.

Learning from Data Streams

Sensor networks consist of distributed autonomous devices that cooperatively monitor an environment. Sensors are equipped with capacities to store information in memory, process this information and communicate with their neighbors. Processing data streams generated from wireless sensor networks has raised new research challenges over the last few years due to the huge numbers of data streams to be managed continuously and at a very high rate. The 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. The set of chapters covers the state-of-art in data stream mining approaches using clustering, predictive learning, and tensor analysis techniques, and applying them to applications in security, the natural sciences, and education. This research monograph delivers to researchers and graduate students the state of the art in data stream processing in sensor networks. The huge bibliography offers an excellent starting point for further reading and future research.