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Wireless Sensor Network Technologies for Information Explosion Era The amount and value of information available due to rapid spread of information technology is exploding. Typically, large enterprises have approximately a petabyte of operational data stored in hundreds of data repositories supporting thousands of applications. Data storage volumes grow in excess of 50% annually. This growth is expected to continue due to vast proliferation of existing infor- tion systems and the introduction of new data sources. Wireless Sensor Networks (WSNs) represent one of the most notable examples of such new data sources. In recent few years, various types of WSNs have been deployed and the amount of information generated by wireless sensors increases rapidly. The information - plosion requires establishing novel data processing and communication techniques for WSNs. This volume aims to cover both theoretical and practical aspects - lated to this challenge, and it explores directions for future research to enable ef- cient utilization of WSNs in the information-explosion era. The book is organized in three main parts that consider (1) technical issues of WSNs, (2) the integration of multiple WSNs, and (3) the development of WSNs systems and testbeds for conducting practical experiments. Each part consists of three chapters.
The LNCS journal Transactions on Large-Scale Data- and Knowledge-Centered Systems focuses on data management, knowledge discovery, and knowledge processing, which are core and hot topics in computer science. Since the 1990s, the Internet has become the main driving force behind application development in all domains. An increase in the demand for resource sharing across different sites connected through networks has led to an evolution of data- and knowledge-management systems from centralized systems to decentralized systems enabling large-scale distributed applications providing high scalability. Current decentralized systems still focus on data and knowledge as their main resource. Feasibility of these systems relies basically on P2P (peer-to-peer) techniques and the support of agent systems with scaling and decentralized control. Synergy between grids, P2P systems, and agent technologies is the key to data- and knowledge-centered systems in large-scale environments. This volume, the 32nd issue of Transactions on Large-Scale Data- and Knowledge-Centered Systems, focuses on Big Data Analytics and Knowledge Discovery, and contains extended and revised versions of five papers selected from the 17th International Conference on Big Data Analytics and Knowledge Discovery, DaWaK 2015, held in Valencia, Spain, during September 1-4, 2015. The five papers focus on the exact detection of information leakage, the binary shapelet transform for multiclass time series classification, a discrimination-aware association rule classifier for decision support (DAAR), new word detection and tagging on Chinese Twitter, and on-demand snapshot maintenance in data warehouses using incremental ETL pipelines, respectively. discovery,="" contains="" extended="" revised="" versions="" five="" papers="" selected="" from="" 17th="" international="" conference="" discovery="" (dawak="" 2015),="" held="" in="" valencia,="" spain,="" during="" september="" 1-4,="" 2015.="" focus="" exact="" detection="" information="" leakage,="" binary="" shapelet="" transform="" for="" multiclass="" time="" series="" classification,="" a="" discrimination-aware="" association="" rule="" classifier="" decision="" support="" (daar),="" new="" word="" tagging="" chinese="" twitter,="" on-demand="" snapshot="" maintenance="" warehouses="" using="" incremental="" etl="" pipelines,="" respectively.
This book describes the main ideas, methods, results and resources relevant to the study of bionanosensor networks. Its primary goal is to spark application-oriented studies of molecular communication; that is, to investigate how collections of bionanosensors, referred to here as bionanosensor networks, can be used for practical purposes such as nanomedical sensing. In particular, the book focuses on two key functionalities for nanomedical applications: target detection and target tracking. Bionanosensor networks represent a new interdisciplinary research area that expands the traditional area of network engineering by incorporating the latest advances in bionanotechnology. These networks consist of spatially distributed bionanosensors that are engineered with the help of bionanotechnology. As a research area, bionanosensor networks are aimed at designing robust networks on the basis of spatially distributed bionanosensors, as well as at developing innovative applications of those networks.
Wireless Sensor Network Technologies for Information Explosion Era The amount and value of information available due to rapid spread of information technology is exploding. Typically, large enterprises have approximately a petabyte of operational data stored in hundreds of data repositories supporting thousands of applications. Data storage volumes grow in excess of 50% annually. This growth is expected to continue due to vast proliferation of existing infor- tion systems and the introduction of new data sources. Wireless Sensor Networks (WSNs) represent one of the most notable examples of such new data sources. In recent few years, various types of WSNs have been deployed and the amount of information generated by wireless sensors increases rapidly. The information - plosion requires establishing novel data processing and communication techniques for WSNs. This volume aims to cover both theoretical and practical aspects - lated to this challenge, and it explores directions for future research to enable ef- cient utilization of WSNs in the information-explosion era. The book is organized in three main parts that consider (1) technical issues of WSNs, (2) the integration of multiple WSNs, and (3) the development of WSNs systems and testbeds for conducting practical experiments. Each part consists of three chapters.
This book constitutes the refereed proceedings of the 18th International Conference on Data Warehousing and Knowledge Discovery, DaWaK 2016, held in Porto, Portugal, September 2016. The 25 revised full papers presented were carefully reviewed and selected from 73 submissions. The papers are organized in topical sections on Mining Big Data, Applications of Big Data Mining, Big Data Indexing and Searching, Big Data Learning and Security, Graph Databases and Data Warehousing, Data Intelligence and Technology.
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.
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