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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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