C Shoba Bindu

Ce livre est publi pour r pondre aux besoins acad miques et de recherche en mati re de cloud computing. Le cloud computing est apparu comme le paradigme de l'informatique distribu e, qui fournit aux utilisateurs un norme pool de ressources informatiques partag es comme le stockage, la m moire, les r seaux, les applications et la puissance de traitement. En fonction de la demande, ils peuvent fournir et lib rer les ressources selon leurs besoins en ne payant que pour le nombre de ressources qu'ils utilisent. Ce livre se concentre principalement sur les concepts de base (par exemple, la question de la s curit dans les nuages) et les sujets de recherche avanc e.

Este Livro lan ado para abordar as necessidades acad micas e de investiga o na computa o em nuvem. A computa o em nuvem surgiu como o paradigma da computa o distribu da, que fornece um enorme conjunto de recursos inform ticos partilhados, como armazenamento, mem ria, redes, aplica es, e poder de processamento aos utilizadores. Com base na procura, eles podem fornecer e libertar os recursos tal como s o necess rios, pagando apenas pelo n mero de recursos que utilizam. Este livro concentra-se principalmente em conceitos centrais (ou seja, quest o de seguran a na nuvem) e t picos avan ados de investiga o.

Questo libro stato pubblicato per rispondere alle esigenze accademiche e di ricerca sul cloud computing. Il cloud computing emerso come paradigma di calcolo distribuito, che mette a disposizione degli utenti un enorme pool di risorse informatiche condivise, come storage, memoria, reti, applicazioni e potenza di elaborazione. In base alla domanda, gli utenti possono fornire e rilasciare le risorse secondo le loro necessit , pagando solo per il numero di risorse utilizzate. Questo libro si concentra principalmente sui concetti fondamentali (ad esempio, il problema della sicurezza nel cloud) e su argomenti di ricerca avanzati.

Dieses Buch wird ver ffentlicht, um den akademischen und Forschungsbedarf im Bereich Cloud Computing zu decken. Cloud Computing hat sich zu einem Paradigma der verteilten Datenverarbeitung entwickelt, das den Nutzern einen riesigen Pool gemeinsam genutzter Datenverarbeitungsressourcen wie Speicher, Arbeitsspeicher, Netzwerke, Anwendungen und Rechenleistung zur Verf gung stellt. Je nach Bedarf k nnen sie die Ressourcen bereitstellen und freigeben, wobei sie nur f r die Anzahl der genutzten Ressourcen bezahlen. Dieses Buch konzentriert sich vor allem auf Kernkonzepte (z. B. Sicherheitsfragen in der Cloud) und fortgeschrittene Forschungsthemen.

This Book is released to address the academic and research needs in cloud computing. Cloud computing has emerged as the distributed computing paradigm, that provides an enormous pool of shared computing resources like storage, memory, networks, applications, and processing power to the users. Based on the demand, they may provide and release the resources as they required by paying only for the number of resources they utilized. This book majorly concentrated on core concepts (i.e. security issue in cloud) and advanced research topics.

The tremendous growth of data due to Internet and electronic commerce has created serious challenges to the researches in pattern recognition. There is a need of processing and analysing data. Advances in data mining and knowledge discovery provide the requirement of new approaches to reduce the data. The reduction of data is an important problem that attracts the eyes of researches in pattern recognition. The reduction of data is the core problem in classifiers especially for Nearest Neighbor Classifier since it stores the entire training set for classifying the query patterns and also the classifier needs to compute the distances between the query pattern and each and every pattern from the stored training set. Hence the time and space requirements are high for Nearest Neighbor Classifier. In this book, methods are proposed to overcome the computational requirements of Nearest Neighbor Classifier. This book explores some of the possible remedies to overcome the problems with Nearest Neighbor based classifiers. The main disadvantages of Nearest Neighbor Classifier can be avoided using the proposed methods in this book.

Nowadays, the number of wireless users accessing the Internet is increasing day by day and each user wants to experience better performance. The IEEE 802.11 based wireless mesh network is the promising technology to provide wireless broadband Internet connectivity to the wireless users. In order to access the Internet through the pre-deployed WMN, the user has to associate with one of the mesh access points present in the WMN. The user performance majorly depends on the access point with which he/she is associated with and hence the access point selection problem is considered as critical in the context of WMN. This research work is focused on the problem of how to select the best access point that provides the best quality of service to the user.

Data has increased due to the growing use of web applications and communication devices. It is necessary to develop new techniques of managing data in order to ensure adequate usage.Modern Technologies for Big Data Classification and Clustering is an essential reference source for the latest scholarly research on handling large data sets with conventional data mining and provide information about the new technologies developed for the management of large data. Featuring coverage on a broad range of topics such as text and web data analytics, risk analysis, and opinion mining, this publication is ideally designed for professionals, researchers, and students seeking current research on various concepts of big data analytics.Topics Covered:The many academic areas covered in this publication include, but are not limited to:Data visualizationDistributed Computing SystemsOpinion MiningPrivacy and securityRisk analysisSocial Network AnalysisText Data AnalyticsWeb Data Analytics