tailieunhanh - Ebook Data and computer communications (5th edition): Part 1

(BQ) Part 1 book "Data and computer communications" has contents: Data communications, data networking, and the internet; protocol architecture,tcp ip, and internet based applications; data transmission; transmission media; signal encoding techniques, digital data communication techniques; data link control protocols,. and other contents. | DATA AND COMPUTER COMMUNICATIONS Eighth Edition William Stallings Upper Saddle River, New Jersey 07458 Library of Congress Cataloging-in-Publication Data on File Vice President and Editorial Director, ECS: Marcia J. Horton Executive Editor: Tracy Dunkelberger Assistant Editor: Carole Snyder Editorial Assistant: Christianna Lee Executive Managing Editor: Vince O’Brien Managing Editor: Camille Trentacoste Production Editor: Rose Kernan Director of Creative Services: Paul Belfanti Creative Director: Juan Lopez Cover Designer: Bruce Kenselaar Managing Editor,AV Management and Production: Patricia Burns Art Editor: Gregory Dulles Director, Image Resource Center: Melinda Reo Manager, Rights and Permissions: Zina Arabia Manager,Visual Research: Beth Brenzel Manager, Cover Visual Research and Permissions: Karen Sanatar Manufacturing Manager, ESM: Alexis Heydt-Long Manufacturing Buyer: Lisa McDowell Executive Marketing Manager: Robin O’Brien Marketing Assistant: Mack Patterson ©2007 Pearson Education, Inc. Pearson Prentice Hall Pearson Education, Inc. Upper Saddle River, NJ 07458 All rights reserved. No part of this book may be reproduced in any form or by any means, without permission in writing from the publisher. Pearson Prentice Hall™ is a trademark of Pearson Education, Inc. All other tradmarks or product names are the property of their respective owners. The author and publisher of this book have used their best efforts in preparing this efforts include the development, research, and testing of the theories and programs to determine their author and publisher make no warranty of any kind, expressed or implied, with regard to these programs or the documentation contained in this author and publisher shall not be liable in any event for incidental or consequential damages in connection with, or arising out of, the furnishing, performance, or use of these programs. Printed in the United States of America 10 9 8 7 6 5 4 3 2 .

• Quản trị mạng
• Data and computer communication
• Luận văn Thạc sĩ
• Công nghệ thông tin
• Data communication
• Computer networks
• Cloud Fog system
• The problem of IoT
• International journal of computer science & communication networks
• Improved privacy of cloud storage data
• Using enhanced data access control scheme
• Multi authority cloud storage
• The authorized user
• The data access control
• Secure data access control
• Active groups in cloud data storage
• Data sharing model
• Sender friendly approach
• Diffe Hellman ciphering exchanges
• Cluster based data distribution techniques for leakage detection
• Data distribution techniques
• Done data leakage
• Share the data
• A robusat and efficient data transmission in adhoc networks
• Efficient data transmission in adhoc networks
• Efficient data access
• Simulation results reveal
• Empirical comparison by data mining classification algorithms
• Thyroid cancer data set
• E health services
• UCI machine learning repository
• Analysis of data hiding with ads in NTFS
• Data hiding with ads in NTFS
• The NTFS file system
• Alternate data stream
• Data leakage detection
• The original distributor’s data
• Data recipient is malicious
• Objects or records
• Techniques for detecting leakage
• Local area network overview
• High speed lans
• Wreless lans
• Network security
• Internet applications
• Network management
• Self sustainable data centre virtualization
• Self sustainable data virtualization
• Configure the client network
• Scripting the kickstart module of Linux kernel
• Issues in data mining and information retrieval
• Information retrieval and data warehousing
• The nature of the available data
• Online imposition aware aggregation with generative data flow model
• Online imposition aware aggregation
• Generative data flow model
• New attack instance
• The model parameters
• Suppression of multidimensional data using k anonymity
• Multidimensional data using k anonymity
• Domain hierarchy trees
• A review on clustering with genetic algorithms
• Clustering with genetic algorithms
• Data analysis and image analysis
• Data mining for exploring data sets
• Anomaly detection using genetic
• SVM algorithm in data mining
• Algorithm in data mining
• K mean algorithm
• Two algorithm genetic and SVM
• Efficient data access in WSN using AVGDRA scheme
• WSN using AVGDRA scheme
• Wireless sensor network
• Influencing unique data to boost the performance
• Key uploaded systems through cloud computing
• Perform volume arranged data yield Deduplication
• Process Oriented in put Deduplication
• Embedded digital signature based data sharing scheme in cloud computing
• Embedded digital signature
• Data sharing scheme in cloud computing
• Users’ private keys
• Secure cloud data storage with efficient key exposure
• Secure cloud data storage
• Efficient key exposure
• Multi cloud storage systems
• Data mining over large datasets using hadoop in cloud environment
• Hadoop in cloud environment
• Data mining over large datasets
• The HBase Heap Memory
• International Journal of Computer Networks and Communications Security
• Combined localization synchronization method for underwater communication
• Combined localization synchronization method
• The proposed method
• Well known method
• Prototype data showed
• Effect of noise on hidden data
• The least significant bits
• Least significant bits
• VoIP over UDP with bandwidth on demand analysis
• Bandwidth on demand analysis
• Packet loss for TCP data traffic
• TCP data traffic
• Feature specific criminal mapping
• Data mining techniques
• Generalized gaussiun mixture model
• Mapping the criminal
• The suspect table
• Maintaining stored procedures in database application
• Maintaining stored procedures
• Preserving data integrity
• Data end user