Search Results - (((((((ant OR kwants) OR wants) OR markant) OR cantor) OR anne) OR shared) OR hints) algorithms.

IP multicast with applications to IPTV and mobile DVB-H by Minoli, Daniel, 1952-

Table of Contents: “…Cover -- TOC36;CONTENTS -- Preface -- About the Author -- CH36;1 INTRODUCTION TO IP MULTICAST -- 146;1 Introduction -- 146;2 Why Multicast Protocols are Wanted47;Needed -- 146;3 Basic Multicast Protocols and Concepts -- 146;4 IPTV and DVB45;H Applications -- 146;5 Course of Investigation -- Appendix 146;A58; Multicast IETF Request for Comments -- Appendix 146;B58; Multicast Bibliography -- References -- CH36;2 MULTICAST ADDRESSING FOR PAYLOAD -- 246;1 IP Multicast Addresses -- 246;146;1 Limited Scope Addresses -- 246;146;2 GLOP Addressing -- 246;146;3 Generic IPv4 Addressing -- 246;2 Layer 2 Multicast Addresses -- 246;246;1 Ethernet MAC Address Mapping -- 246;3 MPEG45;Layer Addresses -- References -- CH36;3 MULTICAST PAYLOAD FORWARDING -- 346;1 Multicasting on a LAN Segment -- 346;2 Multicasting between Network Segments -- 346;3 Multicast Distribution Trees -- 346;4 Multicast Forwarding58; Reverse Path Forwarding -- 346;5 Multicast Forwarding58; Center45;Based Tree Algorithm -- 346;6 Implementing IP Multicast in a Network -- References -- CH36;4 DYNAMIC HOST REGISTRATION8212;INTERNET GROUP MANAGEMENT PROTOCOL -- 446;1 IGMP Messages -- 446;2 IGMPv3 Messages -- 446;3 IGMP Operation -- Appendix 446;A58; Protocol Details for IGMPv2 -- 446;A46;1 Overview -- 446;A46;2 Protocol Description -- 446;A46;3 Receiver 40;Host41; State Diagram -- 446;A46;4 Router State Diagram -- Appendix 446;B58; IGMP Snooping Switches -- Appendix 446;C58; Example of Router Configurations -- References -- CH36;5 MULTICAST ROUTING8212;SPARSE45;MODE PROTOCOLS58; PROTOCOL INDEPENDENT MULTICAST -- 546;1 Introduction to PIM -- 546;2 PIM SM Details -- 546;246;1 Approach -- 546;246;2 PIM SM Protocol Overview -- 546;246;3 Detailed Protocol Description -- 546;246;4 Packet Formats -- References -- CH36;6 MULTICAST ROUTING8212;SPARSE45;MODE PROTOCOLS58; CORE45;BASED TREES -- 646;1 Motivation -- 646;2 Basic Operation -- 646;3 CBT Components and Functions -- 646;346;1 CBT Control Message Retransmission Strategy -- 646;346;2 Nonmember Sending -- 646;4 Core Router Discovery -- 646;5 Protocol Specification Details -- 646;546;1 CBT HELLO Protocol -- 646;546;2 JOIN_REQUEST Processing -- 646;546;3 JOIN_ACK Processing -- 646;546;4 QUIT_NOTIFICATION Processing -- 646;546;5 ECHO_REQUEST Processing -- 646;546;6 ECHO_REPLY Processing -- 646;546;7 FLUSH_TREE Processing -- 646;546;8 Nonmember Sending -- 646;546;9 Timers and Default Values -- 646;546;10 CBT Packet Formats and Message Types -- 646;546;11 Core Router Discovery -- 646;6 CBT Version 3 -- 646;646;1 The First Step58; Joining the Tree -- 646;646;2 Transient State -- 646;646;3 Getting 34;On Tree34; -- 646;646;4 Pruning and Prune State -- 646;646;5 The Forwarding Cache -- 646;646;6 Packet Forwarding -- 646;646;7 The 34;Keepalive34; Protocol -- 646;646;8 Control Message Precedence and Forwarding Criteria -- 646;646;9 Broadcast LANs -- 646;646;10 The 34;all45;cbt45;routers34; Group -- 646;646;11 Nonmember Sending -- References -- CH36;7 MULTICAST ROUTING8212;DENSE45;MODE PROTOCOLS58; PIM DM.…”
Full text (MFA users only)

Security, Privacy and Reliability in Computer Communications and Networks. by Sha, Kewei

Table of Contents: “…Front Cover -- Half Title Page -- RIVER PUBLISHERS SERIES IN INNOVATION AND CHANGE IN EDUCATION -- CROSS-CULTURAL PERSPECTIVE -- Title Page -- Security, Privacy and Reliability in Computer Communications and Networks -- Copyright Page -- Contents -- Preface -- Acknowledgments -- List of Contributors -- List of Figures -- List of Tables -- List of Algorithms -- List of Abbreviations -- PART I -- Privacy -- Chapter 1 -- Distributed Beamforming Relay Selection to Increase Base Station Anonymity in Wireless Ad Hoc Networks -- Abstract -- 1.1 Introduction -- 1.2 Anonymity Definition, Metrics, and Contemporary Measures -- 1.2.1 Anonymity Definition and Assessment -- 1.2.2 Antitraffic Analysis Measures -- 1.3 System Assumptions and Attack Model -- 1.3.1 Network Model -- 1.3.2 Adversary Model -- 1.3.3 Evidence Theory and Belief Metric -- 1.4 Distributed Beamforming to Increase the BS Anonymity -- 1.4.1 Overview of the DiBAN Protocol -- 1.4.2 DiBAN Illustrative Example -- 1.4.3 DiBAN Energy Analysis -- 1.5 Distributed Beamforming Relay Selection Approach -- 1.6 Validation Experiments -- 1.6.1 Simulation Environment -- 1.6.2 Simulation Results -- 1.7 Conclusions and FutureWork -- Appendix I: Numerical Evidence Theory Belief Calculation Example -- References -- Chapter 2 -- A Privacy-Preserving and Efficient Information Sharing Scheme for VANET Secure Communication -- Abstract -- 2.1 Introduction -- 2.2 Related Works -- 2.3 System Model and Preliminaries -- 2.3.1 Network Model -- 2.3.2 Attack Model -- 2.3.3 Security Requirements -- 2.4 The Proposed PETS Scheme -- 2.4.1 Scheme Overview -- 2.4.2 System Initiation -- 2.4.3 Vehicle-RSU Key Agreement -- 2.4.4 Traffic Information Collection and Aggregation -- 2.4.5 Traffic Jam Message Propagation -- 2.5 Security Analysis -- 2.6 Performance Evaluation -- 2.6.1 Traffic Information Sending/Collection Overhead.…”
Full text (MFA users only)

Advanced wireless communications & Internet : future evolving technologies by Glisic, Savo G.

Table of Contents: “…Glisic -- 11.1 Introduction 585 -- 11.2 Background and Related Work 586 -- 11.3 Cooperative Communications 593 -- 11.4 Relay-Assisted Communications 616 -- 11.5 Two-Way Relay-Assisted Communications 646 -- 11.6 Relay-Assisted Communications With Reuse of Resources 651 -- Appendices 668 -- 12 Biologically Inspired Paradigms inWireless Networks 683 -- 12.1 Biologically Inspired Model for Securing Hybrid Mobile Ad Hoc Networks 683 -- 12.2 Biologically Inspired Routing in Ad Hoc Networks 687 -- 12.3 Analytical Modeling of AntNet as Adaptive Mobile Agent Based Routing 691 -- 12.4 Biologically Inspired Algorithm for Optimum Multicasting 697 -- 12.5 Biologically Inspired (BI) Distributed Topology Control 703 -- 12.6 Optimization of Mobile Agent Routing in Sensor Networks 708 -- 12.7 Epidemic Routing 710 -- 12.8 Nano-Networks 715 -- 12.9 Genetic Algorithm Based Dynamic Topology Reconfiguration in Cellular Multihop Wireless Networks 718 -- References 739 -- 13 Positioning in Wireless Networks 743 -- 13.1 Mobile Station Location in Cellular Networks 743.…”
Full text (MFA users only)

SCADA Security : Machine Learning Concepts for Intrusion Detection and Prevention. by Almalawi, Abdulmohsen

Table of Contents: “…CHAPTER 4 Efficient k-Nearest Neighbour Approach Based on Various-Widths Clustering -- 4.1 INTRODUCTION -- 4.2 RELATED WORK -- 4.3 THE kNNVWC APPROACH -- 4.3.1 FWC Algorithm and Its Limitations -- 4.3.2 Various-Widths Clustering -- 4.3.3 The k-NN Search -- 4.4 EXPERIMENTAL EVALUATION -- 4.4.1 Data Sets -- 4.4.2 Performance Metrics -- 4.4.3 Impact of Cluster Size -- 4.4.4 Baseline Methods -- 4.4.5 Distance Metric -- 4.4.6 Complexity Metrics -- 4.5 CONCLUSION -- CHAPTER 5 SCADA Data-Driven Anomaly Detection -- 5.1 INTRODUCTION -- 5.2 SDAD APPROACH -- 5.2.1 Observation State of SCADA Points…”
Full text (MFA users only)

Anesthesia student survival guide : a case-based approach

Full text (MFA users only)

The Johns Hopkins guide to digital media

Table of Contents: “…Berry -- Cognitive implications of new media / Anne Mangen and Jean-Luc Velay -- Collaborative narrative / Scott Rettberg -- Collective intelligence / John Duda -- Combinatory and automatic text generation / Philippe Bootz and Christopher Funkhouser -- Computational linguistics / Inderjeet Mani -- Conceptual writing / Darren Wershler -- Copyright / Benjamin J. …”

Two-degree-of-freedom control systems : the Youla Parameterization approach by Keviczky, László, Bányász, Csilla

Full text (MFA users only)

Machine Learning with Apache Spark Quick Start Guide : Uncover Patterns, Derive Actionable Insights, and Learn from Big Data Using MLlib. by Quddus, Jillur

Full text (MFA users only)

Big data : concepts, technology and architecture by Balusamy, Balamurugan, R, Nandhini Abirami, Kadry, Seifedine, 1977-, Gandomi, Amir Hossein

Table of Contents: “…<i>3</i>Big Data Analytics. 31</p> <p>1.7.4 Visualizing Big Data. 32</p> <p>1.8 Big Data Technology. 32</p> <p>1.8.1 Challenges faced by Big Data technology. 34</p> <p>1.8.1 Heterogeneity and incompleteness. 34</p> <p>1.8.2 Volume and velocity of the Data. 35</p> <p>1.8.3 Data Storage. 35</p> <p>1.8.4 Data Privacy. 36</p> <p>1.9 Big Data Applications. 36</p> <p>1.10 Big Data Use Cases. 37</p> <p>1.9. 1 Healthcare. 37</p> <p>1.9.2 Telecom.. 38</p> <p>1.9.3 Financial Services. 39</p> <p>Chapter 1 refresher: 40</p> <p>Conceptual short Questions with answers. 43</p> <p>Frequently asked Interview questions. 45</p> <p>Chapter Objective. 46</p> <p>Big Data Storage Concepts. 46</p> <p>2.1 Cluster computing. 47</p> <p>2.1.1 Types of cluster. 49</p> <p>2.1.1.1 High availability cluster. 50</p> <p>2.1.1.2 Load balancing cluster. 50</p> <p>2.1.2 Cluster structure. 51</p> <p>2.3 Distribution Models. 53</p> <p>2.3.1 Sharding. 54</p> <p>2.3.2 Data Replication. 56</p> <p>2.3.2.1 Master-Slave model 57</p> <p>2.3.2.2 Peer-to-Peer model 58</p> <p>2.3.3 Sharding and Replication. 59</p> <p>2.4 Distributed file system.. 60</p> <p>2.5 Relational and Non Relational Databases. 61</p> <p>CoursesOffered. 62</p> <p>Figure 2.12 Data divided across multiple related tables. 62</p> <p>2.4.2 RDBMS Databases. 63</p> <p>2.4.3 NoSQL Databases. 63</p> <p>2.4.4 NewSQL Databases. 64</p> <p>2.5 Scaling Up and Scaling Out Storage. 65</p> <p>Chapter 2 refresher. 67</p> <p>Conceptual short questions with answers. 69</p> <p>Chapter Objective. 72</p> <p>3.1 Introduction to NoSQL. 72</p> <p>3.2 Why NoSQL. 72</p> <p>3.3 CAP theorem.. 73</p> <p>3.4 ACID.. 75</p> <p>3.5 BASE. 76</p> <p>3.6 Schemaless Database. 77</p> <p>3.7 NoSQL (Not Only SQL) 77</p> <p>3.7.1 NoSQL Vs RDBMS. 78</p> <p>3.7.2Features of NoSQL database. 79</p> <p>3.7.3Types of NoSQL Technologies. 80</p> <p>3.7.3.1 Key-Value store database. 81</p> <p>3.7.3.2 Column-store database. 82</p> <p>3.7.3.3 Document Oriented Database. 84</p> <p>3.7.3.4 Graph-oriented Database. 86</p> <p>3.7.4 NoSQL Operations. 93</p> <p>3.9 Migrating from RDBMS to NoSQL. 98</p> <p>Chapter 3 refresher. 99</p> <p>Conceptual short questions with answers. 102</p> <p>Chapter Objective. 104</p> <p>4.1 Data Processing. 104</p> <p>4.2 Shared Everything Architecture. 106</p> <p>4.2.1 Symmetric multiprocessing architecture. 107</p> <p>4.2.2 Distributed Shared memory. 108</p> <p>4.3 Shared nothing architecture. 109</p> <p>4.4 Batch Processing. 110</p> <p>4.5 Real-Time Data Processing. 111</p> <p>4.6 Parallel Computing. 112</p> <p>4.7 Distributed Computing. 113</p> <p>4.8 Big Data Virtualization. 113</p> <p>4.8.1 Attributes of Virtualization. 114</p> <p>4.8.1.1 Encapsulation. 115</p> <p>4.8.1.2 Partitioning. 115</p> <p>4.8.1.3 Isolation. 115</p> <p>4.8.2Big Data Server Virtualization. 116</p> <p>4.9 Introduction. 116</p> <p>4.10 Cloud computing types. 118</p> <p>4.11Cloud Services. 120</p> <p>4.12 Cloud Storage. 121</p> <p>4.12.1 Architecture of GFS. 121</p> <p>4.12.1.1 Master. 123</p> <p>4.12.1.2 Client. 123</p> <p>4.13 Cloud Architecture. 127</p> <p>Cloud Challenges. 129</p> <p>Chapter 4 Refresher. 130</p> <p>Conceptual short questions with answers. 133</p> <p>Chapter Objective. 139</p> <p>5.1 Apache Hadoop. 139</p> <p>5.1.1 Architecture of Apache Hadoop. 140</p> <p>5.1.2Hadoop Ecosystem Components Overview.. 140</p> <p>5.2 Hadoop Storage. 142</p> <p>5.2.1HDFS (Hadoop Distributed File System). 142</p> <p>5.2.2Why HDFS?. …”
Full text (MFA users only)

Language, vision, and music : selected papers from the 8th International Workshop on the Cognitive Science of Natural Language Processing, Galway, Ireland, 1999

Full text (MFA users only)

Politics of disinformation : the influence of fake news on the public sphere

Full text (MFA users only)

Deep learning with Python : a hands-on introduction by Ketkar, Nikhil

Full text (MFA users only)

Deep learning for dummies by Mueller, John, 1958-, Massaron, Luca

Full text (MFA users only)

Robust and error-free geometric computing by Eberly, Dave

Full text (MFA users only)

QoS in integrated 3G networks by Lloyd-Evans, Robert

Full text (MFA users only)

Big data analytics : turning big data into big money by Ohlhorst, Frank, 1964-

Full text (MFA users only)

AI and the future of banking by Boobier, Tony, 1956-

Full text (MFA users only)

Applied mechanics and manufacturing technology : selected, peer reviewed papers of the 2011 International Conference on Applied Mechanics and Manufacturing Technology (AMMT 2011),...

Full text (MFA users only)

Hands-On Deep Learning with TensorFlow. by Boxel, Dan Van

Full text (MFA users only)

Technologies for sustainable development : proceedings of the 7th Nirma University International Conference on Engineering (NUiCONE 2019), November 21-22, 2019, Ahmedabad, India

Full text (MFA users only)