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E-raamat: Modeling and Simulation of Complex Communication Networks

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  • Formaat: PDF+DRM
  • Sari: Computing and Networks
  • Ilmumisaeg: 08-Feb-2019
  • Kirjastus: Institution of Engineering and Technology
  • Keel: eng
  • ISBN-13: 9781785613562
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Modeling and Simulation of Complex Communication NetworksSuurem pilt
  • Formaat: PDF+DRM
  • Sari: Computing and Networks
  • Ilmumisaeg: 08-Feb-2019
  • Kirjastus: Institution of Engineering and Technology
  • Keel: eng
  • ISBN-13: 9781785613562
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Modern network systems such as Internet of Things, Smart Grid, VoIP traffic, Peer-to-Peer protocol, and social networks, are inherently complex. They require powerful and realistic models and tools not only for analysis and simulation but also for prediction.



This book covers important topics and approaches related to the modeling and simulation of complex communication networks from a complex adaptive systems perspective. The authors present different modeling paradigms and approaches as well as surveys and case studies.



With contributions from an international panel of experts, this book is essential reading for networking, computing, and communications professionals, researchers and engineers in the field of next generation networks and complex information and communication systems, and academics and advanced students working in these fields.
Preface xiii
Part I Modeling and simulation
1 Modeling and simulation: the essence and increasing importance
3(24)
Turner Oren
Saurabh Mittal
Umut Durak
1.1 Introduction
3(2)
1.2 Experimentation aspects of simulation
5(1)
1.3 Experience aspects of simulation
6(2)
1.3.1 Simulation for training
6(2)
1.3.2 Simulation for entertainment
8(1)
1.4 Taxonomies and ontologies of simulation
8(2)
1.4.1 Background
8(1)
1.4.2 Taxonomies of simulation
9(1)
1.4.3 Ontologies of simulation
10(1)
1.5 Evolution and increasing importance of simulation
10(1)
1.6 Conclusion
11(1)
Appendix A A list of over 750 types of simulation
12(8)
Appendix B A list of 120 types of input
20(1)
References
21(6)
2 Flexible modeling with Simio
27(28)
David T. Sturrock
C. Dennis Pegden
2.1 Overview
27(1)
2.2 Simio object framework
27(3)
2.3 Simio object classes
30(1)
2.4 Modeling movements
31(2)
2.5 Modeling physical components
33(5)
2.6 Processes
38(2)
2.7 Data tables
40(2)
2.8 Experimentation with the model
42(1)
2.9 Application programming interface
43(1)
2.10 Applications in scheduling
44(6)
2.11 Summary
50(1)
Glossary
50(2)
References
52(3)
3 A simulation environment for cybersecurity attack analysis based on network traffic logs
55(28)
Salva Daneshgadeh
Mehmet Ugur Oney
Thomas Kemmerich
Nazife Baykal
3.1 Introduction
55(5)
3.1.1 Network simulation
56(2)
3.1.2 Network emulation
58(1)
3.1.3 The application of network simulation and emulation in network security
58(1)
3.1.4 Virtualization
58(1)
3.1.5 Virtualization using hypervisor
58(1)
3.1.6 Virtualization using container
59(1)
3.1.7 Virtual machines and simulation
59(1)
3.2 Literature review
60(4)
3.2.1 Network anomalies and detection methods
60(1)
3.2.2 Network workload generators
61(1)
3.2.3 Network simulation for security studies
61(3)
3.3 Methodology
64(1)
3.4 Defining a simulated and virtualized test bed for network anomaly detection researches
64(4)
3.4.1 GNS3
64(2)
3.4.2 Ubuntu
66(1)
3.4.3 Network interfaces
66(2)
3.5 Simulated environment for network anomaly detection researches
68(7)
3.5.1 Victim machine
68(1)
3.5.2 Attacker machine
68(1)
3.5.3 pfSense firewall
69(1)
3.5.4 NAT and VMware host-only networks
70(1)
3.5.5 Traffic generator machine
70(1)
3.5.6 NTOPNG tool
71(3)
3.5.7 Repository machine
74(1)
3.6 Discussion and results
75(1)
3.7 Summary
75(1)
References
76(7)
Part II Surveys and reviews
4 Demand-response management in smart grid: a survey and future directions
83(28)
Waseem Akram
Muaz A. Niazi
4.1 Overview
83(1)
4.2 Introduction
83(2)
4.3 Backgrounds
85(2)
4.3.1 Smart grid
85(1)
4.3.2 Demand-response management
86(1)
4.3.3 Complex systems
87(1)
4.3.4 Learning-based approaches
87(1)
4.4 A review of demand-response management in SG
87(15)
4.4.1 Learning-based approaches
88(2)
4.4.2 Complex system
90(2)
4.4.3 Other techniques
92(10)
4.5 Open-research problems and discussion
102(3)
4.5.1 Open-research problems in learning system
102(1)
4.5.2 Open-research problems in complex system
102(1)
4.5.3 Open-research problems in other techniques
103(2)
4.6 Conclusions
105(1)
References
105(6)
5 Applications of multi-agent systems in smart grid: a survey and taxonomy
111(34)
Waseem Akram
Muaz A. Niazi
5.1 Overview
111(1)
5.2 Introduction
111(2)
5.3 A review of multi-agent system to smart-grid application
113(21)
5.3.1 Communication management
113(4)
5.3.2 Demand-response management
117(4)
5.3.3 Fault monitoring
121(4)
5.3.4 Power scheduling
125(4)
5.3.5 Storage and voltage management
129(5)
5.4 Open research problems and discussion
134(3)
5.5 Conclusions
137(1)
References
138(7)
6 Shortest path models for scale-free network topologies: literature review and cross comparisons
145(30)
Agnese V. Ventrella
Giuseppe Piro
Luigi Alfredo Grieco
6.1 Mapping the Internet topology
146(8)
6.1.1 Interface level
147(4)
6.1.2 Router level
151(1)
6.1.3 AS level
152(2)
6.1.4 Geographic network topologies
154(1)
6.2 Internet models based on the graph theory
154(6)
6.2.1 Fundamental notions from the graph theory
155(1)
6.2.2 Topology models
156(2)
6.2.3 Topology generator tools
158(2)
6.3 Shortest path models
160(7)
6.3.1 Parameters definition
160(1)
6.3.2 Shortest path models
161(1)
6.3.3 Cross-comparison among shortest path models
162(1)
6.3.4 Shortest path models applications
163(4)
6.4 Conclusion
167(1)
Acknowledgment
167(1)
References
168(7)
Part III Case studies and more
7 Accurate modeling of VoIP traffic in modern communication
175(34)
Homero Toral-Cruz
Al-Sakib Khan Pathan
Julio C. Ramirez Pacheco
7.1 Introduction
175(2)
7.2 Modern communication networks: from simple packet network to multiservice network
177(2)
7.3 Voice over IP (VoIP) and quality of service (QoS)
179(13)
7.3.1 Basic structure of a VoIP system
179(2)
7.3.2 VoIP frameworks: H.323 and SIP
181(5)
7.3.3 Basic concepts of QoS
186(1)
7.3.4 QoS assessment
186(2)
7.3.5 Oneway delay
188(1)
7.3.6 Jitter
188(1)
7.3.7 Packetloss rate
189(3)
7.4 Self-similarity processes in modern communication networks
192(3)
7.4.1 Self-similar processes
192(2)
7.4.2 Haar wavelet-based decomposition and Hurst index estimation
194(1)
7.5 QoS parameters modeling on VoIP traffic
195(9)
7.5.1 Jitter modeling by self-similar and multifractal processes
195(5)
7.5.2 Packet-loss modeling by Markov models
200(2)
7.5.3 Packet-loss simulation and proposed model
202(2)
7.6 Conclusions
204(1)
References
205(4)
8 Exploratory and validated agent-based modeling levels case study: Internet of Things
209(30)
Komal Batool
Muaz A. Niazi
8.1 Introduction
209(20)
8.1.1 Agent-based modeling framework
210(1)
8.1.2 Agent-based simulator
211(2)
8.1.3 Case study: 5G networks and Internet of Things
213(8)
8.1.4 Results and discussion
221(8)
8.1.5 Conclusion
229(1)
8.2 Validated agent-based modeling level case study: Internet of Things
229(8)
8.2.1 Introduction
229(1)
8.2.2 Validated agent-based level
230(3)
8.2.3 Case study: 5G networks and Internet of Things
233(2)
8.2.4 Results and discussion
235(1)
8.2.5 Validation discussion
236(1)
8.2.6 Conclusion
236(1)
References
237(2)
9 Descriptive agent-based modeling of the "Chord" P2P protocol
239(46)
Hasina Attaullah
Urva Latif
Kashif Ali
9.1 Introduction
239(1)
9.2 Background and literature review
240(10)
9.2.1 CAS literature
240(1)
9.2.2 Modeling and simulation of CACOONS
240(1)
9.2.3 Chord P2P protocol
241(1)
9.2.4 Hashing and key mapping
242(1)
9.2.5 Node joining
242(1)
9.2.6 Finger table
242(1)
9.2.7 Stabilization
243(2)
9.2.8 Performance of chord
245(1)
9.2.9 PeerSim
245(1)
9.2.10 Literature review
245(5)
9.3 ODD model of a "Chord"
250(4)
9.3.1 Purpose
251(1)
9.3.2 Entities, state variables, and scales
251(1)
9.3.3 Process overview and scheduling
252(1)
9.3.4 Design concepts
252(2)
9.3.5 Initialization
254(1)
9.3.6 Input data
254(1)
9.3.7 Sub-models
254(1)
9.4 DREAM model of a "Chord"
254(13)
9.4.1 Agent design
254(1)
9.4.2 Activity diagrams
255(1)
9.4.3 Flowchart
255(1)
9.4.4 Pseudo-code based specification
256(11)
9.5 Results and discussion
267(13)
9.5.1 Metrics (table and description)
267(2)
9.5.2 PeerSim results
269(1)
9.5.3 ABM results
270(1)
9.5.4 Comparison of PeerSim and ABM
271(1)
9.5.5 DREAM network models
272(6)
9.5.6 Discussion (ODD vs. DREAM pros and cons of both) and which is more useful for modeling the chosen P2P protocol
278(2)
9.5.7 Chord and theory of computation
280(1)
9.6 Conclusions and future work
280(1)
References
280(5)
10 Descriptive agent-based modeling of Kademlia peer-to-peer protocol
285(48)
Hammad-Ur-Rehman
Muhammad Qasim Mehboob
10.1 Introduction
285(1)
10.2 Background and literature review
286(12)
10.2.1 Complex adaptive systems
287(1)
10.2.2 Cognitive agent-based computing
287(1)
10.2.3 Complex network modeling
287(1)
10.2.4 Architecture of the "Kademlia" protocol
287(5)
10.2.5 Literature review
292(6)
10.3 Model design
298(15)
10.3.1 ODD model of "Kademlia"
299(1)
10.3.2 Overview
299(1)
10.3.3 Design concept
299(1)
10.3.4 Details
300(1)
10.3.5 Activity diagrams of "Kademlia"
301(1)
10.3.6 DREAM model of "Kademlia"
301(1)
10.3.7 Network model
301(1)
10.3.8 Pseudo-code description
301(12)
10.4 Results and discussion
313(15)
10.4.1 Evaluation metrics
313(1)
10.4.2 Power law plots of centrality measures
313(1)
10.4.3 PeerSim simulation using existing code in PeerSim
314(9)
10.4.4 ABM simulation
323(2)
10.4.5 Comparison of PeerSim and ABM results
325(1)
10.4.6 Discussion
325(3)
10.5 Conclusion and future work
328(1)
References
328(5)
11 Descriptive agent-based modeling of the "BitTorrent" P2P protocol
333(48)
Abdul Saboor
Nasir Khan
Mubariz Rehman
11.1 Introduction
333(3)
11.1.1 Contributions
335(1)
11.2 Background and literature review
336(2)
11.2.1 Complex adaptive systems
336(1)
11.2.2 Modeling and simulation of CACOONS
337(1)
11.3 BitTorrent peer-to-peer protocol
338(5)
11.3.1 BitTorrent history overview
339(1)
11.3.2 Content publishing in BitTorrent
340(1)
11.3.3 Joining swarm and peers discovery in BitTorrent
340(1)
11.3.4 Delivery procedure BitTorrent
340(1)
11.3.5 BitTorrent architecture and working
341(2)
11.4 BitTorrent literature review
343(6)
11.4.1 PeerSim
348(1)
11.5 Model design
349(26)
11.5.1 ODD approach
349(2)
11.5.2 Overview of the proposed model
351(3)
11.5.3 DREAM model
354(2)
11.5.4 Pseudocode-based specification
356(1)
11.5.5 Globals
357(1)
11.5.6 Procedures
358(4)
11.5.7 Experiments
362(3)
11.5.8 Results and discussions
365(1)
11.5.9 PeerSim results
366(1)
11.5.10 ABM results
366(1)
11.5.11 Comparison of both
367(2)
11.5.12 DREAM network models
369(6)
11.6 Discussion (ODD vs DREAM)
375(1)
11.7 Conclusion
376(1)
References
376(5)
12 Social networks--a scientometric visual survey
381(32)
Bisma S. Khan
Muaz A. Niazi
12.1 Introduction
381(1)
12.2 Background
382(2)
12.2.1 Social networks--an overview
382(1)
12.2.2 Citation networks
383(1)
12.2.3 Co-citation networks
383(1)
12.2.4 Bibliographic coupling
383(1)
12.2.5 Coauthorship networks
384(1)
12.2.6 Co-occurrence networks
384(1)
12.3 Materials and methods
384(4)
12.3.1 Data collection
385(1)
12.3.2 CiteSpace--a science mapping tool
385(3)
12.4 Results and discussion
388(21)
12.4.1 Cited-references co-citation network analysis
388(5)
12.4.2 Authors collaboration network analysis
393(3)
12.4.3 Institution collaboration network analysis
396(4)
12.4.4 Country collaboration network analysis
400(3)
12.4.5 Keywords co-occurrence network analysis
403(2)
12.4.6 Category co-occurrence network analysis
405(4)
12.4.7 Journal co-citation network analysis
409(1)
12.5 Summary of results
409(1)
12.6 Conclusions and future work
410(1)
References
411(2)
Index 413
Muaz A. Niazi is Chief Scientific Officer (Professor) at COMSATS Islamabad, Pakistan. His areas of research interest are in the Modeling, Simulation, and Engineering of Complex Adaptive Systems using various techniques such as agent-based and complex network based approaches. He also has an interest and experience in distributed pervasive/mobile application development. He is the founding Editor-in-Chief of two journals and a senior member of the IEEE.
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