Internet topology dynamics in ten minutes
|
|
|
- Madeline Ray
- 7 years ago
- Views:
Transcription
1 Internet topology dynamcs n ten mnutes Sergey Krgzov under the supervson of Clémence Magnen Complex Networks LIP6 (UPMC CNRS) 4 March 2014
2 Outlne 1 What do we observe? 2 Why t s so mportant? 3 How do we study our observatons? 2
3 What do we observe?
4 Internet IP-level topology Nodes: Lnks: IP addresses connectons between hosts 3
5 Internet IP-level topology Impossble to obtan a full map Nodes: Lnks: IP addresses connectons between hosts 3
6 Ego-centered vews d 1 d 2 m (shortest) paths between montor and destnatons 4
7 Ego-centered vews d 1 d 2 m a measurement by tracetree 4
8 Ego-centered vews d 1 d 2 m another measurement by tracetree load-balancng 4
9 Ego-centered vews d 1 d 2 m yet another measurement by tracetree evoluton of routes 4
10 Ego-centered vew dynamcs d1 d2 d1 d2 d1 d2 m m m Tme Fast perodc measurements = study of the dynamcs 5
11 Why we should study ths?
12 Some possble applcatons Develop a good model of the network Securty (unstable routes means more spyware?) Robustness of the network and protocols Event detecton Web cachng etc 6
13 Can we see the dynamcs?
14 Evoluton of symmetrc dfference between measurements (one destnaton) : frst measurement (delay 1 mn 30 sec)
15 Evoluton of symmetrc dfference between measurements (one destnaton) : frst measurement (delay 1 mn 30 sec)
16 Evoluton of symmetrc dfference between measurements (one destnaton) : frst measurement Load-balancng (delay 1 mn 30 sec)
17 Evoluton of symmetrc dfference between measurements (one destnaton) : frst measurement Load-balancng (delay 1 mn 30 sec)
18 Evoluton of symmetrc dfference between measurements (one destnaton) : frst measurement Load-balancng (delay 1 mn 30 sec)
19 Evoluton of symmetrc dfference between measurements (one destnaton) : frst measurement Load-balancng (delay 1 mn 30 sec)
20 Evoluton of symmetrc dfference between measurements (one destnaton) : frst measurement Load-balancng (delay 1 mn 30 sec)
21 Evoluton of symmetrc dfference between measurements (one destnaton) : frst measurement Load-balancng (delay 1 mn 30 sec)
22 Evoluton of symmetrc dfference between measurements (one destnaton) : frst measurement Load-balancng (delay 1 mn 30 sec)
23 Evoluton of symmetrc dfference between measurements (one destnaton) : frst measurement Load-balancng (delay 1 mn 30 sec)
24 Evoluton of symmetrc dfference between measurements (one destnaton) : frst measurement Load-balancng (delay 1 mn 30 sec)
25 Evoluton of symmetrc dfference between measurements (one destnaton) : frst measurement Load-balancng (delay 1 mn 30 sec)
26 Evoluton of symmetrc dfference between measurements (one destnaton) : frst measurement Load-balancng (delay 1 mn 30 sec)
27 Evoluton of symmetrc dfference between measurements (one destnaton) : frst measurement Load-balancng (delay 1 mn 30 sec)
28 Evoluton of symmetrc dfference between measurements (one destnaton) : frst measurement Load-balancng (delay 1 mn 30 sec)
29 Evoluton of symmetrc dfference between measurements (one destnaton) : frst measurement Load-balancng (delay 1 mn 30 sec)
30 Evoluton of symmetrc dfference between measurements (one destnaton) : frst measurement Load-balancng (delay 1 mn 30 sec)
31 Evoluton of symmetrc dfference between measurements (one destnaton) : frst measurement Load-balancng (delay 1 mn 30 sec)
32 Evoluton of symmetrc dfference between measurements (one destnaton) : frst measurement Load-balancng (delay 1 mn 30 sec)
33 Evoluton of symmetrc dfference between measurements (one destnaton) : frst measurement Load-balancng (delay 1 mn 30 sec)
34 Evoluton of symmetrc dfference between measurements (one destnaton) : frst measurement Evoluton (delay 1 mn 30 sec)
35 Delay: 1 mn 30 sec 3 mn Destnatons
36 Delay: 1 mn 30 sec 3 mn Destnatons
37 Overvew of problems and methods number of destnatons frequency of observatons? observed evoluton Methods: Real-world measurements Smulated measurements usng random graphs Theoretcal study of dynamc random graphs Stochastc process estmaton from partal observatons 9
38 Questons?
Internet measurements at complexnetworks.fr
Internet measurements at complexnetworks.fr Guillaume Valadon - http://valadon.complexnetworks.fr LIP6 (CNRS - UPMC) Complex Networks team http://complexnetworks.fr 2 The team http://complexnetworks.fr
luis m. rocha school of informatics and computing indiana university, bloomington, usa and instituto gulbenkian de ciência oeiras, portugal
sem-metrc topology and collectve computaton Informatcs n complex networks lus m. rocha school of nformatcs and computng ndana unversty, bloomngton, usa and nsttuto gulbenkan de cênca oeras, portugal complex
SDN: Systemic Risks due to Dynamic Load Balancing
SDN: Systemc Rsks due to Dynamc Load Balancng Vladmr Marbukh IRTF SDN Abstract SDN acltates dynamc load balancng Systemc benets o dynamc load balancng: - economc: hgher resource utlzaton, hgher revenue,..
Stochastic Protocol Modeling for Anomaly Based Network Intrusion Detection
Stochastc Protocol Modelng for Anomaly Based Network Intruson Detecton Juan M. Estevez-Tapador, Pedro Garca-Teodoro, and Jesus E. Daz-Verdejo Department of Electroncs and Computer Technology Unversty of
PAS: A Packet Accounting System to Limit the Effects of DoS & DDoS. Debish Fesehaye & Klara Naherstedt University of Illinois-Urbana Champaign
PAS: A Packet Accountng System to Lmt the Effects of DoS & DDoS Debsh Fesehaye & Klara Naherstedt Unversty of Illnos-Urbana Champagn DoS and DDoS DDoS attacks are ncreasng threats to our dgtal world. Exstng
IT 3202 Internet Working (New)
[All Rights Reserved] SLIATE SRI LANKA INSTITUTE OF ADVANCED TECHNOLOGICAL EDUCATION (Established in the Ministry of Higher Education, vide in Act No. 29 of 1995) Instructions for Candidates: Answer any
RequIn, a tool for fast web traffic inference
RequIn, a tool for fast web traffc nference Olver aul, Jean Etenne Kba GET/INT, LOR Department 9 rue Charles Fourer 90 Evry, France Olver.aul@nt-evry.fr, Jean-Etenne.Kba@nt-evry.fr Abstract As networked
Level Annuities with Payments Less Frequent than Each Interest Period
Level Annutes wth Payments Less Frequent than Each Interest Perod 1 Annuty-mmedate 2 Annuty-due Level Annutes wth Payments Less Frequent than Each Interest Perod 1 Annuty-mmedate 2 Annuty-due Symoblc approach
Calendar Corrected Chaotic Forecast of Financial Time Series
INTERNATIONAL JOURNAL OF BUSINESS, 11(4), 2006 ISSN: 1083 4346 Calendar Corrected Chaotc Forecast of Fnancal Tme Seres Alexandros Leonttss a and Costas Sropoulos b a Center for Research and Applcatons
On-Line Fault Detection in Wind Turbine Transmission System using Adaptive Filter and Robust Statistical Features
On-Lne Fault Detecton n Wnd Turbne Transmsson System usng Adaptve Flter and Robust Statstcal Features Ruoyu L Remote Dagnostcs Center SKF USA Inc. 3443 N. Sam Houston Pkwy., Houston TX 77086 Emal: ruoyu.l@skf.com
Ethernet. Ethernet Frame Structure. Ethernet Frame Structure (more) Ethernet: uses CSMA/CD
Ethernet dominant LAN technology: cheap -- $20 for 100Mbs! first widely used LAN technology Simpler, cheaper than token rings and ATM Kept up with speed race: 10, 100, 1000 Mbps Metcalfe s Etheret sketch
Peak Inverse Voltage
9/13/2005 Peak Inerse Voltage.doc 1/6 Peak Inerse Voltage Q: I m so confused! The brdge rectfer and the fullwae rectfer both prode full-wae rectfcaton. Yet, the brdge rectfer use 4 juncton dodes, whereas
Proactive Secret Sharing Or: How to Cope With Perpetual Leakage
Proactve Secret Sharng Or: How to Cope Wth Perpetual Leakage Paper by Amr Herzberg Stanslaw Jareck Hugo Krawczyk Mot Yung Presentaton by Davd Zage What s Secret Sharng Basc Idea ((2, 2)-threshold scheme):
The Application of Fractional Brownian Motion in Option Pricing
Vol. 0, No. (05), pp. 73-8 http://dx.do.org/0.457/jmue.05.0..6 The Applcaton of Fractonal Brownan Moton n Opton Prcng Qng-xn Zhou School of Basc Scence,arbn Unversty of Commerce,arbn zhouqngxn98@6.com
Clarify Outline. Installation
Clarfy Outlne Installaton The Basc Idea of Smulaton (and why t makes sense for substante nterpretaton) Components of Clarfy estsmp setx smq A Real Le Example Logt odel Contnuous IVs Bnary IVs Concludng
An RFID Distance Bounding Protocol
An RFID Dstance Boundng Protocol Gerhard P. Hancke and Markus G. Kuhn May 22, 2006 An RFID Dstance Boundng Protocol p. 1 Dstance boundng Verfer d Prover Places an upper bound on physcal dstance Does not
GIS: data processing. 3.1.1. Example of spatial queries. 3.1 Spatial queries. Chapter III. Geographic Information Systems: Data Processing
Vsal Informaton Systems Pr. Robert Larn GIS: data processng Chapter III Geographc Informaton Systems: Data Processng 3.1 Spatal qeres 3. Introdcton to Spatal nalyss 3.3 Spatal ndexng 3. Updatng 3. Conclsons
VoIP Playout Buffer Adjustment using Adaptive Estimation of Network Delays
VoIP Playout Buffer Adjustment usng Adaptve Estmaton of Network Delays Mroslaw Narbutt and Lam Murphy* Department of Computer Scence Unversty College Dubln, Belfeld, Dubln, IRELAND Abstract The poor qualty
2. What is the maximum value of each octet in an IP address? A. 28 B. 255 C. 256 D. None of the above
CCNA1 V3.0 Mod 10 (Ch 8) 1. How many bits are in an IP C. 64 2. What is the maximum value of each octet in an IP A. 28 55 C. 256 3. The network number plays what part in an IP A. It specifies the network
14.74 Lecture 5: Health (2)
14.74 Lecture 5: Health (2) Esther Duflo February 17, 2004 1 Possble Interventons Last tme we dscussed possble nterventons. Let s take one: provdng ron supplements to people, for example. From the data,
Network Security Situation Evaluation Method for Distributed Denial of Service
Network Securty Stuaton Evaluaton Method for Dstrbuted Denal of Servce Jn Q,2, Cu YMn,2, Huang MnHuan,2, Kuang XaoHu,2, TangHong,2 ) Scence and Technology on Informaton System Securty Laboratory, Bejng,
Routing in packet-switching networks
Routing in packet-switching networks Circuit switching vs. Packet switching Most of WANs based on circuit or packet switching Circuit switching designed for voice Resources dedicated to a particular call
Types of Injuries. (20 minutes) LEARNING OBJECTIVES MATERIALS NEEDED
U N I T 3 Types of Injures (20 mnutes) PURPOSE: To help coaches learn how to recognze the man types of acute and chronc njures. LEARNING OBJECTIVES In ths unt, coaches wll learn how most njures occur,
Scalable Source Routing
Scalable Source Routing January 2010 Thomas Fuhrmann Department of Informatics, Self-Organizing Systems Group, Technical University Munich, Germany Routing in Networks You re there. I m here. Scalable
PSYCHOLOGICAL RESEARCH (PYC 304-C) Lecture 12
14 The Ch-squared dstrbuton PSYCHOLOGICAL RESEARCH (PYC 304-C) Lecture 1 If a normal varable X, havng mean µ and varance σ, s standardsed, the new varable Z has a mean 0 and varance 1. When ths standardsed
Monitoring sea level change at Cascais tide gauge
Journal of Coastal Research SI 64 pg - pg ICS211 (Proceedngs) Poland ISSN 749-28 Montorng sea level change at Cascas tde gauge C. Antunes IDL Unversty of Lsbon, Lsbon, 1794-16 Portugal cmantunes@fc.ul.pt
Testing CAB-IDS through Mutations: on the Identification of Network Scans
Testng CAB-IDS through Mutatons: on the Identfcaton of Network Scans Emlo Corchado, Álvaro Herrero, José Manuel Sáz Department of Cvl Engneerng, Unversty of Burgos, Span {escorchado, ahcoso, msaz}@ubu.es
Negative Selection and Niching by an Artificial Immune System for Network Intrusion Detection
Negatve Selecton and Nchng by an Artfcal Immune System for Network Intruson Detecton Jungwon Km and Peter Bentley Department of omputer Scence, Unversty ollege London, Gower Street, London, W1E 6BT, U.K.
A Statistical Model for Detecting Abnormality in Static-Priority Scheduling Networks with Differentiated Services
A Statstcal odel for Detectng Abnoralty n Statc-Prorty Schedulng Networks wth Dfferentated Servces ng L 1 and We Zhao 1 School of Inforaton Scence & Technology, East Chna Noral Unversty, Shangha 0006,
Lecture 8: Routing I Distance-vector Algorithms. CSE 123: Computer Networks Stefan Savage
Lecture 8: Routing I Distance-vector Algorithms CSE 3: Computer Networks Stefan Savage This class New topic: routing How do I get there from here? Overview Routing overview Intra vs. Inter-domain routing
An Approach for Detecting a Flooding Attack Based on Entropy Measurement of Multiple E-Mail Protocols
Journal of Appled Scence and Engneerng, Vol. 18, No. 1, pp. 79 88 (2015) DOI: 10.6180/jase.2015.18.1.10 An Approach for Detectng a Floodng Attack Based on Entropy Measurement of Multple E-Mal Protocols
RESEARCH ON DUAL-SHAKER SINE VIBRATION CONTROL. Yaoqi FENG 1, Hanping QIU 1. China Academy of Space Technology (CAST) yaoqi.feng@yahoo.
ICSV4 Carns Australa 9- July, 007 RESEARCH ON DUAL-SHAKER SINE VIBRATION CONTROL Yaoq FENG, Hanpng QIU Dynamc Test Laboratory, BISEE Chna Academy of Space Technology (CAST) yaoq.feng@yahoo.com Abstract
Project Networks With Mixed-Time Constraints
Project Networs Wth Mxed-Tme Constrants L Caccetta and B Wattananon Western Australan Centre of Excellence n Industral Optmsaton (WACEIO) Curtn Unversty of Technology GPO Box U1987 Perth Western Australa
Hedging Interest-Rate Risk with Duration
FIXED-INCOME SECURITIES Chapter 5 Hedgng Interest-Rate Rsk wth Duraton Outlne Prcng and Hedgng Prcng certan cash-flows Interest rate rsk Hedgng prncples Duraton-Based Hedgng Technques Defnton of duraton
NPAR TESTS. One-Sample Chi-Square Test. Cell Specification. Observed Frequencies 1O i 6. Expected Frequencies 1EXP i 6
PAR TESTS If a WEIGHT varable s specfed, t s used to replcate a case as many tmes as ndcated by the weght value rounded to the nearest nteger. If the workspace requrements are exceeded and samplng has
Everybody needs somebody: Modeling social and grouping behavior on a linear programming multiple people tracker
Everybody needs somebody: Modelng socal and groupng behavor on a lnear programmng multple people tracker Laura Leal-Taxe, Gerard Pons-Moll and Bodo Rosenhahn Insttute for Informaton Processng (TNT) Lebnz
Assignment #3 Routing and Network Analysis. CIS3210 Computer Networks. University of Guelph
Assignment #3 Routing and Network Analysis CIS3210 Computer Networks University of Guelph Part I Written (50%): 1. Given the network graph diagram above where the nodes represent routers and the weights
I. ADDITIONAL EVALUATION RESULTS. A. Environment
1 A. Environment I. ADDITIONAL EVALUATION RESULTS The tests have been performed in a virtualized environment with Mininet 1.0.0 [?]. Mininet is tool to create a virtual network running actual kernel, switch
A Parallel Architecture for Stateful Intrusion Detection in High Traffic Networks
A Parallel Archtecture for Stateful Intruson Detecton n Hgh Traffc Networks Mchele Colajann Mrco Marchett Dpartmento d Ingegnera dell Informazone Unversty of Modena {colajann, marchett.mrco}@unmore.t Abstract
Traffic State Estimation in the Traffic Management Center of Berlin
Traffc State Estmaton n the Traffc Management Center of Berln Authors: Peter Vortsch, PTV AG, Stumpfstrasse, D-763 Karlsruhe, Germany phone ++49/72/965/35, emal peter.vortsch@ptv.de Peter Möhl, PTV AG,
NMT EE 589 & UNM ME 482/582 ROBOT ENGINEERING. Dr. Stephen Bruder NMT EE 589 & UNM ME 482/582
NMT EE 589 & UNM ME 482/582 ROBOT ENGINEERING Dr. Stephen Bruder NMT EE 589 & UNM ME 482/582 7. Root Dynamcs 7.2 Intro to Root Dynamcs We now look at the forces requred to cause moton of the root.e. dynamcs!!
Distance Degree Sequences for Network Analysis
Universität Konstanz Computer & Information Science Algorithmics Group 15 Mar 2005 based on Palmer, Gibbons, and Faloutsos: ANF A Fast and Scalable Tool for Data Mining in Massive Graphs, SIGKDD 02. Motivation
Course outline. Financial Time Series Analysis. Overview. Data analysis. Predictive signal. Trading strategy
Fnancal Tme Seres Analyss Patrck McSharry patrck@mcsharry.net www.mcsharry.net Trnty Term 2014 Mathematcal Insttute Unversty of Oxford Course outlne 1. Data analyss, probablty, correlatons, vsualsaton
Internet Packets. Forwarding Datagrams
Internet Packets Packets at the network layer level are called datagrams They are encapsulated in frames for delivery across physical networks Frames are packets at the data link layer Datagrams are formed
CS335 Sample Questions for Exam #2
CS335 Sample Questions for Exam #2.) Compare connection-oriented with connectionless protocols. What type of protocol is IP? How about TCP and UDP? Connection-oriented protocols Require a setup time to
Economic Interpretation of Regression. Theory and Applications
Economc Interpretaton of Regresson Theor and Applcatons Classcal and Baesan Econometrc Methods Applcaton of mathematcal statstcs to economc data for emprcal support Economc theor postulates a qualtatve
A Hierarchical Anomaly Network Intrusion Detection System using Neural Network Classification
IDC IDC A Herarchcal Anomaly Network Intruson Detecton System usng Neural Network Classfcaton ZHENG ZHANG, JUN LI, C. N. MANIKOPOULOS, JAY JORGENSON and JOSE UCLES ECE Department, New Jersey Inst. of Tech.,
Monitoring Network Traffic to Detect Stepping-Stone Intrusion
Montorng etork Traffc to Detect Steng-Stone Intruson Janhua Yang, Byong Lee, Stehen S. H. Huang Deartment of Math and Comuter Scence, Bennett College E-mal: {jhyang, blee }@bennett.edu Deartment of Comuter
Damage detection in composite laminates using coin-tap method
Damage detecton n composte lamnates usng con-tap method S.J. Km Korea Aerospace Research Insttute, 45 Eoeun-Dong, Youseong-Gu, 35-333 Daejeon, Republc of Korea yaeln@kar.re.kr 45 The con-tap test has the
Multihoming and Multi-path Routing. CS 7260 Nick Feamster January 29. 2007
Multihoming and Multi-path Routing CS 7260 Nick Feamster January 29. 2007 Today s Topic IP-Based Multihoming What is it? What problem is it solving? (Why multihome?) How is it implemented today (in IP)?
Subnet Based Internet Topology Generation
Subnet Based Internet Topology Generation Mehmet Burak AKGÜN with Mehmet Hadi GÜNEŞ ISMA 2011 Workshop on Active Internet Measurements Outline Introduction Related Work Methodology Algortihm Results Future
Study on Model of Risks Assessment of Standard Operation in Rural Power Network
Study on Model of Rsks Assessment of Standard Operaton n Rural Power Network Qngj L 1, Tao Yang 2 1 Qngj L, College of Informaton and Electrcal Engneerng, Shenyang Agrculture Unversty, Shenyang 110866,
A hybrid global optimization algorithm based on parallel chaos optimization and outlook algorithm
Avalable onlne www.ocpr.com Journal of Chemcal and Pharmaceutcal Research, 2014, 6(7):1884-1889 Research Artcle ISSN : 0975-7384 CODEN(USA) : JCPRC5 A hybrd global optmzaton algorthm based on parallel
How To Detect An 802.11 Traffc From A Network With A Network Onlne Onlnet
IEEE TRANSACTIONS ON MOBILE COMPUTING, VOL. X, NO. X, XXX 2008 1 Passve Onlne Detecton of 802.11 Traffc Usng Sequental Hypothess Testng wth TCP ACK-Pars We We, Member, IEEE, Kyoungwon Suh, Member, IEEE,
Lecture 2.1 : The Distributed Bellman-Ford Algorithm. Lecture 2.2 : The Destination Sequenced Distance Vector (DSDV) protocol
Lecture 2 : The DSDV Protocol Lecture 2.1 : The Distributed Bellman-Ford Algorithm Lecture 2.2 : The Destination Sequenced Distance Vector (DSDV) protocol The Routing Problem S S D D The routing problem
LiMoSense: live monitoring in dynamic sensor networks
Dstrb. Comput. DOI 10.1007/s00446-014-0213-8 LMoSense: lve montorng n dynamc sensor networks Ittay Eyal Idt Kedar Raphael Rom Receved: 7 Aprl 2013 / Accepted: 19 March 2014 Sprnger-Verlag Berln Hedelberg
Module 15: Network Structures
Module 15: Network Structures Background Topology Network Types Communication Communication Protocol Robustness Design Strategies 15.1 A Distributed System 15.2 Motivation Resource sharing sharing and
PRECISE GPS POSITIONING IMPROVEMENTS BY REDUCING ANTENNA AND SITE DEPENDENT EFFECTS
PRECISE GPS POSITIONING IMPROVEMENTS BY REDUCING ANTENNA AND SITE DEPENDENT EFFECTS Günter Seeber, Falko Menge, Chrstof Völksen Insttut für Erdmessung, Unverstät Hannover, D-3167 Hannover, Germany Gerhard
An Interest-Oriented Network Evolution Mechanism for Online Communities
An Interest-Orented Network Evoluton Mechansm for Onlne Communtes Cahong Sun and Xaopng Yang School of Informaton, Renmn Unversty of Chna, Bejng 100872, P.R. Chna {chsun,yang}@ruc.edu.cn Abstract. Onlne
Introduction CONTENT. - Whitepaper -
OneCl oud ForAl l YourCr t c al Bus nes sappl c at ons Bl uew r esol ut ons www. bl uew r e. c o. uk Introducton Bluewre Cloud s a fully customsable IaaS cloud platform desgned for organsatons who want
Application of Quasi Monte Carlo methods and Global Sensitivity Analysis in finance
Applcaton of Quas Monte Carlo methods and Global Senstvty Analyss n fnance Serge Kucherenko, Nlay Shah Imperal College London, UK skucherenko@mperalacuk Daro Czraky Barclays Captal DaroCzraky@barclayscaptalcom
On the pricing of illiquid options with Black-Scholes formula
7 th InternatonalScentfcConferenceManagngandModellngofFnancalRsks Ostrava VŠB-TU Ostrava, Faculty of Economcs, Department of Fnance 8 th 9 th September2014 On the prcng of llqud optons wth Black-Scholes
A Network Management Software Based on Secure Shell (SSH) Channels. and Java Universal Network Graph (JUNG)
A Network Management Software Based on Secure Shell (SSH) Channels and Java Universal Network Graph (JUNG) Students: Simran Khalsa, Gerald Castaneda, Ruben Rivera. Mentor: Dr. Jorge Crichigno Department
Measuring Homophily in Social Network: Identification of Flow of Inspiring Influence under New Vistas of Evolutionary Dynamics
(IJACSA) Internatonal Journal of Advanced Computer Scence and Applcatons, Measurng Homophly n Socal Network: Identfcaton of Flow of Insprng Influence under New Vstas of Evolutonary Dynamcs Hameed Al-Qaher
Available online www.bmdynamics.com ISSN: 2047-7031. Society for Business and Management Dynamics
Vol., No.6, Dec 20, pp.2332 Comparson of the Ratng of Socal Securty Insurance Branches of Sstan and Baluchestan Provnce Based on Effcency Usng DEA and SFA Models Peymaneh ahmad pour, Nazar Dahmardeh 2,
Faraday's Law of Induction
Introducton Faraday's Law o Inducton In ths lab, you wll study Faraday's Law o nducton usng a wand wth col whch swngs through a magnetc eld. You wll also examne converson o mechanc energy nto electrc energy
Configuring a Gateway of Last Resort Using IP Commands
Configuring a Gateway of Last Resort Using IP Commands Document ID: 16448 Contents Introduction Prerequisites Requirements Components Used Conventions ip default gateway ip default network Flag a Default
Feature selection for intrusion detection. Slobodan Petrović NISlab, Gjøvik University College
Feature selecton for ntruson detecton Slobodan Petrovć NISlab, Gjøvk Unversty College Contents The feature selecton problem Intruson detecton Traffc features relevant for IDS The CFS measure The mrmr measure
WAN Wide Area Networks. Packet Switch Operation. Packet Switches. COMP476 Networked Computer Systems. WANs are made of store and forward switches.
Routing WAN Wide Area Networks WANs are made of store and forward switches. To there and back again COMP476 Networked Computer Systems A packet switch with two types of I/O connectors: one type is used
How To Understand The Network Of A Network
Roles in Networks Roles in Networks Motivation for work: Let topology define network roles. Work by Kleinberg on directed graphs, used topology to define two types of roles: authorities and hubs. (Each
Estimation of Dispersion Parameters in GLMs with and without Random Effects
Mathematcal Statstcs Stockholm Unversty Estmaton of Dsperson Parameters n GLMs wth and wthout Random Effects Meng Ruoyan Examensarbete 2004:5 Postal address: Mathematcal Statstcs Dept. of Mathematcs Stockholm
Train Timetabling New Approach
Tran Tmetablng New Approach Tomáš Robenek CUSO Doctoral Programme n Operatons Research Sprng Semnar January 13, 2015 1 / 27 Lberalsaton 01.01.2010 2 / 27 Lberalsaton Overvew 3 / 27 Publc Sector Accessblty/Moblty
Survival analysis methods in Insurance Applications in car insurance contracts
Survval analyss methods n Insurance Applcatons n car nsurance contracts Abder OULIDI 1 Jean-Mare MARION 2 Hervé GANACHAUD 3 Abstract In ths wor, we are nterested n survval models and ther applcatons on
Operating System Concepts. Operating System 資 訊 工 程 學 系 袁 賢 銘 老 師
Lecture 7: Distributed Operating Systems A Distributed System 7.2 Resource sharing Motivation sharing and printing files at remote sites processing information in a distributed database using remote specialized
Data Center Content Delivery Network
BM 465E Distributed Systems Lecture 4 Networking (cont.) Mehmet Demirci Today Overlay networks Data centers Content delivery networks Overlay Network A virtual network built on top of another network Overlay
The Joint Degree Distribution as a Definitive Metric of the Internet AS-level Topologies
The Joint Degree Distribution as a Definitive Metric of the Internet AS-level Topologies Priya Mahadevan, Dimitri Krioukov, Marina Fomenkov, Brad Huffaker, Xenofontas Dimitropoulos, kc claffy, Amin Vahdat
Marginal Benefit Incidence Analysis Using a Single Cross-section of Data. Mohamed Ihsan Ajwad and Quentin Wodon 1. World Bank.
Margnal Beneft Incdence Analyss Usng a Sngle Cross-secton of Data Mohamed Ihsan Ajwad and uentn Wodon World Bank August 200 Abstract In a recent paper, Lanjouw and Ravallon proposed an attractve and smple
Fast Reroute Techniques in MPLS Networks. George Swallow swallow@cisco.com
Fast Reroute Techniques in MPLS Networks George Swallow swallow@cisco.com Agenda What are your requirements? The solution space U-turns Traffic Engineering for LDP Traffic Engineering Some Observations
A New Technique for Vehicle Tracking on the Assumption of Stratospheric Platforms. Department of Civil Engineering, University of Tokyo **
Fuse, Taash A New Technque for Vehcle Tracng on the Assumton of Stratosherc Platforms Taash FUSE * and Ehan SHIMIZU ** * Deartment of Cvl Engneerng, Unversty of Toyo ** Professor, Deartment of Cvl Engneerng,
Analysis of Premium Liabilities for Australian Lines of Business
Summary of Analyss of Premum Labltes for Australan Lnes of Busness Emly Tao Honours Research Paper, The Unversty of Melbourne Emly Tao Acknowledgements I am grateful to the Australan Prudental Regulaton
EE627 Lecture 22. Multihoming Route Control Devices
EE627 Lecture 22 Multihoming Route Control Devices 1 Multihoming Connect to multiple ISPs Provide reliability from access link/isp failures Potential for load balancing Intelligent Route Control Devices
Reliable State Monitoring in Cloud Datacenters
Relable State Montorng n Cloud Datacenters Shcong Meng Arun K. Iyengar Isabelle M. Rouvellou Lng Lu Ksung Lee Balaj Palansamy Yuzhe Tang College of Computng, Georga Insttute of Technology, Atlanta, GA
Chapter 14: Distributed Operating Systems
Chapter 14: Distributed Operating Systems Chapter 14: Distributed Operating Systems Motivation Types of Distributed Operating Systems Network Structure Network Topology Communication Structure Communication
Reinforcement Learning for Quality of Service in Mobile Ad Hoc Network (MANET)
Renforcement Learnng for Qualty of Servce n Moble Ad Hoc Network (MANET) *T.KUMANAN AND **K.DURAISWAMY *Meenaksh College of Engneerng West K.K Nagar, Cheena-78 **Dean/academc,K.S.R College of Technology,Truchengode
Portfolio Loss Distribution
Portfolo Loss Dstrbuton Rsky assets n loan ortfolo hghly llqud assets hold-to-maturty n the bank s balance sheet Outstandngs The orton of the bank asset that has already been extended to borrowers. Commtment
PERFORMANCE OF MOBILE AD HOC NETWORKING ROUTING PROTOCOLS IN REALISTIC SCENARIOS
PERFORMANCE OF MOBILE AD HOC NETWORKING ROUTING PROTOCOLS IN REALISTIC SCENARIOS Julian Hsu, Sameer Bhatia, Mineo Takai, Rajive Bagrodia, Scalable Network Technologies, Inc., Culver City, CA, and Michael
8.5 UNITARY AND HERMITIAN MATRICES. The conjugate transpose of a complex matrix A, denoted by A*, is given by
6 CHAPTER 8 COMPLEX VECTOR SPACES 5. Fnd the kernel of the lnear transformaton gven n Exercse 5. In Exercses 55 and 56, fnd the mage of v, for the ndcated composton, where and are gven by the followng
GRAVITY DATA VALIDATION AND OUTLIER DETECTION USING L 1 -NORM
GRAVITY DATA VALIDATION AND OUTLIER DETECTION USING L 1 -NORM BARRIOT Jean-Perre, SARRAILH Mchel BGI/CNES 18.av.E.Beln 31401 TOULOUSE Cedex 4 (France) Emal: jean-perre.barrot@cnes.fr 1/Introducton The
denote the location of a node, and suppose node X . This transmission causes a successful reception by node X for any other node
Fnal Report of EE359 Class Proect Throughput and Delay n Wreless Ad Hoc Networs Changhua He changhua@stanford.edu Abstract: Networ throughput and pacet delay are the two most mportant parameters to evaluate
INVESTIGATION OF VEHICULAR USERS FAIRNESS IN CDMA-HDR NETWORKS
21 22 September 2007, BULGARIA 119 Proceedngs of the Internatonal Conference on Informaton Technologes (InfoTech-2007) 21 st 22 nd September 2007, Bulgara vol. 2 INVESTIGATION OF VEHICULAR USERS FAIRNESS
Canon NTSC Help Desk Documentation
Canon NTSC Help Desk Documentaton READ THIS BEFORE PROCEEDING Before revewng ths documentaton, Canon Busness Solutons, Inc. ( CBS ) hereby refers you, the customer or customer s representatve or agent
Topical Workshop for PhD students Adsorption and Diffusion in MOFs Institut für Nichtklassische Chemie, Germany, www.uni-leipzig.
Gas Separaton and Purfcaton Measurement of Breakthrough Curves Topcal Workshop for PhD students Adsorpton and Dffuson n MOFs Adsorpton on Surfaces / Separaton effects Useful features Thermodynamc effect
Chapter 10 Link-State Routing Protocols
Chapter 10 Link-State Routing Protocols CCNA2-1 Chapter 10 Note for Instructors These presentations are the result of a collaboration among the instructors at St. Clair College in Windsor, Ontario. Thanks
A FEATURE SELECTION AGENT-BASED IDS
A FEATURE SELECTION AGENT-BASED IDS Emlo Corchado, Álvaro Herrero and José Manuel Sáz Department of Cvl Engneerng, Unversty of Burgos C/Francsco de Vtora s/n., 09006, Burgos, Span Phone: +34 947259395,
Link-State Routing Protocols
Link-State Routing Protocols Malin Bornhager Halmstad University Session Number 2002, Svenska-CNAP Halmstad University 1 Objectives Link-state routing protocol Single-area OSPF concepts Single-area OSPF
O 10.16.1.0/27 [110/129] via 192.168.1.5, 00:00:05, Serial0/0/1
![O 10.16.1.0/27 [110/129] via 192.168.1.5, 00:00:05, Serial0/0/1](/thumbs/39/20242582.jpg "O 10.16.1.0/27 [110/129] via 192.168.1.5, 00:00:05, Serial0/0/1")
1 Which two statements are true regarding the advantages of the use of static routes? (Choose increased security reduced effort in configuring routes the administrator maintains control over routing easier
Finite Math Chapter 10: Study Guide and Solution to Problems
Fnte Math Chapter 10: Study Gude and Soluton to Problems Basc Formulas and Concepts 10.1 Interest Basc Concepts Interest A fee a bank pays you for money you depost nto a savngs account. Prncpal P The amount
CROSS LAYER BASED MULTIPATH ROUTING FOR LOAD BALANCING
CHAPTER 6 CROSS LAYER BASED MULTIPATH ROUTING FOR LOAD BALANCING 6.1 INTRODUCTION The technical challenges in WMNs are load balancing, optimal routing, fairness, network auto-configuration and mobility
HALL EFFECT SENSORS AND COMMUTATION
OEM770 5 Hall Effect ensors H P T E R 5 Hall Effect ensors The OEM770 works wth three-phase brushless motors equpped wth Hall effect sensors or equvalent feedback sgnals. In ths chapter we wll explan how
Chapter 16: Distributed Operating Systems
Module 16: Distributed ib System Structure, Silberschatz, Galvin and Gagne 2009 Chapter 16: Distributed Operating Systems Motivation Types of Network-Based Operating Systems Network Structure Network Topology