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Traffic dimensioning and traffic measurements in IP networks. Konkoly Lászlóné konkoly47@t-online.hu. Traffic dimensioning. The objectives of traffic dimensioning. Main objective:. TRAFFIC FORECAST. QUANTITY ORGANIZATION of NETWORK ELEMENTS. PRESCRIBED. SERVICE QUALITY. Organization:

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Traffic dimensioning and traffic measurements in IP networks


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    1. Traffic dimensioning and traffic measurements inIP networks Konkoly Lászlóné konkoly47@t-online.hu

    2. Traffic dimensioning Konkoly Lászlóné/Traffic dimensioning and traffic measurements in IP networks

    3. The objectives of traffic dimensioning Main objective: TRAFFIC FORECAST • QUANTITY • ORGANIZATION • of • NETWORK ELEMENTS PRESCRIBED SERVICE QUALITY • Organization: • Topology (ring, meshed etc.) • Traffic routing (OSPF, IS-IS) • Transport (SDH, WDM etc.) • Queueing mechanisms etc. Aim: low cost high utilization of equipments Input data: New services (business, residential) Forecasts about number of customers (for old and new services) Probable changes in usage (e.g. changes in uplink utilization) Equipments and capabilities of the existing network Planning directives etc. Konkoly Lászlóné/Traffic dimensioning and traffic measurements in IP networks

    4. Traffic dimensioning among network planning tasks Traffic measurements on the existing network Traffic analysis Traffic forecast Decide on changes of: network topology, traffic routing architecture, network redundancies, new functionalities, quality of service etc. N E T W O R K P LA N N I N G Traffic dimensioning Network level Link and equipment level Planning tasks needed for building the planned network Traffic theory Simulation and other planning tools Planning changes in network management and network operation Probability theory Stochastic processes Konkoly Lászlóné/Traffic dimensioning and traffic measurements in IP networks

    5. Dimensioning methods in PSTN networks(PSTN=Public Switched Telephone Network) Dimensioning trunks (first-choice circuit groups): Erlang 1. (B) formula(loss systems, infinite population of sources, Poisson arrival process, exponentially distributed holding times, full availability group of circuits) Notice: the formula is valid for general holding time distributions as well Erlang 2. (C) formula (waiting systems) Engset formula (finite population of sources) smooth traffic V/M =1 Dimensioning alternate routing systems (second-choice circuit groups): T Tandem exchange Overflow traffic is already bursty! V/M > 1 Erlang B formula Second-choice circuit group M1,V1 ERT (Equivalent Random Theory) method M=∑Mi Mi=Ai* ENi(Ai) V=∑Vi Vi=Mi(1-Mi+Ai/(Ni+1+Mi-Ai)) Subscribers C D1 Subscribers First-choice circuit group Subscribers D2 Local exchange D3 Subscribers Local exchanges Dn Subscribers Konkoly Lászlóné/Traffic dimensioning and traffic measurements in IP networks

    6. Traffic dimensioning in ISDN networks(ISDN=Integrated services digital network) PSTN: telephone (or telefax) calls need 1 time slot 64 kbit/sec by customers (homogenous sources) n*64 kbit/sec by customers n=1, 2, 6, 12, 16 … (different service classes) ISDN: different services need 1 or moretime slots Services: telephone, video-telephony, data-transmission, video-conference etc. Traffic mix on shared resources is bursty ! Konkoly Lászlóné/Traffic dimensioning and traffic measurements in IP networks

    7. Multi-dimensional Erlang formula/1 Notation: N : number of circuits M : number of service classes (Poisson arrival by service classes) ai : offered traffic (in number of calls) for the ith service class di : bandwidth factor (number of time slots) for the ith service class Calculation of state probabilities: Blocking probability for the ith service class: Konkoly Lászlóné/Traffic dimensioning and traffic measurements in IP networks

    8. Multi-dimensional Erlang formula/2 N=100 d1=1 a1=1→35 erlang d2=16 a2=64 erlang (in time slot units) Erlang B formula Multi-dimensional Erlang formula • Blocking probability for the bigger bandwidth service classwill be higher • Erlang-B formula under-estimates blocking for both service classes • Blocking curve for calls using 1 time slot will be „wavering” • Conclusion: shared links can not be used without traffic control • Solution: blocking-equalizer trunk reservation (e.g. new telephone calls are not allowed entering the system if there are only 16 free time slots) Konkoly Lászlóné/Traffic dimensioning and traffic measurements in IP networks

    9. Comparing features of telephone (circuit-switched) and IP (packet-switched) traffic Konkoly Lászlóné/Traffic dimensioning and traffic measurements in IP networks

    10. Comparing traffic dimensioning methodologies applied for telephone and for IP traffic [5] Konkoly Lászlóné/Traffic dimensioning and traffic measurements in IP networks

    11. IP traffic classification – elastic and real-time traffic TCP=Transmission Control Protocol UDP=User Datagram Protocol Konkoly Lászlóné/Traffic dimensioning and traffic measurements in IP networks

    12. IP network structure outline IP core network 10GE PE(Provider Edge) n*GE, 10 GE Aggregation network n*GE, 10 GE GE= GigabitEthernet Access network 1- 8 Mbps Konkoly Lászlóné/Traffic dimensioning and traffic measurements in IP networks

    13. Simplified show of the triple-play service IP network Internet BRAS TV+STB DSLAM Data platform router splitter router PC Switch Switch Switch router HGW Switch router Telephone exchange Encoders, servers Switch/ router IP telephone analog telephone Access network Ethernet aggregation network Video platform PSTN network SSW gateways Voip platform Triple-play (3-play): 1. voice(VoIP=Voice over IP) 2. data (internet) 3.video (TV+VoD)VoD=Video on Demand DSLAM: Digital Subscriber Line Access Multiplexer BRAS: Broadband Remote Access Server Konkoly Lászlóné/Traffic dimensioning and traffic measurements in IP networks

    14. IP dimensioning tasks Link dimensioning tasks (simple examples): 1.task: How many ADSL user’s traffic can be aggregated on a given link if users have c kbit/s access speed and (m, σ) traffic parameters? IP core network LAN LAN Internet ? ISP1 ? ISP2 ISP3 Aggregating network LAN 2.task: How many LAN network’s traffic can be aggregated on a given link if LANs have c kbit/s access speed and (m, σ,H) traffic parameters? 3.task: Is it possible to reach bandwidth gain (and how much) if we use bigger bandwidth links instead of smaller ones? Konkoly Lászlóné/Traffic dimensioning and traffic measurements in IP networks

    15. Dimensioning principles/1: What about link dimensioning for the peak rate of customers ?? Pay attention! Waste of bandwidth ! Konkoly Lászlóné/Traffic dimensioning and traffic measurements in IP networks

    16. Dimensioning principles/2: What about link dimensioning for the mean rate of customers ?? Pay attention! Unsafe! Coincident traffic peaks can occur! Consequence: High packet loss, big packet delay and jitter (slow downloads, bad service performance) Konkoly Lászlóné/Traffic dimensioning and traffic measurements in IP networks

    17. Dimensioning principles/3: Konkoly Lászlóné/Traffic dimensioning and traffic measurements in IP networks

    18. Dimensioning principles/4: The concept of effective (or equivalent) bandwidth: Effective bandwidth (Eeff) is a portion of the link bandwidth C that is „ensured”(only administratively!) for a traffic sourcewith(m, σ, H) traffic parameters in order to fulfilthe expected service quality (ε). Eeff = f (C, m, σ, H, ε) where C: link bandwidth, m: mean of traffic, σ: dispersion of traffic H: Hurst parameter (self-similarity measure) ε : requirement for e.g. packet loss, delay, jitter n= C/ Eeff (n= number of users that can be aggregated on link C ) Konkoly Lászlóné/Traffic dimensioning and traffic measurements in IP networks

    19. Classification of statistical multiplexing methods Bufferless multiplexing(in case of small buffer capacity) Small buffer ensures small delay principle: aggregated traffic can exceed link capacity with small probability aim: expected small packet loss should be realized Advantage: simple methods dimensioning does not depend on the traffic correlations Disadvantage: moderate multiplexing gain Buffered multiplexing (in case of large buffer capacity) Maximum delay can be changed with buffer size settings principle: queue length can be exceeded with small probability aim: expected small packet loss should be realized Advantage: bigger multiplexing gain than in the bufferless case Disadvantage:more complex dimensioning procedures strongly depends on traffic correlations Konkoly Lászlóné/Traffic dimensioning and traffic measurements in IP networks

    20. Lindberger formula (Tidblom formula) [2, 6] Bufferless multiplexing: d: equivalent bandwidth m: mean traffic : traffic dispersion C: link bandwidth d=1.2m+602/C The formula is valid only in case of 10-9 loss probability (IP packet loss) and small (of the order of 100) buffer size. For ON-OFF sources: 2=m*(h-m) d=1.2m+60m(h-m)/C m h Konkoly Lászlóné/Traffic dimensioning and traffic measurements in IP networks

    21. Application of the Tidblom formula (generalization of the Lindberger method) d=am[1+3y(1-m/h)] if 3y min(3,h/m) d=am[1+3y2(1-m/h)] if 3 < 3y2  h/m d=ah otherwise, where y=(-2log Ploss)/(C/h) and a=1-(2log Ploss / 100) Effective bandwidth as a function of the link speed Konkoly Lászlóné/Traffic dimensioning and traffic measurements in IP networks

    22. Effective bandwidth in case of self-similar traffic sources [3,4] Ilkka Norros formula in case of buffered multiplexing: c(m,a) = m + B -(1-H)/H (m*a) 1/(2H) H: Hurst parameter (self-similarity measure, value in range 0.5-1) κ(H) : HH(1-H)1-H m: mean bit-rate of the traffic stream a: variance coefficient of the traffic stream (Ω2/m) Ω2 :variance of the number of bits measured for 1 sec intervals B: buffer size ε : packet loss probability Number of sources that can be admitted to a link of bandwidth C is expressed as: C/c(m,a) Konkoly Lászlóné/Traffic dimensioning and traffic measurements in IP networks

    23. Loadability of a 1 Gbps link with LAN flows of 10 Mbps peak bandwidth H = 0.8 buffer : 1.336 Mbyte Variance coefficient=90000 M=2.5Mbps Util=25% M=5Mbps Util=50% M=7.5Mbps Util=75% Utilization: 73-89 % Konkoly Lászlóné/Traffic dimensioning and traffic measurements in IP networks

    24. Delay calculation on a 1 Gb/s link - M/M/1 modelQuestion is: what load limit will ensure a given delay performance for packets in case of Poisson arrivals? Complementary distribution function of delay in case of 1 Gb/s link 1,2 P(x>t) 1 Utilization=0.8 0,8 Utilization=0.9 Utilization=0.95 0,6 0,4 0,2 0 0 0,1 0,2 0,3 0,4 0,5 0,6 0,7 0,8 msec M/M/1 model: Waiting places Link (server) Mean packet size: 1500 byte Link speed: 1Gb/s For waiting calls: P(waiting time > t) =e –t(1-A)/s A: link utilization (offered traffic) Average service time (s) is a function of the mean packet size and of link speed: s = 1500 byte/1 Gb/s=0.012 msec Applicable only in cases when traffic is „smooth” enough ! Konkoly Lászlóné/Traffic dimensioning and traffic measurements in IP networks

    25. Introduction of the Processor Sharing (PS) model/1 (simple case) TCP congestion control – the saw-tooth diagram Bandwidth [kbit/sec] Time Modeling TCP fairness: in ideal cases TCP sources share available bandwidth fairly on bottleneck links Konkoly Lászlóné/Traffic dimensioning and traffic measurements in IP networks

    26. + * 1 E ( R , R RO ) X X ( ) = * = * 2 E T ( X ) f * - C R ( 1 RO ) C user user Erlang 2.formula for fractional circuit numbers delay factor (>1) reciproc : Fun factor (<1) ideal download time Introduction of the processor sharing model/2 (simple case) Basic idea: the link services the users at their access rate deals with not all demand at a time! - some users are waiting in a queue file download time = file download time at access speed + waiting time Notations: X: size of the file to be downloaded (Kbit) T(X): download time for X , E(T(X)) :expectation value of the download time T(X) Cuser : download access peak rate of a customer (Kbit/s) C: link capacity (Kbit/s), RO: link utilization (measurable parameter) R=C/ Cuser : important model parameter, the C link can accomodate R times the user’speak rate Advantages: does not need information about traffic mix characteristics takes into account only the average load of the link Konkoly Lászlóné/Traffic dimensioning and traffic measurements in IP networks

    27. Results of the processor sharing model = C Variation of the delay factor as a function of link utilization (C=1Mbps – 10 Mbps), Cuser=512 Kbps Konkoly Lászlóné/Traffic dimensioning and traffic measurements in IP networks

    28. IP network traffic analysis by using flow and packet based measurements Konkoly Lászlóné/Traffic dimensioning and traffic measurements in IP networks

    29. IP traffic measurement types Passive Active (workload measurements) (test traffic generation) link load, processor load, number of connections on a link, packet and flow level data about connections, traffic per user, etc. packet delay packet delay variance (jitter) RTT (Round Trip Time) packet loss Passive measurement tools usable in network planning: MRTG (Multi-Router Traffic Grapher) - measures aggregated traffic on links Netflow - measures traffic flows Tools abovedo not give information about: packet level features (e.g. packet size distribution, input process of packets), variance and burstiness, self-similarity, auto-correlations etc. Protocol analyzer measurements are needed to be able to analyze the traffic on the packet level ! Konkoly Lászlóné/Traffic dimensioning and traffic measurements in IP networks

    30. MRTG (Multi-Router Traffic Grapher) - Tobias Oetiker By using this tool, statistics can be obtained from the inner counters of routers (MIB - Management Information Base) Appropriate protocol (e.g. SNMP=Simple Network Management Protocol) can be used for querying routers ■MRTG is a tool to collect monitor save and store traffic load of links MRTG uses cyclic database (efficient buffer utilization) ■Aggregates data daily data → → weekly data → → monthly data → → yearly data yearly monthly daily weekly Konkoly Lászlóné/Traffic dimensioning and traffic measurements in IP networks

    31. MRTG measurement example Budapest Internet Exchange (www.bix.hu)/1 Daily traffic profile 5 minute’s averages Weekly traffic profile 30 minute’s averages Konkoly Lászlóné/Traffic dimensioning and traffic measurements in IP networks

    32. MRTG measurement example Budapest Internet Exchange (www.bix.hu)/2 Monthly traffic profile 2 hour’s averages Yearly traffic profile Daily averages Konkoly Lászlóné/Traffic dimensioning and traffic measurements in IP networks

    33. NetFlow – collecting IP traffic information on the flow-level Flow: unidirectional sequence of packets aggregated by some features Basic information involved in the flows: Source IP address, Destination IP address Source port for UDP or TCP Destination port for UDP or TCP IP protocol, ingress interface IP Type of Service Different aggregation schemes (e.g. Call record, AS record) Further information involved in NetFlow records: start and end-time of the flow (flow holding time) carried bytes and carried packets in the flow (mean packet size)etc. : Konkoly Lászlóné/Traffic dimensioning and traffic measurements in IP networks

    34. An example for analyzing NetFlow measurements/1(data from 2005) Changes in the ratio of peer-to-peer file downloads and web browsing Night 1-2 o’clock Night 4-5 o’clock Morning 8-9 o’clock TCP other: peer-to-peer (P2P) file download TCP www: web browsing Konkoly Lászlóné/Traffic dimensioning and traffic measurements in IP networks

    35. An example for analyzing NetFlow measurements/2(data from 2006) Traffic partition according to applications Konkoly Lászlóné/Traffic dimensioning and traffic measurements in IP networks

    36. Measurement methods on packet level Object: save packet headers and elaborate information gained from the headers GE interface traffic mirrored on a free interface (port monitoring) SnifferBook Ultra 256 MB memory frequent archiving, packet loss • PC+ appropriate measurement card • Data saved directly to hard disc (640 GB) • Measurements done through several days • 0 % packet loss PC + software (Sniffer portable) • Results may be used for different tasks: • Explore bottlenecks in the network • Detect and analyze special traffic types (e.g. Skype or other peer-to-peer) • Outline network performance measures • (packet loss, delay, jitter, burstiness etc.) • Collect packet length statistics Konkoly Lászlóné/Traffic dimensioning and traffic measurements in IP networks

    37. Searching bottleneck links in IP networks/1 Object:conclude for blocking realized farther from the measurement point on the basis of packet header statistics calculated from measurement data collected on a given link X-measure – peakedness (V/M) of the throughput of TCP flows „relatively small values on bottleneck links” Konkoly Lászlóné/Traffic dimensioning and traffic measurements in IP networks

    38. Delay factor investigations „Assumption: on bottleneck links the value of the delay factor is >3” Investigation of the Packet Interarrival Times (4.moment=PIT-kurtosis) „if the bottleneck is before the measurement point” – peaks can be seen in the 4.moments Packet loss „In case of TCP traffic its higher size does not imply bottleneck” : its value can be a similar order of magnitude on bottleneck links as in cases without blocking ■ Connection bandwidth – depends on several factors, so its small value does not imply bottleneck definitely Searching bottleneck links in IP networks/2 Konkoly Lászlóné/Traffic dimensioning and traffic measurements in IP networks

    39. Examining the micro-structure of traffic • Burstiness investigations (msec) – for capacity planning • Determining self similarity - Hurst parameter (H=0.5 - 0,7) Method: R/S (Rescaled Range) analysis • Packet interarrival time investigations (if it can be supposed to be Poissonian) Konkoly Lászlóné/Traffic dimensioning and traffic measurements in IP networks

    40. Packet size statistics/1 Konkoly Lászlóné/Traffic dimensioning and traffic measurements in IP networks

    41. Packet size statistics/2 Packet size distribution and density functions Konkoly Lászlóné/Traffic dimensioning and traffic measurements in IP networks

    42. Identification of P2P traffic Main features of P2P applications: Continuously changing and often encrypted protocols Random,fix, default portsor usage of port 80 (HTTP port!) Big-sized (~1490 byte) packets in file download Some heuristics: 1. Known non P2P applications (except http) can be filtered according to source_port /destination_port e.g. FTP:21, telnet:23, ssh:22, http, web:80 2. Identification and separation of default P2P ports: e.g. gnutella:6346, Kazaa:1214 3. Separation of P2P applications using HTTP ports (www and P2P separation) www: several parallel connections between source and destination we can identify web servers P2P: several connections with many different hosts 4. IP pairs having TCP and UDP connections at the same time → P2P traffic 5. If a host uses a given fix port several times → P2P traffic 6. Carried data > 1 MByte and/or holding time > 10 minutes Konkoly Lászlóné/Traffic dimensioning and traffic measurements in IP networks

    43. Usable for: Internet telephony video-telephony Video and audio conference Instant messaging (chat) file transfer Inside the Skype network it is free of charge There is a possibility for: Skype In Skype Out Advantages: Skype bypasses NAT and firewalls Reasonable call quality if available bandwidth is only 32 Kbit/s (due to its VBR codec) Tolerates higher packet losses Disadvantage: no guaranteed quality of service Skype update server Skype login server (user names, update Buddy-list server passwords) messages login messages Partner-list updates Super Node (Boot-strap SN) Directs communication, gives address services, connects clients being behind NAT or firewall ordinary node (client) Skype traffic identification [8,9] Konkoly Lászlóné/Traffic dimensioning and traffic measurements in IP networks

    44. Characteristics of Skype P2P application-layer protocol, encryptedtherefore practically unsolvable Only transport layer protocols can be analyzed (IP addresses, TCP/UDP ports) Its identification can not be done unambiguously on the basis of bandwidth and packet size, because other applications can have the same statistics. Packet size Bandwidth 20-80 Kbit/sec Average 38 -45 Kbit/sec Konkoly Lászlóné/Traffic dimensioning and traffic measurements in IP networks

    45. Skype identification/1 1. Connection with servers (port- and IP address-based identification) Can be used when the user enters (logins) into the Skype network after starting the measurement. – Login Server (LS) – user identification Direct connection: client→LS indirect: client→SN→LS Konkoly Lászlóné/Traffic dimensioning and traffic measurements in IP networks

    46. – Bootstrap Super Node – sure connection only at first login – Update Server – for searching new software version – Buddy-list Server – provide partner-list updates The client will be connected rarely to the above servers, therefore the absence of these connections does not prove a denial of being a Skype user. 180 Frequency of occurrences of different packet sizes according to arrival-time modulo 60 160 Frequency 140 120 100 80 60 40 20 0 0 10 20 30 40 50 60 arrival-time modulo 60 Skype identification/2 2. SC ↔ SN signalling connection Can be used also in cases when the user made its login before starting the measurement. Typical traffic sample in the signalling traffic ! In outgoing direction (SC→SN) packets of a special packet size show 1 minute periodicity (periodic „heart-beat” – keep alive- messages) „heart-beat” packets Konkoly Lászlóné/Traffic dimensioning and traffic measurements in IP networks

    47. Service Provider GURU planning tool OPNET Technologies, Inc. NetDoctor For validating network configurations FlowAnalysis Reachability Analysis Failure Analysis Routing simulator – for modeling and analysing the routing procedure, determining link loads quick – good for examining big networks N e t w o r k a n a l y s i s Performance analysis for applications and for network resources Long run times– accurate results Discrete Event Simulation (DES) Hybrid Simulation Shorter run times – but less accurate results MPLS Traffic Engineering design Network load and performance optimization (using optimal traffic routing instead of OSPF) Planning OSPF:Open Shortest Path first MPLS: Multi-Protocol Label Switching Konkoly Lászlóné/Traffic dimensioning and traffic measurements in IP networks

    48. FLEXPLANET network planning tool Interfaces with network databases, inventories Auxiliary planning data: coordinates, hierarchy etc. FLEXPLANET (building layered network model) lists Network layers: IP, Ethernet, SDH/PDH, WDM, optical network Traffic and availability analysis grafical representation Network planner Konkoly Lászlóné/Traffic dimensioning and traffic measurements in IP networks

    49. References [1] J. Charzinski: Fun factor for dimensioning elastic traffic http://www.jcho.de/jc/Pubs/itc2000-col.pdf [2] Lindberger, K.: Dimensioning and Design methods for Integrated ATM Networks Proceedings of ITC 14. Antibes Juan-les-Pins, France [3] A. Patel: Statistical Multiplexing of Self-Similar Traffic: Theoretical and Simulation Results http://www.cs.usask.ca/faculty/carey/papers/statmuxing.ps [4]: S. Bodamer, J. Charzinsky: Evaluation of Effective Bandwidth Schemes for self-Similar traffic, http://www.ikr.uni-stuttgart.de/Content/Publications/Archive/Bo_IP00_32462.pdf [5] W. Paxson, S. Floyd: Wide-Area traffic: The failure of Poisson modeling http://www.cs.berkeley.edu/~istoica/classes/cs268/05/papers/paxson95widearea.pdf [6] Cost-257, Final Report http://www3.informatik.uni-wuerzburg.de/cost/FinalReport/report_web.pdf [7] Converged networks and services. Internal lecture presentation material of Norwegian University of Science and Technology http://www.item.ntnu.no/fag/ttm7/Lectures/4_1_Convergence_Fix_Net.ppt [8] Salman A. Baset and Henning Schulzrinne: An Analysis of the Skype Peer-to-Peer Internet Telephony Protocol, Department of Computer Science Columbia University, New York NY 10027, September 15, 2004 http://arxiv.org/ftp/cs/papers/0412/0412017.pdf [9] Dario Rossi, Marco Mellia, Michela Meo: A Detailed Measurement of Skype Network Traffic http://perso.telecom-paristech.fr/~drossi/paper/rossi08iptps.pdf Konkoly Lászlóné/Traffic dimensioning and traffic measurements in IP networks

    50. Thank you for your attention ! Konkoly Lászlóné/Traffic dimensioning and traffic measurements in IP networks