Internet Measurement.ppt

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1、Internet Measurement,Jennifer Rexford,Outline,Measurement overview Why measure? Why model measurements? What to measure? Where to measure? Internet challenges Measurement tools Active: ping, traceroute, and pathchar Passive: logs, SNMP, packet, and flow monitoring Operational applications of measure

2、ment Discussion,Why Measure?,The Internet is a man-made system, so why do we need to measure it? Because we still dont really understand it Because sometimes things go wrong Measurement for network operations Detecting and diagnosing problems What-if analysis of future changes Measurement for scient

3、ific discovery Characterizing a complex system as organism Creating accurate models that represent reality Identifying new features and phenomena,Why Build Models of Measurements?,Compact summary of measurements Efficient way to represent a large data set E.g., exponential distribution with mean 100

4、 sec Expose important properties of measurements Reveals underlying cause or engineering question E.g., mean RTT to help explain TCP throughout Generate random but realistic data as input Generate new data that agree in key properties E.g., topology models to feed into simulators,“All models are wro

5、ng, but some models are useful.” George Box,What Can be Measured?,Traffic Load statistics Packet or flow traces Performance of paths Application performance, e.g,. Web download time Transport performance, e.g., TCP bulk throughput Network performance, e.g., packet delay and loss Network structure To

6、pology, and paths on the topology Dynamics of the routing protocol,Where Measure?,Short answer Anywhere you can! End hosts Application logs, e.g., Web server logs Sending active probes to measure performance Individual links/routers Load statistics, packet traces, flow traces Configuration state Rou

7、ting-protocol messages or table dumps Alarms,Internet Challenges Make Measurement an Art,Stateless routers Routers do not routinely store packet/flow state Measurement is an afterthought, adds overhead IP narrow waist IP measurements cannot see below network layer E.g., link-layer retransmission, tu

8、nnels, etc. Violations of end-to-end argument E.g., firewalls, address translators, and proxies Not directly visible, and may block measurements Decentralized control Autonomous Systems may block measurements No global notion of time,Active Measurement: Ping,Adding traffic for purposes of measuremen

9、t Trade-offs between accuracy and overhead Need careful methods to avoid introducing bias Ping Host sends an ICMP ECHO packet to a target and captures the ICMP ECHO REPLY Useful for checking connectivity, and RTT Only requires control of one of the two end-points Problems with ping Round-trip rather

10、 than one-way delays Some hosts might not respond,Active Measurement: Traceroute,Time-To-Live field in IP packet header Source sends a packet with a TTL of n Each router along the path decrements the TTL “TTL exceeded” sent when TTL reaches 0 Traceroute tool exploits this TTL behavior,source,destina

11、tion,Send packets with TTL=1, 2, 3, and record source of “time exceeded” message,Active Measurement: Challenges of Traceroute,Measuring multiple paths Successive probes may traverse different paths Non-participating network elements Some routers and firewalls dont reply Inaccurate delay information

12、Includes processing delays on the router CPU Round-trip vs. one-way measurements Paths may have asymmetric properties Interfaces, not routers Returns IP address of interfaces, not routers,Active Measurement: Applications of Traceroute,Network troubleshooting Identify forwarding loops and black holes

13、 Identify long and convoluted paths See how far the probe packets get Network topology inference Launch traceroute probes from many places toward many destinations Join together to fill in parts of the topology though traceroute undersamples the edges,Active Measurement: Pathchar for Links,Three del

14、ay components:,How to infer d,c?,d,min. RTT (L),L,rtt(i+1) -rtt(i),slope=1/c,Passive Measurement: Logs at Hosts,Web server logs Host, time, URL, response code, content length, E.g., 122.345.131.2 - - 15/Oct/1998:00:00:25 -0400 “GET /images/wwwtlogo.gif HTTP/1.0“ 304 - “http:/www.aflcio.org/home.htm“

15、 “Mozilla/2.0 (compatible; MSIE 3.02; Update a; AK; AOL 4.0; Windows 95)“ “-“ DNS logs Request, response, time Useful for workload characterization, troubleshooting, etc.,Passive Measurement: SNMP,Simple Network Management Protocol Coarse-grained counters on the router E.g., byte and packet counts P

16、olling Management system can poll the counters E.g., once every five minutes Limitations Extremely coarse-grained statistics Delivered over UDP! Advantages: ubiquitous,Passive Measurement: Packet Monitoring,Tapping a link,Router A,Line card that does packet sampling,Packet Monitoring: Selecting the

17、Traffic,Filter to focus on a subset of the packets IP addresses/prefixes (e.g., to/from specific Web sites, client machines, DNS servers, mail servers) Protocol (e.g., TCP, UDP, or ICMP) Port numbers (e.g., HTTP, DNS, BGP, Napster) Collect first n bytes of packet (snap length) Medium access control

18、header (if present) IP header (typically 20 bytes) IP+UDP header (typically 28 bytes) IP+TCP header (typically 40 bytes) Application-layer message (entire packet),Tcpdump Output (three-way TCP handshake and HTTP request message),23:40:21.008043 eth0 135.207.38.125.1043 lovelace.acm.org.www: S 617756

19、405:617756405(0) win 32120 (DF),timestamp,client address and port #,Web server (port 80),SYN flag,23:40:21.036758 eth0 135.207.38.125.1043: S 2598794605:2598794605(0) ack 617756406 win 16384 23:40:21.036789 eth0 135.207.38.125.1043 lovelace.acm.org.www: . 1:1(0) ack 1 win 32120 (DF)23:40:21.037372 e

20、th0 135.207.38.125.1043 lovelace.acm.org.www: P 1:513(512) ack 1 win 32256 (DF) 23:40:21.085106 eth0 135.207.38.125.1043: . 1:1(0) ack 513 win 16384 23:40:21.085140 eth0 135.207.38.125.1043 lovelace.acm.org.www: P 513:676(163) ack 1 win 32256 (DF) 23:40:21.124835 eth0 135.207.38.125.1043: P 1:179(17

21、8) ack 676 win 16384,sequence number,TCP options,Analysis of Packet Traces,IP header Traffic volume by IP addresses or protocol Burstiness of the stream of packets Packet properties (e.g., sizes, out-of-order, etc.) TCP header Traffic breakdown by application (e.g., Web) TCP congestion and flow cont

22、rol Number of bytes and packets per session Application header URLs, HTTP headers (e.g., cacheable response?) DNS queries and responses, user key strokes, ,flow 1,flow 2,flow 3,flow 4,Aggregating Packets into IP Flows,Set of packets that “belong together” Source/destination IP addresses and port num

23、bers Same protocol, ToS bits, Same input/output interfaces at a router (if known) Packets that are “close” together in time Maximum spacing between packets (e.g., 15 sec, 30 sec) Example: flows 2 and 4 are different flows due to time,Packet vs. Flow Measurement,Basic statistics (available from both

24、techniques) Traffic mix by IP addresses, port numbers, and protocol Average packet size Traffic over time Both: traffic volumes on a medium-to-large time scale Packet: burstiness of the traffic on a small time scale Statistics per TCP connection Both: number of packets & bytes transferred over the l

25、ink Packet: frequency of lost or out-of-order packets, and the number of application-level bytes delivered Per-packet info (available only from packet traces) TCP seq/ack #s, receiver window, per-packet flags, Probability distribution of packet sizes Application-level header and body (full packet co

26、ntents),Measurement Challenges for Operators,Network-wide view Crucial for evaluating control actions Multiple kinds of data from multiple locations Large scale Large number of high-speed links and routers Large volume of measurement data Poor state-of-the-art Working within existing protocols and p

27、roducts Technology not designed with measurement in mind The “do no harm” principle Dont degrade router performance Dont require disabling key router features Dont overload the network with measurement data,Network Operations Tasks,Reporting of network-wide statistics Generating basic information ab

28、out usage and reliability Performance/reliability troubleshooting Detecting and diagnosing anomalous events Security Detecting, diagnosing, and blocking security problems Traffic engineering Adjusting network configuration to the prevailing traffic Capacity planning Deciding where and when to instal

29、l new equipment,Basic Reporting,Producing basic statistics about the network For business purposes, network planning, ad hoc studies Examples Proportion of transit vs. customer-customer traffic Total volume of traffic sent to/from each private peer Mixture of traffic by application (Web, Napster, et

30、c.) Mixture of traffic to/from individual customers Usage, loss, and reliability trends for each link Requirements Network-wide view of basic traffic and reliability statistics Ability to “slice and dice” measurements in different ways (e.g., by application, by customer, by peer, by link type),Troub

31、leshooting,Detecting and diagnosing problems Recognizing and explaining anomalous events Examples Why a backbone link is suddenly overloaded Why the route to a destination prefix is flapping Why DNS queries are failing with high probability Why a route processor has high CPU utilization Why a custom

32、er cannot reach certain Web sites Requirements Network-wide view of many protocols and systems Diverse measurements at different protocol levels Thresholds for isolating significant phenomena,Security,Detecting and diagnosing problems Recognizing suspicious traffic or disruptions Examples Denial-of-

33、service attack on a customer or service Spread of a worm or virus through the network Route hijack of an address block by adversary Requirements Detailed measurements from multiple places Including deep-packet inspection, in some cases Online analysis of the data Installing filters to block the offe

34、nding traffic,Traffic Engineering,Adjusting resource allocation policies Path selection, buffer management, and link scheduling Examples OSPF weights to divert traffic from congested links BGP policies to balance load on peering links Link-scheduling weights to reduce delay for “gold” traffic Requir

35、ements Network-wide view of the traffic carried in the backbone Timely view of the network topology and configuration Accurate models to predict impact of control operations (e.g., the impact of RED parameters on TCP throughput),Capacity Planning,Deciding whether to buy/install new equipment What? W

36、here? When? Examples Where to put the next backbone router When to upgrade a link to higher capacity Whether to add/remove a particular peer Whether the network can accommodate a new customer Whether to install a caching proxy for cable modems Requirements Projections of future traffic patterns from

37、 measurements Cost estimates for buying/deploying the new equipment Model of the potential impact of the change (e.g., latency reduction and bandwidth savings from a caching proxy),Examples of Public Data Sets,Network-wide data Abilene and GEANT backbones Netflow, IGP, and BGP traces CAIDA DatCat Da

38、ta catalogue maintained by CAIDA http:/imdc.datcat.org/ Interdomain routing RouteViews and RIPE-NCC BGP routing tables and update messages Traceroute and looking glass servers http:/www.traceroute.org/ http:/www.nanog.org/lookingglass.html,Discussion,How important is accuracy of the data? How can we

39、 validate measurement studies? (If we know the answer already, why are we measuring?) How to do controlled experiments with measurement techniques? Can we move measurement to a science rather than an art? Can we identify incentives for making measurement possible and data available? Distributed analysis of measurement data? An architecture for router or line-card support for traffic and performance measurement? Trade-offs between security and privacy?,