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 measurement Discussion

Why Measure? The Internet is a man-made system, so why do we need to measure it? –Because we still don’t really understand it –Because sometimes things go wrong Measurement for network operations –Detecting and diagnosing problems –What-if analysis of future changes Measurement for scientific 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 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 wrong, 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 –Topology, 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 –Routing-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, tunnels, 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 measurement –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 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 destination TTL=1 Time exceeded TTL=2 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 don’t reply Inaccurate delay information –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 –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 delay 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., [15/Oct/1998:00:00: ] "GET /images/wwwtlogo.gif HTTP/1.0" " "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 Polling –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 Host A Host B Monitor Shared media (Ethernet, wireless) Router ARouter B Monitor Splitting a point-to-point link Router A Line card that does packet sampling Host A Host B Host C Monitor SwitchSwitch Multicast switch

Packet Monitoring: Selecting the 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 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: eth0 > > lovelace.acm.org.www: S : (0) win (DF) timestamp client address and port # Web server (port 80) SYN flag 23:40: eth : S : (0) ack win :40: eth0 > > lovelace.acm.org.www:. 1:1(0) ack 1 win (DF) 23:40: eth0 > > lovelace.acm.org.www: P 1:513(512) ack 1 win (DF) 23:40: eth :. 1:1(0) ack 513 win :40: eth0 > > lovelace.acm.org.www: P 513:676(163) ack 1 win (DF) 23:40: eth : P 1:179(178) ack 676 win 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 control –Number of bytes and packets per session Application header –URLs, HTTP headers (e.g., cacheable response?) –DNS queries and responses, user key strokes, …

flow 1flow 2flow 3 flow 4 Aggregating Packets into IP Flows Set of packets that “belong together” –Source/destination IP addresses and port numbers –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 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 link –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 contents)

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 products –Technology not designed with measurement in mind The “do no harm” principle –Don’t degrade router performance –Don’t require disabling key router features –Don’t overload the network with measurement data

Network Operations Tasks Reporting of network-wide statistics –Generating basic information about 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 install 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, etc.) –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)

Troubleshooting 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 customer 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-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 offending 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 Requirements –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? Where? 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 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 –Data catalogue maintained by CAIDA – Interdomain routing –RouteViews and RIPE-NCC –BGP routing tables and update messages Traceroute and looking glass servers – –

Discussion How important is accuracy of the data? How can we 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?