Scalability & Stability of the Internet Infrastructure Farnam Jahanian Department of EECS University of Michigan

Context Network Infrastructure Network Attacks S/H Failures Operational Faults Windmill Probes Netflow Statistics Protocol Scrubbers Event Aggregation Data Mining Replication schemes Active Response Capabilities Analysis Engines RoutersName Servers Critical Services Anomalous Network Events Coarse and Fine Grained Measurement Tools Countermeasures LIGHTHOUSE: Survivable Network Infrastructure Joint projects between U. Michigan & Merit Network

Motivation Increasing reliance of financial and national utility infrastructures on interconnected IP-based networks Explosive growth in both size and topological complexity of the underlying communication infrastructure Reliance on off-the-self infrastructure & shrink-wrapped code Network infrastructure is vulnerable: –inherent instability and transient oscillations –delayed convergence and long failover –coordinated denial of service attacks on network resources –hardware and software failures –operational faults and misconfigurations

Joint effort between University of Michigan and Merit Network Study Scalability and Stability of the Internet Infrastructure

Overview Measurement and Probe Software Data Dissemination Service Visualization and Data Mining Tools Tools for measurement & analysis of network perf. and stability: Current Internet Architecture: Decentralization of the Backbone Regional networks, national ISPs Trend toward private peering Increasing complexity and heterogeneity

Imminent Collapse of the Internet Collapse of the Internet Now ?

Internet Growth Explosive growth in both size and topological complexity Internet end-system growth Traffic volume & characteristics Infrastructure topological evolution

Internet End-System Growth

Growth of the Web Dramatic increase in the number of users, number of web sites, amount of content available, Web traffic. Source: IDC, 1998.

Exponential Traffic Growth Traffic Breakdown Source: Merit Network, Inc

Infrastructure Topological Evolution Between : Decentralization: from a single backbone network to a conglomeration of 100s of backbone and 1000s ISP. Loss of hierarchy and abstraction: from strict hierarchical network to increasingly a full-mesh interconnection. Significant bandwidth increase: from signle T3 (45MB) circuit and T1 (1MB) links to multiple OC48 (1.2GB) circuits and OC12 (622MB) lines between nodes.

Internet Evolution: NSFNet NSFNet Backbone Regional Campus Hello/EGP Hierarchical network with a single central backbone

Internet Evolution: Today AS1 AS2 AS3 AS4 C4 C2 C3 C1 Full-mesh interconnection of ISP backbones and customers

Impact of Instability & Failures –Increased end-to-end Loss/Latency –Increased delay in convergence & network reachability –Backbone infrastructure CPU/Memory requirements –Backbone “route flap storms” –Network management complexity

Background: Internet Architecture BGP

Background: Internet Routing Two major categories –Inter-domain (BGP between autonomous systems) –Intra-domain (OSPF, ISIS, IGRP inside an AS) BGP –Incremental: announcements and withdraws –Updates include policy (e.g. MED, ASPath) –Maintain multiple possible routes

Background: BGP Routing Protocol BGP is an incremental protocol that sends update information only upon changes in network topology or routing policy. Two forms of messages:  announcements:  New network accessible  Prefer another route to network destination  withdrawals:  Destination network is no longer accessible Routing policies vs. shortest number of hops

MCI Sprint Border Gateway Protocol (BGP) Inter-domain protocol between Autonomous Systems Routing peers exchange reachability information incrementally BGP uses TCP as the transport protocol between peer routers

Background: Internet Core Networks aggregated into CIDR (Classless Inter-Domain Routing) prefixes Prefix represents a set of destination IP addresses At Internet “core” all routers maintain paths to “default- free” routes Originally 5 major Internet Exchange Points (IXPs) In 1996, approximately 30,000 default-free routes

Roadmap Study of stability of routing in the Internet backbone –Transient oscillations, pathological redundant updates –congestion collapse and correlation to network usage –SIGCOMM’97 and INFOCOMM’99 Study of route availability and failover rates –long-term availability of Internet backbone routes –Case study of regional provider –FTCS’99 Study of convergence behavior of routing protocols –Injection of route changes into the Internet backbone –Impact of convergence delay on end-to-end path –18-month study & ongoing

Internet Exchange Points Deployed probes machines at five public exchange points Collected all routing updates at IXPs over four year period

Internet Routing Instability Results Number of BGP routing updates exchanged per day in the Internet core is orders of magnitude larger than expected. Most routing information is dominated by pathological, or redundant updates, which do not directly reflect changes in routing policy or topology. Instability and redundant updates exhibit a specific periodicity of 30 and 60 seconds. Instability and redundant updates show a surprising correlation to network usage and exhibit corresponding daily and weekly cyclic trends.

Instability Results (Continued) Instability is not dominated by a small set of autonomous systems or routes. Instability is not disproportionately dominated by prefixes of specific lengths, i.e. independent of aggregation. Discounting policy fluctuation and pathological behavior, there remains a significant level of Internet forwarding instability. Details: SIGCOMM’97 & INFOCOMM’99

Taxonomy WADiff (forwarding change) AADiff (policy or forwarding change) AADup (pathology) WWDup (pathology) WADup (failure)

Growth in Routing State Linear growth in routing table

Growth in Routing State Linear growth in routing table & autonomous systems Significant instability and pathological behavior

Initial Findings (SIGCOMM’97) Up to 60 million BGP updates/day for only 30,000 default-free routes! –On avg. 2-6 Million withdraws per day (mostly duplicates) –e.g., ISP A had 259 routes but withdrew 2.4 million routes All state changes well distributed across prefix lengths, autonomous systems Unexpected frequency components –30 second inter-arrival time between updates –Daily/weekly components

More Initial Observations Most routing updates pathological (millions!) –Some due to misconfiguration Private networks Host routes Multicast routes –Majority duplicate updates Duplicate withdraws (WWDup > 99.99%) Duplicate announcements (AADup)

BGP Updates

30 Second Frequency Components 1997

Origins of Pathological Updates (INFOCOM99) Majority stem from two router software implementation issues: –stateless BGP withdraws –non-transitive attribute filtering Frequency due to non-jittered router timers –lack of precise specification Others sources of pathologies: –BGP/IBGP misconfiguration –Still others DSU/CSU oscillation –And still others due distance-vector algorithm

After Initial Publication of Results One popular vendor validated our conjectures and released updated software in 1997 –Software rapidly deployed by ISPs –Stateful BGP reduced updates by orders of magnitude –Addition of random intervals to timers diminished frequency components

BGP Announcements and Withdraws NANOG presentationISP Geeks ReleaseMainline Release

Frequency Components

BGP Failures -- Congestion Collapse (BGP Frequency)

A Short Story Sigcomm '97 findings were puzzling: Bandwidth Utilization  Instability Hypothesis: Congestion causes underlying TCP to backoff BGP-level timers expire, causing termination

MCI Sprint Border Gateway Protocol (BGP) Interdomain protocol between Autonomous Systems Routing peers exchange reachability information incrementally BGP uses TCP as the transport protocol between peer routers

BGP Congestion Collapse Hypothesis Congestion causes underlying TCP to backoff BGP-level timers expire, causing termination Interaction between BGP and TCP leads to router congestion collapse High bandwidth utilization  BGP Instability Validated using Windmill tool (SIGCOMM98)

What about Failures? Some state changes due to policy changes & network failures Cannot distinguish between policy, intra-domain and inter- domain failures Methodology: –Measure long-term rate of failure for Internet backbone routes –Case study of regional provider

Internet Infrastructure Failures (FTCS99) Internet significantly less reliable and available than PSTN telephone network. After a network becomes unreachable, in most cases, it takes longer than 5 mins before it is reachable again. Even for transient oscillations, convergence of backbone routing states may be in the order of mins! Route failover (re-routing of traffic to a given network) occurs on average of once every three days or more. A small fraction of network paths contribute disproportionately to number of long-term outages

Definitions Route Failure: Prefix destination unavailable for 30 or more minutes Route Repair: A failed route becomes available Route Failover: A route replaced with one associated with a different path

Organizational Diameter of Internet Number of administrative domains between two networks Rapid regional commercialization of the Internet during 1997

Route Failures: How long before a network is unreachable?

Route Repairs: How long before a network is reachable again?

Failover: How long before traffic is re-routed?

Source of Failures Inside a Regional ISP Michnet Backbone Failures 11/ /98

Conventional Wisdom on Convergence Internet is highly redundant –Just reroute around in a few milliseconds Routing protocol convergence takes only a few ???? “Bad news travels fast” –Fast withdraw propagation valid goal –Announcements slower because bundled BGP has great convergence properties –Path vector solved the convergence and counting to infinity (looping) problems All my customers are multi-homed, triple-homed –Convergence -- what, me worry? Not True!

18-Month Study of Convergence Behavior Instrument the Internet –Inject routes into geographically and topologically diverse provider BGP peering sessions (Japan, Michigan, US Exchange Points, Canada, UK) –Periodically fail and change these routes (i.e. send withdraws or new attributes) –Time events using ICMP ping and NTP synchronized BGP “routeviews” monitoring machines –Wait 18 months… (50,000 routing events)

Passive & Active Measurement Infrastructure

Internet ISP4 Stub AS RouteViews Data Collection Probe ISP5 ISP6 ISP3 Upstream ISP1 Stub AS Fault Injection Server Upstream ISP2 BGP Fault BGP ICMP Echos Passive & Active Measurement Infrastructure

Terminology Tdown: A previously available route is withdrawn. This is a route failure. Tup: previously unavailable route is announced as available. This is a route repair. Tshort: A route is replaced with another route having a shorter path. This is a route failover. Tlong: A route is replaced by another route with a longer path. This is a route failover.

Avg. number of messages generated by each ISP following a routing update event Tdown and Tlong generated more messages than Tup and Tshort Significant variation among ISPs within each category of message

Withdraw Convergence (Tdown) After a BGP route is withdrawn, barring other failures, how long does it take Internet routing tables to reach steady-state?

Convergence delay after a Tdown Withdraw Convergence

Different providers exhibit different behavior 70% of withdraws from most ISPs take more than a minute For ISP in Canada, 20% withdraws took more than three minutes to converge Observed latencies of up to 10 mins for certain events No correlation between convergence latency and geography or topological (except for MichNet)

Failovers and Repairs What are the relative convergence latencies for failovers and repairs? Does bad news (withdraws) travel faster?

Failures, Failovers and Repairs Bad News Does Not Travel Fast!

Failures, Failovers and Repairs Bad News Does Not Travel Fast!

Failures, Failovers and Repairs Bad news does not travel fast… Repairs (Tup) exhibit similar convergence properties as long  short path failover Failures (Tdown) and short  long failovers also similar –Slower than Tup (e.g. a repair) –60% take longer than two minutes –Failover times degrade the greater the degree of multi- homing!

End2End Connectivity Impact of delayed convergence on E2E connectivity? After a failover, how long before my site is reachable? –Modified ICMP pings sent once a second –Source IP address block of pseudo-AS –100 randomly chosen web sites from cache logs

Impact of Convergence Delay on End-to-End Path Avg. packet loss to 100 web sites (1 min bins in the ten mins preceding and following a routing update)

What is Happening? Non-deterministic ordering of BGP update messages leads to –Transient oscillations –Each change in FIB adds delay (CPU, BGP bundling timer) –At extreme, convergence triggers BGP dampening

BGP Bad News Given best current routing practices, inter-domain BGP convergence times degrade exponentially with increase in the degree of interconnectivity for a given route … and the degree of inter-connectivity (multi-homing, transit, etc) is increasing

Internet vs. Telephone Network Packet-switched vs. circuit-switched No explicit reservation on the Internet Fault-tolerant switches in telephone networks Significantly shorter development, testing and deployment cycle in the Internet world Reliability vs. time-to-market Relative degree of operational experience Small number of telecommunication companies vs. a conglomeration of thousands of ISPs

The Next Challenge Jeopardizing the Explosive Growth of the Web is AVAILABILITY. Growing reliance on the Internet for commerce, healthcare, education,... Challenges Facing Today’s Internet are Bandwidth and Latency

Context Network Infrastructure Network Attacks S/H Failures Operational Faults Windmill Probes Netflow Statistics Protocol Scrubbers Event Aggregation Data Mining Replication schemes Active Response Capabilities Analysis Engines RoutersName Servers Critical Services Anomalous Network Events Coarse and Fine Grained Measurement Tools Countermeasures LIGHTHOUSE: Survivable Network Infrastructure Sponsors: NSF, DARPA and INTEL

Acknowledgements Michigan Students & Merit Staff: Abha Ahuja, Mukesh Agrawal, Paul Howell, Craig Labovitz, Rob Malan, Matt Smart, David Watson Sponsors: National Science Foundation, DARPA, Intel, IBM, HP