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Improving Internet Availability with Path Splicing Nick Feamster Georgia Tech Joint work with Murtaza Motiwala and Santosh Vempala.

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Presentation on theme: "Improving Internet Availability with Path Splicing Nick Feamster Georgia Tech Joint work with Murtaza Motiwala and Santosh Vempala."— Presentation transcript:

1 Improving Internet Availability with Path Splicing Nick Feamster Georgia Tech Joint work with Murtaza Motiwala and Santosh Vempala

2 2 It is not difficult to create a list of desired characteristics for a new Internet. Deciding how to design and deploy a network that achieves these goals is much harder. Over time, our list will evolve. It should be: 1. Robust and available. The network should be as robust, fault-tolerant and available as the wire-line telephone network is today. It is not difficult to create a list of desired characteristics for a new Internet. Deciding how to design and deploy a network that achieves these goals is much harder. Over time, our list will evolve. It should be: 1.Robust and available. The network should be as robust, fault-tolerant and available as the wire-line telephone network is today. 2.… Can the Internet be Always On? Various studies (Paxson, etc.) show the Internet is at about 2.5 nines More critical (or at least availability- centric) applications on the Internet At the same time, the Internet is getting more difficult to debug –Scale, complexity, disconnection, etc.

3 3 Availability of Other Services Carrier Airlines (2002 FAA Fact Book) –41 accidents, 6.7M departures –99.9993% availability 911 Phone service (1993 NRIC report +) –29 minutes per year per line –99.994% availability Std. Phone service (various sources) –53+ minutes per line per year –99.99+% availability

4 4 Threats to Availability Natural disasters Physical failures (node, link) Implementation bugs Misconfiguration Mis-coordination Denial-of-service (DoS) attacks Changes in traffic patterns (e.g., flash crowd) …

5 5 Availability: Two Aspects Reliability: Connectivity in the routing tables should approach the that of the underlying graph –If two nodes s and t remain connected in the underlying graph, there is some sequence of hops in the routing tables that will result in traffic Recovery: In case of failure (i.e., link or node removal), nodes should quickly be able to discover a new path

6 6 Multipath: Promise and Problems Bad: If any link fails on both paths, s is disconnected from t Want: End systems remain connected unless the underlying graph has a cut ts

7 7 Path Splicing: Main Idea Step 1 (Perturbations): Run multiple instances of the routing protocol, each with slightly perturbed versions of the configuration Step 2 (Slicing): Allow traffic to switch between instances at any node in the protocol t s Compute multiple forwarding trees per destination. Allow packets to switch slices midstream.

8 8 Generating Slices Goal: Each instance provides different paths Mechanism: Each edge is given a weight that is a slightly perturbed version of the original weight –Two schemes: Uniform and degree-based ts 3 3 3 Base Graph ts 3.5 4 5 1.5 1.25 Perturbed Graph

9 9 Constructing Paths Goal: Allow multiple instances to co-exist Mechanism: Virtual forwarding tables a t c s b t a t c Slice 1 Slice 2 dstnext-hop

10 10 Forwarding Traffic Packet has shim header with forwarding bits Routers use lg(k) bits to index forwarding tables –Shift bits after inspection To access different (or multiple) paths, end systems simply change the forwarding bits –Incremental deployment is trivial –Persistent loops cannot occur Various optimizations are possible

11 11 Evaluation Defining reliability Does path splicing improve reliability? –How close can splicing get to the best possible reliability (i.e., that of the underlying graph)? Can path splicing enable fast recovery? –Can end systems (or intermediate nodes) find alternate paths fast enough?

12 12 Defining Reliability Reliability: the probability that, upon failing each edge with probability p, the graph remains connected Reliability curve: the fraction of source- destination pairs that remain connected for various link failure probabilities p The underlying graph has an underlying reliability (and reliability curve) –Goal: Reliability of routing system should approach that of the underlying graph.

13 13 Reliability Curve: Illustration Probability of link failure (p) Fraction of source-dest pairs disconnected Better reliability More edges available to end systems -> Better reliability

14 14 Reliability Approaches Optimal Sprint (Rocketfuel) topology 1,000 trials p indicates probability edge was removed from base graph Reliability approaches optimal Average stretch is only 1.3 Sprint topology, degree-based perturbations

15 15 Recovery: Two Mechanisms End-system recovery –Switch slices at every hop with probability 0.5 Network-based recovery –Router switches to a random slice if next hop is unreachable –Continue for a fixed number of hops till destination is reached 15

16 16 Simple Recovery Strategies Work Well Which paths can be recovered within 5 trials? –Sequential trials: 5 round-trip times –…but trials could also be made in parallel Recovery approaches maximum possible Adding a few more slices improves recovery beyond best possible reliability with fewer slices.

17 17 Splicing Improves Availability Reliability: Connectivity in the routing tables should approach the that of the underlying graph –Approach: Overlay trees generated using random link-weight perturbations. Allow traffic to switch between them –Result: Splicing ~ 10 trees achieves near-optimal reliability Recovery: In case of failure, nodes should quickly be able to discover a new path –Approach: End nodes randomly select new bits –Result: Recovery within 5 trials approaches best possible

18 18 Open Questions How does splicing interact with traffic engineering? Sources controlling traffic? What are the best mechanisms for generating slices and recovering paths? Can splicing eliminate dynamic routing?

19 19 Conclusion Simple: Forwarding bits provide access to different paths through the network Scalable: Exponential increase in available paths, linear increase in state Stable: Fast recovery does not require fast routing protocols http://www.cc.gatech.edu/~feamster/papers/splicing-hotnets.pdf

20 20

21 21 How to Perturb the Link Weights? Uniform: Perturbation is a function of the initial weight of the link Degree-based: Perturbation is a linear function of the degrees of the incident nodes –Intuition: Deflect traffic away from nodes where traffic might tend to pass through by default

22 22 Putting It Together End system sets forwarding bits in packet header Forwarding bits specify slice to be used at any hop Router: examines/shifts forwarding bits, and forwards t s

23 23 What About Loops? Persistent loops are avoidable –In the simple scheme, path bits are exhausted from the header –Never switching back to the same Transient loops can still be a problem because they increase end-to-end delay (stretch) –Longer end-to-end paths –Wasted capacity

24 24 Significant Novelty for Modest Stretch Novelty: difference in nodes in a perturbed shortest path from the original shortest path Example s d Novelty: 1 – (1/3) = 2/3 Fraction of edges on short path shared with long path

25 25 Extension: Interdomain Paths Observation: Many routers already learn multiple alternate routes to each destination. Idea: Use the forwarding bits to index into these alternate routes at an ASs ingress and egress routers. Storing multiple entries per prefix Indexing into them based on packet headers Selecting the best k routes for each destination Required new functionality d default alternate Splice paths at ingress and egress routers


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