Locality Aware Mechanisms for Large-scale Networks: The Tapestry - - PowerPoint PPT Presentation

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Locality Aware Mechanisms for Large-scale Networks: The Tapestry - - PowerPoint PPT Presentation

Locality Aware Mechanisms for Large-scale Networks: The Tapestry Infrastructure John D. Kubiatowicz UC Berkeley Global Scale Applications Clear demand for global scale applications Exploiting collective resources File sharing, data


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Locality Aware Mechanisms for Large-scale Networks: The Tapestry Infrastructure

John D. Kubiatowicz

UC Berkeley

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John Kubiatowicz Tahoe Retreat 06/02

Global Scale Applications

Clear demand for global scale applications

– Exploiting collective resources – File sharing, data dissemination, shared computation

Wide-area issues

– Scalability, fault-handling, adaptability, manageability

Decentralized Object Location and Routing (DOLR)

– Provides scalable message routing to objects

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John Kubiatowicz Tahoe Retreat 06/02

Utility-based Storage: OceanStore

Pac Bell

Sprint

IBM

AT&T

Canadian OceanStore

IBM

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Locality, Locality, Locality

“The ability to exploit local resources over remote

  • nes whenever possible”

“-Centric” approach

– Client-centric, server-centric, data source-centric

Requirements:

– Find data quickly, wherever it might reside

Locate nearby object without global communication Permit rapid object migration

– Verifiable: can’t be sidetracked

Data name cryptographically related to data

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4 2 3 3 3 2 2 1 2 4 1 2 3 3 1 3 4 1 1 4 3 2 4 NodeID 0xEF34 NodeID 0xEF31 NodeID 0xEFBA NodeID 0x0921 NodeID 0xE932 NodeID 0xEF37 NodeID 0xE324 NodeID 0xEF97 NodeID 0xEF32 NodeID 0xFF37 NodeID 0xE555 NodeID 0xE530 NodeID 0xEF44 NodeID 0x0999 NodeID 0x099F NodeID 0xE399 NodeID 0xEF40 NodeID 0xEF34

Basic Tapestry Mesh

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Randomization and Locality

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Parallel Insert Algorithms (SPAA ’02)

Massive parallel insert is important

– We now have algorithms that handle “arbitrary

simultaneous inserts”

– Construction of nearest-neighbor mesh links

Log2 n message complexity⇒fully operational routing mesh

– Objects kept available during this process

Incremental movement of pointers

Interesting Issue: Introduction service

– How does a new node find a gateway into the

Tapestry?

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Highly Dynamic Systems

Instability is the common case….!

– Small half-life for P2P apps (1 hour????) – Congestion, flash crowds, misconfiguration, faults

BGP convergence 3-30 mins!

– Mobile clients in semi-connected mode

Must Use Overlay under instability! Must be somehow:

– Insensitive to faults and denial of service attacks

Route around bad servers and ignore bad data

– Repairable infrastructure

Easy to reconstruct routing and location information

– Without care, worst case: sub-optimal paths, network

partitions, broken invariants ⇒ loss of availability

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Continuous Self-Repair

All state is Soft State

– Continuous probing, selection of neighbors – Periodic restoration of state

Stability through statistics:

– Redundancy at many levels: – Neighbor links, Object Roots, etc.

Dynamic Stabilization:

– Integrate/remove themselves automatically – Pointer state routed around faulty node

Markov Models:

– What is a misbehaving router? Communication link? – What level of redundancy necessary? – Are we under attack?

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State Maintenance

Maintenance of link conditions, routing state Example: soft-state beacons measure link

conditions between neighbors (Tapestry, Scribe)

Locality awareness

– Naïve: messages sent across overlay hops at same

rate regardless of actual network distance

– Traffic can scale with length of overlay hop, possibly

causing congestion

Alternatives:

– Scale soft-state frequency w/ length of overlay hop – External fault-detection / measurement platform

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Locality-Based Heartbeats

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Redundant Routing

Keep multiple routes for every link

– Pre-compute alternatives – Quick adaptation (using up pre-computing)

Destination-rooted spanning tree

– For each node N, reachable by all other nodes – All paths union to form spanning tree rooted at N

Convergence

– # of candidates for the next hop decreases by b every

hop, where b = base of Tapestry ID

– Nodes routing to same ID converge as a function of

the network density between them

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Convergence

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First Reachable Link Selection (FRLS)

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FRLS Reachability

FRLS Packet Delivery Rate vs. Link Failure

0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1 0.02 0.04 0.06 0.08 0.1 0.12 0.14 0.16 0.18 0.2

Fraction of Failed Links Packet Delivery Rate

E: No route connecting endpoints D: Route exists, FRLS = no, IP = no C: FRLS=yes, IP=no B: FRLS=no, IP=yes A: FRLS = yes, IP = yes

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Proactive Multicast

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Self-Organizing Soft-State Replication

Simple algorithms for placing replicas on nodes in

the interior

– Intuition: locality properties

  • f Tapestry help select positions

for replicas

– Tapestry helps associate

parents and children to build multicast tree

Preliminary results

show that this is effective

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The Living Network Model

Gaia: a living network

– James Lovelock [1979]

Large scale self-management

– Locally constrained interactions scalability,

performance

– Layered control structure – Upward propagation of aggregate data

Survival via active redundancy & self-repair

– Catastrophic failures handled by top level control

(human interaction)

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Conclusion

Decentralized Object Location and Routing (DOLR)

– Important to be able to route to objects

… With Locality

– Use of local resources whenever possible!

Continuous adaptation, repair

– System never quite fully stable – Continuous convergence – Keep objects as available as possible