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Selfservice, with applications to distributed classifier construction

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Title: Selfservice, with applications to distributed classifier construction


1
Self-service, with applications to distributed
classifier construction
Michael K. Reiter and Asad Samar
Service Implementations
Our approach
  • The Self-Service approach
  • Clients perform their own operations
  • No resource increase required at server as
    clients increase
  • Algorithms guarantee strong consistency
    properties
  • Can recover from client failures, though at some
    cost
  • Centralized services
  • Provides strong consistency, but
  • Scales poorly
  • Cluster-based services
  • Can provide strong consistency, but
  • Requires adding resources to the cluster as
    number of clients increases
  • Clients are arranged in a tree rooted at server
  • Service state divided into small objects
  • Each client retrieves the objects required for
    its operation
  • And applies the operation locally
  • Self-service
  • Scales to a large client population (particularly
    compute scalability)
  • Does not require adding resources to the server
    as clients increase
  • Provides strong consistency guarantees
  • Can recover from client failures
  • but best suited for services where
  • Clients are trustworthy (ongoing work) and churn
    is low
  • Service state can be decomposed into small
    objects such that client operations typically
    involve only a few

Experiments
Properties Related Work
Algorithms
  • Nodes arrange themselves in a logical distributed
    queue
  • And take turns to apply their operations on the
    object
  • Implemented algorithms and traffic modeling
    application
  • Micro-benchmarks on PlanetLab
  • Model building experiments (CPU intensive) on
    local cluster
  • Compared with a centralized implementation of
    same service
  • Self-Service achieves three properties
  • Scalability
  • Single clusters are only incrementally scalable
  • Consistency
  • Most P2P systems do not achieve strong
    consistency properties
  • Multiple clusters (one per object) lack
    consistency for multi-object operations
  • Failure recovery
  • DHTs supporting atomic operations do not recover
    from failures
  • Self-Service recovers from failures but may lose
    recent operations

b has requested from a, c from b and d from c. e
now requests from d. a completes operation and
transfers to b.
  • If a node disconnects, any objects in its
    sub-tree are reconstituted from latest state seen
    at any connected node
  • Connected nodes continue to make progress even if
    a node in the distributed queue gets disconnected

April 27, 2006
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