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Non-Sticky Fingers: Policy-Driven Self-optimization for DHTs

  • Matti Siekkinen
  • Vera Goebel
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 5918)

Abstract

It is a common situation with distributed hash tables (DHT) that insertions and lookups frequently target only specific fractions of the entire value range. We present in this paper a self-optimization scheme for DHTs that optimizes the routing behavior in such situations. In our scheme, called Non-Sticky (NS) fingers, each node continuously measures the routing behavior and guides neighboring nodes to adjust their NS fingers (a subset of all the long distance links that the node establishes) accordingly in order to shortcut the most popular sections of routes. Our scheme enables self-optimization, which means that it adapts to the current system state and only operates when advantageous. It is also policy-driven, which means that the application can specify its policy on the tradeoff between performance and cost efficiency. We implemented the NS-fingers scheme for an existing order-preserving DHT and report the evaluation results. Our simulation results show that in a realistic application scenario, NS-fingers can halve the number of routing hops.

Keywords

Video Streaming Range Query Distribute Hash Table Service Demand Distance Link 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© IFIP International Federation for Information Processing 2009

Authors and Affiliations

  • Matti Siekkinen
    • 1
    • 2
  • Vera Goebel
    • 2
  1. 1.Dept. of Computer Science and EngineeringHelsinki University of TechnologyFinland
  2. 2.Dept. of InformaticsUniversity of OsloBlindernNorway

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