Comparing Locality of Reference - Some Folk Theorems for the Miss Rates and the Output of Caches

Abstract

The performance of demand-driven caching is known to depend on the locality of reference exhibited by the stream of requests made to the cache. In spite of numerous efforts, no consensus has been reached on how to formalize this notion, let alone on how to compare streams of requests on the basis of their locality of reference. The authors take on this issue with an eye towards validating operational expectations associated with the notion of locality of reference. They focus on two "folk theorems," namely (1) the stronger locality of reference, the smaller the miss rate of the cache; and (2) good caching is expected to produce an output stream of requests exhibiting less locality of reference than the input stream of requests. The authors discuss these two folk theorems in the context of a cache operating under a demand-driven replacement policy when document requests are modeled according to the Independent Reference Model (IRM). As they propose to measure strength of locality of reference in a stream of requests through the skewness of its popularity distribution, they introduce the notion of majorization as a means for capturing this degree of skewness. They show that these folk theorems hold for caches operating under a large class of cache replacement policies, including the optimal policy and the random policy, but may fail under the Least Recently Used (LRU) policy.

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Document Details

Document Type
Technical Report
Publication Date
Jan 01, 2004
Accession Number
ADA444359

Entities

People

  • Armand M. Makowski
  • Sarut Vanichpun

Organizations

  • University of Maryland

Tags

Communities of Interest

  • C4I
  • Space

DTIC Thesaurus Topics

  • Algorithms
  • Computer Communications
  • Computer Science
  • Computers
  • Markov Chains
  • Monotone Functions
  • Naval Warfare
  • Networks
  • New York
  • Permutations
  • Probability
  • Sequences
  • Simulations
  • Statistics
  • Steady State
  • Test And Evaluation
  • Universities

Fields of Study

  • Computer science

Readers

  • Applied Combinatorial Optimization and Logic Circuit Design.
  • Educational Psychology
  • Statistical inference.