Pith. sign in

REVIEW 1 cited by

An Adaptive Dynamic Replacement Approach for a Multicast based Popularity Aware Prefix Cache Memory System

Not yet reviewed by Pith; the record is open.

This paper has not been read by Pith yet. Machine review is queued; the pith claim, tier, and objections will appear here once it completes.

SPECIMEN: schema-true, not a live event

T0 review · schema-true

One-sentence machine reading of the paper's core claim.

pith:XXXXXXXX · record.json · timestamp

arxiv 1001.4135 v1 pith:ZYS2ZXK6 submitted 2010-01-23 cs.MM

classification cs.MM
keywords cacheprefixreplacementadaptivealgorithmdynamicapproachmemory
verification ladder T0 review T1 audit T2 compute T3 formal
0 comments
read the original abstract

In this paper we have proposed an adaptive dynamic cache replacement algorithm for a multimedia servers cache system. The goal is to achieve an effective utilization of the cache memory which stores the prefix of popular videos. A replacement policy is usually evaluated using hit ratio, the frequency with which any video is requested. Usually discarding the least recently used page is the policy of choice in cache management. The adaptive dynamic replacement approach for prefix cache is a self tuning, low overhead algorithm that responds online to changing access patterns. It constantly balances between lru and lfu to improve combined result. It automatically adapts to evolving workloads. Since in our algorithm we have considered a prefix caching with multicast transmission of popular objects it utilizes the hard disk and network bandwidth efficiently and increases the number of requests being served.

Discussion (0). Continue with ORCID to comment.

Forward citations

Cited by 1 Pith paper

Reviewed papers in the Pith corpus that reference this work. Sorted by Pith novelty score. Full citation record

  1. Brame: Hierarchical Data Management Framework for Cloud-Edge-Device Collaboration

    cs.DB 2025-02 conditional novelty 4.0 of 10

    Brame groups relational tuples into workload-aware blocks and schedules block placement across cloud, edge, and terminal tiers, reporting improved query hit rates over data-aware baselines on two datasets.

Pith tools