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Intelligent Data Caching in the LTE Telecom Network.
KTH, School of Computer Science and Communication (CSC).
2012 (English)Independent thesis Advanced level (professional degree), 20 credits / 30 HE creditsStudent thesis
Abstract [en]

This degree project, conducted at Ericsson AB, investigates if an intelligent caching algorithm can achieve better cache hit ratio than a general replacement algorithm in the LTE telecom network environment. The intelligence refers to the use of network statistics available in the operating system. The project includes research on memory management systems, memory access patterns and caching algorithms.

A new algorithm, Three-Queue-Metric (3QM), is designed to conform to the characteristics of the access patterns demonstrated on different traffic scenarios. It is empirically shown that 3QM performs better than all other algorithms included in the study on a workload specific to the LTE network. It is therefore concluded that network statistics indeed can be part of a process to improve cache performance.

Abstract [sv]

Detta examensarbete, utfört på Ericsson AB, ämnar undersöka huruvida en intelligent cachingalgorithm kan förbättra cacheminnets prestanda i ett LTE-nätverk jämfört med en generell utbytesalgoritm. Intelligensen syftar till användning av nätverkstatistik som finns tillgängligt i operativsystemet tillhörande en basstation. Arbetet innefattar även en undersökning av minneshanteringssystem, minnesåtkomstmönster samt utbytesalgoritmer.

Studien leder till att en ny algoritm, kallad Three-Queue-Metric (3QM), designas med avseende att tillgodose alla accessmönster som uppvisats av de olika trafikscenarion och utvärderade algoritmer. Det fastslås empiriskt att 3QM påvisar bättre prestanda än någon av de andra implementerade algoritmerna på det specifika indata som motsvarar ett LTE-nätverk. Därför dras slutsatsen att nätverksstatistik kan användas för att förbättra cacheminnets prestanda.

Place, publisher, year, edition, pages
2012.
Series
Trita-CSC-E, ISSN 1653-5715 ; 2012:077
National Category
Computer Science
Identifiers
URN: urn:nbn:se:kth:diva-130971OAI: oai:DiVA.org:kth-130971DiVA: diva2:654417
Educational program
Master of Science in Engineering - Computer Science and Technology
Uppsok
Technology
Supervisors
Examiners
Available from: 2013-10-07 Created: 2013-10-07

Open Access in DiVA

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Other links

http://www.nada.kth.se/utbildning/grukth/exjobb/rapportlistor/2012/rapporter12/meier_elina_12077.pdf
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CiteExportLink to record
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  • apa
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