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dc.contributor.author
AlSabbagh, Abdullah
el
dc.date.accessioned
2018-03-30T08:18:00Z
dc.date.available
2018-03-31T00:00:23Z
dc.date.issued
2018-03-30
dc.identifier.uri
https://repository.ihu.edu.gr//xmlui/handle/11544/29001
dc.rights
Default License
dc.title
Caching at the radio access network edge for 5G networks
en
heal.type
masterThesis
en_US
heal.creatorID.dhareID
Alsabbagh
heal.classification
Telecomunications
en
heal.keywordURI.LCSH
Wireless communication systems
heal.keywordURI.LCSH
Mobile communication systems
heal.keywordURI.LCSH
Mobile computing
heal.keywordURI.LCSH
Software engineering
heal.keywordURI.LCSH
Transmission network
heal.language
en
en_US
heal.access
free
en_US
heal.license
http://creativecommons.org/licenses/by-nc/4.0
en_US
heal.recordProvider
School of Science and Technology, MSc in Information & Communication Technology Systems
en_US
heal.publicationDate
2018-03-30
heal.abstract
This dissertation was written as a part of the MSc in ICT Systems at the International Hellenic University. Caching at the network edge is a recently proposed technique for the upcoming mobile generation 5G, to reduce the backhaul rates at the peak hours by prefetching popular contents and store them into memories at or near to the end users. However, we focus on a new revolutionary caching scheme named as coded caching that take advantage of the multicast medium of the mobile network to offer a considerable gain through information theory coding techniques. In this work, we analyze the performance of two dominant approaches. A comparative simulation-based study has been established of uncoded and coded caching under various levels of spatial locality of the user contents. Our simulation results show that LFU (Least frequently used) uncoded caching scheme provides a better performance than coded caching schemes for real-life scenarios which were represented in our simulation as non-uniform content popularity. In addition, coded caching scheme still needs additional improvements regarding the supported number of users as well as the computational complexity imposed on users and server sides.
en
heal.tableOfContents
Table of Figures v Acknowledgments vii Chapter 1 Introduction 1 1.1 Motivation 1 1.2 State-of-the-art Work 2 1.2.1 Caching in General 2 1.2.2 Uncoded Femtocaching 4 1.2.3 Coded Caching 6 1.3 Objectives of the Dissertation 10 1.4 Outline of the Dissertation 11 Chapter 2 System Model and Methodology 12 2.1 System Model 12 2.1 Small cells, caches, and users 12 2.1.2 Caching Algorithms 13 2.1.2.1 Uncoded caching: Highest-Popularity First (HPF) 13 2.1.2.2. Coded caching: Decentralized Coded Caching algorithm for non-uniform demand distribution 14 2.2 Evaluation Methodology 15 2.2.1 Content Popularity 15 2.2.2 Performance metrics 17 2.2.2.1 Cache hit-ratio 17 2.2.2.2 Backhaul rate 17 Chapter 3 Evaluation 19 3.1 Uniform Content Popularity: HPF vs DCC vs CC 19 3.1.1 Impact of the cache size, M 19 3.1.2 The impact of the number of files, N 20 3.2 Non-Uniform Content Popularity: HPF vs DCC with file grouping 21 3.2.1 Impact of the Zipf skewness parameter θ 21 3.2.2 Impact of the cache capacity, M 25 Chapter 4 Conclusions and Discussion 38 4.1 Conclusion 38 4.2 Future work 40 Appendix A: MATLAB Code 40 REFERENCES 55
el
heal.advisorName
Karaliopoulos, Merkouris
el
heal.advisorID
Dr.
en_US
heal.committeeMemberName
Gatzianas, Marios
en
heal.academicPublisher
IHU
el
heal.academicPublisherID
ihu
en_US
heal.numberOfPages
63
en_US


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