User Preference Aware Lossless Data Compression at the Edge

Data compression is an efficient technique for saving data storage and transmission costs in networks. Traditional data compression methods usually compress each content item according to its own statistical distribution of symbols and do not take into account user preferences on various content ite...

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Veröffentlicht in:IEEE transactions on communications Jg. 68; H. 6; S. 3792 - 3807
Hauptverfasser: Lu, Yawei, Chen, Wei, Poor, H. Vincent
Format: Journal Article
Sprache:Englisch
Veröffentlicht: New York IEEE 01.06.2020
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Schlagworte:
Algorithms
codebook design
Codes
Coding
Computer simulation
Convex functions
Data compression
Data storage
Design
difference of convex functions
edge source coding
Image coding
Lossless data compression
Lossless equipment
Multicasting
Simulation
Source coding
Statistical distributions
Symbols
TCPIP
user preference
ISSN:0090-6778, 1558-0857
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Abstract Data compression is an efficient technique for saving data storage and transmission costs in networks. Traditional data compression methods usually compress each content item according to its own statistical distribution of symbols and do not take into account user preferences on various content items. However, user preferences significantly impact the statistical distributions of symbols transmitted over communication links. This paper presents an edge source coding method to compress data at the network edge, in which codebooks are designed based on not only the statistical distributions of symbols in the content items but also the user preferences. In edge source coding, multiple content items might be compressed via the same codebook. For discrete user preferences, DCA (difference of convex functions programming algorithm) based and <inline-formula> <tex-math notation="LaTeX">k </tex-math></inline-formula>-means++ based algorithms are proposed to derive codebook designs. For continuous user preferences, a sampling method is applied to yield codebook designs. In addition, edge source coding is extended to the two-user case and codebooks are designed to utilize multicasting opportunities. Simulation results demonstrate that edge source coding significantly reduces transmission costs for short content items.
AbstractList Data compression is an efficient technique for saving data storage and transmission costs in networks. Traditional data compression methods usually compress each content item according to its own statistical distribution of symbols and do not take into account user preferences on various content items. However, user preferences significantly impact the statistical distributions of symbols transmitted over communication links. This paper presents an edge source coding method to compress data at the network edge, in which codebooks are designed based on not only the statistical distributions of symbols in the content items but also the user preferences. In edge source coding, multiple content items might be compressed via the same codebook. For discrete user preferences, DCA (difference of convex functions programming algorithm) based and <inline-formula> <tex-math notation="LaTeX">k </tex-math></inline-formula>-means++ based algorithms are proposed to derive codebook designs. For continuous user preferences, a sampling method is applied to yield codebook designs. In addition, edge source coding is extended to the two-user case and codebooks are designed to utilize multicasting opportunities. Simulation results demonstrate that edge source coding significantly reduces transmission costs for short content items.
Data compression is an efficient technique for saving data storage and transmission costs in networks. Traditional data compression methods usually compress each content item according to its own statistical distribution of symbols and do not take into account user preferences on various content items. However, user preferences significantly impact the statistical distributions of symbols transmitted over communication links. This paper presents an edge source coding method to compress data at the network edge, in which codebooks are designed based on not only the statistical distributions of symbols in the content items but also the user preferences. In edge source coding, multiple content items might be compressed via the same codebook. For discrete user preferences, DCA (difference of convex functions programming algorithm) based and [Formula Omitted]-means++ based algorithms are proposed to derive codebook designs. For continuous user preferences, a sampling method is applied to yield codebook designs. In addition, edge source coding is extended to the two-user case and codebooks are designed to utilize multicasting opportunities. Simulation results demonstrate that edge source coding significantly reduces transmission costs for short content items.
Author Chen, Wei
Lu, Yawei
Poor, H. Vincent
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SubjectTerms Algorithms
codebook design
Codes
Coding
Computer simulation
Convex functions
Data compression
Data storage
Design
difference of convex functions
edge source coding
Image coding
Lossless data compression
Lossless equipment
Multicasting
Simulation
Source coding
Statistical distributions
Symbols
TCPIP
user preference
Title User Preference Aware Lossless Data Compression at the Edge
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