DocumentCode
1464787
Title
Multiple description coding in networks with congestion problem
Author
Alasti, Mehdi ; Sayrafian-Pour, Kamran ; Ephremides, Anthony ; Farvardin, Nariman
Author_Institution
Dept. of Electr. & Comput. Eng., Maryland Univ., College Park, MD, USA
Volume
47
Issue
3
fYear
2001
fDate
3/1/2001 12:00:00 AM
Firstpage
891
Lastpage
902
Abstract
Suppose that the description of a stochastic process needs to be sent to a destination through a communication network. Also assume there is a risk that the description may be lost. A technique to reduce the risk of losing such descriptions is by sending two (or more) descriptions and hoping that in this way at least one of the descriptions will get through. This problem is referred to as multiple description coding (MDC) and was first introduced by Gersho, Witsenhausen, Wolf, Wyner, Ziv and Ozarow (1979). So far, the main focus of research on this subject has been on the achievable rate-distortion functions and the related structural design issues for such encoders and decoders. Little effort has focused on the performance of such coding schemes in simple communication networks and relation of the overall distortion with respect to some network parameter such as congestion. In this paper, a double description coding (DDC) system in a simple network represented by a set of parallel queues is studied. Comparison is made with a single description coding system and it is shown that DDC significantly improves the overall average end-to-end distortion at high network loading
Keywords
encoding; queueing theory; rate distortion theory; stochastic processes; telecommunication congestion control; telecommunication networks; achievable rate-distortion functions; average end-to-end distortion; communication network; decoders; double description coding; encoders; high network loading; multiple description coding; network congestion; network parameter; parallel queues; performance; single description coding system; stochastic process; structural design; Communication networks; Communication systems; Conferences; Decoding; Government; Information theory; Intelligent networks; Rate-distortion; Signal to noise ratio; Stochastic processes;
fLanguage
English
Journal_Title
Information Theory, IEEE Transactions on
Publisher
ieee
ISSN
0018-9448
Type
jour
DOI
10.1109/18.915641
Filename
915641
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