Abstract
Generalized network utility maximization (NUM), which has a multiple-variable vector utility function, is a key framework in network resource allocation that supports multi-class services with a different efficiency and fairness. We propose a generalized gradient scheduling (GS) that easily finds a solution to the generalized NUM problem by simplifying its objective function. The properties of the argument of the maximum and the directional derivative are applied to the simplification process. Achieving a generalized GS is a necessary condition for achieving a generalized NUM, and for a special case with scalar utility functions, the generalized GS and generalized NUM are equivalent problems. A practical application of the findings to uplink cellular networks is also presented in this paper.
| Original language | English |
|---|---|
| Article number | 6397542 |
| Pages (from-to) | 111-114 |
| Number of pages | 4 |
| Journal | IEEE Communications Letters |
| Volume | 17 |
| Issue number | 1 |
| DOIs | |
| Publication status | Published - 2013 Jan 4 |
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All Science Journal Classification (ASJC) codes
- Modelling and Simulation
- Computer Science Applications
- Electrical and Electronic Engineering
Cite this
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Generalized gradient scheduling for vector network utility maximization. / Joung, Heejin; Jo, Han Shin; Mun, Cheol; Yook, Jong Gwan.
In: IEEE Communications Letters, Vol. 17, No. 1, 6397542, 04.01.2013, p. 111-114.Research output: Contribution to journal › Article
TY - JOUR
T1 - Generalized gradient scheduling for vector network utility maximization
AU - Joung, Heejin
AU - Jo, Han Shin
AU - Mun, Cheol
AU - Yook, Jong Gwan
PY - 2013/1/4
Y1 - 2013/1/4
N2 - Generalized network utility maximization (NUM), which has a multiple-variable vector utility function, is a key framework in network resource allocation that supports multi-class services with a different efficiency and fairness. We propose a generalized gradient scheduling (GS) that easily finds a solution to the generalized NUM problem by simplifying its objective function. The properties of the argument of the maximum and the directional derivative are applied to the simplification process. Achieving a generalized GS is a necessary condition for achieving a generalized NUM, and for a special case with scalar utility functions, the generalized GS and generalized NUM are equivalent problems. A practical application of the findings to uplink cellular networks is also presented in this paper.
AB - Generalized network utility maximization (NUM), which has a multiple-variable vector utility function, is a key framework in network resource allocation that supports multi-class services with a different efficiency and fairness. We propose a generalized gradient scheduling (GS) that easily finds a solution to the generalized NUM problem by simplifying its objective function. The properties of the argument of the maximum and the directional derivative are applied to the simplification process. Achieving a generalized GS is a necessary condition for achieving a generalized NUM, and for a special case with scalar utility functions, the generalized GS and generalized NUM are equivalent problems. A practical application of the findings to uplink cellular networks is also presented in this paper.
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UR - http://www.scopus.com/inward/citedby.url?scp=84873059253&partnerID=8YFLogxK
U2 - 10.1109/LCOMM.2012.120612.122235
DO - 10.1109/LCOMM.2012.120612.122235
M3 - Article
VL - 17
SP - 111
EP - 114
JO - IEEE Communications Letters
JF - IEEE Communications Letters
SN - 1089-7798
IS - 1
M1 - 6397542
ER -