DocumentCode :
692351
Title :
Energy-aware optimal resource allocation in MR-MC wireless networks
Author :
Lu Liu ; Xianghui Cao ; Yu Cheng
Author_Institution :
Dept. of Electr. & Comput. Eng., Illinois Inst. of Technol. Chicago, Chicago, IL, USA
fYear :
2013
fDate :
9-13 Dec. 2013
Firstpage :
4865
Lastpage :
4870
Abstract :
Multi-radio multi-channel (MR-MC) networks as a promising technique to enhance the capacity of wireless networks have received a lot of attentions recently. While most of the existing studies focus on capacity optimization, energy-efficient resource allocation for MR-MC networks is an emerging area yet to be exploited. In this paper, we develop an optimization framework for energy-aware optimal resource allocation in MR-MC wireless networks. Our framework is based on a multi-commodity flow (MCF) formulation augmented with constraints developed from a multi-dimensional conflict graph (MDCG). The basic idea is that there normally exist multiple possible resource allocation configurations, i.e., the combinations of routing, channel assignment and scheduling solutions, leading to the same optimal network capacity. Our method can identify the optimal resource allocation with the minimum energy consumption. Numerical results show that our energy-aware resource allocation can considerably improve energy efficiency compared to an energy-blind solution. The amount of saved energy is even more significant with a slight sacrifice of the network capacity.
Keywords :
channel allocation; graph theory; resource allocation; scheduling; telecommunication network routing; telecommunication power management; MCF formulation; MDCG; MR-MC wireless networks; capacity optimization; channel assignment; energy-aware optimal resource allocation; energy-blind solution; energy-efficient resource allocation; minimum energy consumption; multicommodity flow; multidimensional conflict graph; multiradio multichannel networks; optimal network capacity; optimization framework; routing combinations; scheduling solutions; Energy consumption; Interference; Optimal scheduling; Resource management; Throughput; Wireless networks; Multi-radio multi-channel networks; energy ef-ficiency; resource allocation;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Global Communications Conference (GLOBECOM), 2013 IEEE
Conference_Location :
Atlanta, GA
Type :
conf
DOI :
10.1109/GLOCOMW.2013.6855721
Filename :
6855721
Link To Document :
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