Dynamic Resource Allocation Based on Q-learning for VNE in Fiber-Wireless (FiWi) Access Network
Authors: 
QingHai Ou, Honghao Zhao, Yuepian Ye, Xiaohui Yu, Zhu Liu, Xiao Liao, Lin LiuAuthors Info & Claims
QingHai Ou, Honghao Zhao, Yuepian Ye, Xiaohui Yu, Zhu Liu, Xiao Liao, Lin LiuAuthors Info & ClaimsPages 116 - 120
Abstract
As a promising candidate architecture for future access network, Fiber-Wireless (FiWi) access network is also suffering from the bottleneck of resource allocation and optimization due to the complexity and diversity of traffic demands. Although the emerging network virtualization technology has provided a feasible way for FiWi to break the bottleneck, previous works ignored the dynamic characteristics of resource demand of virtual networks which resulted in the resource wasting. In this paper, a dynamic resource management mechanism based on Q-learning algorithm in FiWi access network is proposed. Each physical node and link is equipped with an agent whose responsibility is to detect the delay or packet loss rate of the virtual network embedding periodically and adjust the corresponding resource demand to meet the specific QoS requirement of the virtual networks. Simulation results demonstrate that the proposed dynamic resource management mechanism is able to improve the utilization of network resources on the premise of meeting the QoS requirement of virtual networks.
References
[1]
Y. Liu, L. Guo and B. Gong, "Green survivability in Fiber-Wireless (FiWi) broadband access network," Optical Fiber Technology, 18(2): 68--80, 2012.
[2]
Y. Liu, L. Guo and X. Wei, "Optimizing backup optical-network-units selection and backup fibers deployment in survivable hybrid wireless-optical broadband access networks," IEEE/OSA Journal of Lightwave Technology, 30(10): 1509--1523, Feb. 2012.
[3]
Y. Yu, C. Ranaweera, C. Lim, E. Wong, L. Guo and Y. Liu, "Optimization and Deployment of Survivable Fiber-Wireless (FiWi) Access Networks with Integrated Small Cell and WiFi," in Proc. IEEE ICUWB, Oct. 2015, pp. 1--5.
[4]
Y. Liu, L. Guo, Pengchao Han and Yufang Zhou, "Joint wireless and Optical Resources Allocation based on connection availability in FiWi access network," in Proc. IEEE International Conference on Optical Communications and Networks (ICOCN), Jul. 2015, pp. 1--3.
[5]
P. Han, L. Guo, Y. Liu, X. Wei, J. Hou and X. Han, "A new virtual network embedding framework based on QoS satisfaction and network reconfiguration for fiber-wireless access network," in Proc. IEEE ICC, May 2016, pp. 1--7.
[6]
Q. Dai, G. Shou, Y. Hu and Z. Guo, "A general model for hybrid Fiber-Wireless (FiWi) access network virtualization," in Proc. IEEE ICC, Jun. 2013, pp. 858--862.
[7]
P. Han, L. Guo and Y. Liu, "Virtual Network Embedding in SDN/NFV based Fiber-Wireless Access Network," 2016 in Proc. IEEE ICSN, May 2016, pp. 1--5.
[8]
X. Cheng, S. Su, Z. Zhang, K. Shuang, F. Yang, Y. Luo and Jie Wang. "Virtual Network Embedding Through Topology Awareness and Optimization," Computer Networks, Jul. 2012, 56(6):1797--1813.
[9]
S. Su, Z. Zhang, A. X. Liu, X. Cheng, Y. Wang and X. Zhao. "Energy-Aware Virtual Network Embedding, IEEE/ACM Transactions on Networking," Jan. 2013, 22(5):1607--1620.
[10]
Z. Wang, Y. Han, T. Lin, H. Tang and S. Ci. "Virtual Network Embedding by Exploiting Topological Information," in Proc. IEEE GLOBECOM, Dec. 2012, PP. 2603--2608.
[11]
L. Gong, Y. Wen, Z. Zhu, T. Lee. "Toward Profit-Seeking Virtual Network Embedding Algorithm Via Global Resource Capacity", in Proc. IEEE INFOCOM, May 2014, pp. 1--9.
[12]
S. Haeri, W. W. K. Thong, G. Chen and L. Trajković, "A reinforcement learning-based algorithm for deflection routing in optical burst-switched networks," in Proc. IEEE IRI, Aug. 2013, pp. 474--481.
[13]
I. S. Razo-Zapata, G. Castañon and C. Mex-Perera, "Lightpath requests processing in flexible packet switching optical networks using reinforcement learning," in Proc. IEEE International Conference on Transparent Optical Networks (ICTON), Jun. 2013, pp. 1--4.
[14]
Y. Hou, Y. S. Ong, L. Feng and J. M. Zurada, "An Evolutionary Transfer Reinforcement Learning Framework for Multi-Agent System," IEEE Transactions on Evolutionary Computation, vol. PP, no. 99, pp. 1--15, Feb. 2017.
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- Dynamic Resource Allocation Based on Q-learning for VNE in Fiber-Wireless (FiWi) Access Network
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Published In
June 2017
127 pages
ISBN:9781450352390
DOI:10.1145/3121360
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- Nanyang Technological University
- College of Technology Management, National Tsing Hua University, Taiwan
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Association for Computing Machinery
New York, NY, United States
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Published: 24 June 2017
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ICGSP '17
ICGSP '17: 2017 International Conference on Graphics and Signal Processing
June 24 - 27, 2017
Singapore, Singapore
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