A Fast Convergent Cross-layer Resource Optimization Allocation Algorithm in Wireless Multi-hop Networks

Wei FENG; Yongxin XU; Hao LIU; Xiaorong XU; Yingbiao YAO

doi:10.11999/JEIT180581

Volume 41 Issue 5

Apr. 2019

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Article Navigation > Journal of Electronics & Information Technology > 2019 > 41(5): 1217-1224

Wei FENG, Yongxin XU, Hao LIU, Xiaorong XU, Yingbiao YAO. A Fast Convergent Cross-layer Resource Optimization Allocation Algorithm in Wireless Multi-hop Networks[J]. Journal of Electronics & Information Technology, 2019, 41(5): 1217-1224. doi: 10.11999/JEIT180581

Citation:

Wei FENG, Yongxin XU, Hao LIU, Xiaorong XU, Yingbiao YAO. A Fast Convergent Cross-layer Resource Optimization Allocation Algorithm in Wireless Multi-hop Networks[J]. Journal of Electronics & Information Technology, 2019, 41(5): 1217-1224. doi: 10.11999/JEIT180581

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A Fast Convergent Cross-layer Resource Optimization Allocation Algorithm in Wireless Multi-hop Networks

doi: 10.11999/JEIT180581

College of Telecommunication Engineering, Hangzhou Dianzi University, Hangzhou 310018, China

Funds: The National Natural Sicence Foundation of China (61671192), The Public Welfare Plan Project of Zhejiang Province (LGG19F020014), The Postdoctoral Science Foundation of China (2017M621796), The Natural Sicence Foundation of Zhejiang Province (LY19F010011), The Mobile Science Foundation of China (MCM20-2017-0107), The General Science Foundation of Zhejiang Educational Committee (Y201533647)

Received Date: 2018-06-12
Rev Recd Date: 2019-01-15

Available Online: 2019-01-22

Publish Date: 2019-05-01

Abstract

Abstract

In order to improve the performance of the large queue backlogs and low convergence rate in back pressure routing algorithm, the cross-layer optimization of joint congestion control, multi-path routing and power allocation in wireless multi-hop networks is investigated. The system is modeled as a network utility maximization problem under the constraints of flow balancing condition and power. Based on the Newton’s method, the problem is solved and an algorithm with superlinear convergence speed is proposed. With matrix splitting technology, the algorithm can be implemented distributedly further. The simulation results show that the algorithm can effectively increase the energy utility while achieving the maximum network utility, and can keep the queue length at a very low level to decrease the packet transmission delay.
- Wireless multi-hop networks,
- Routing,
- Queue stability,
- Congestion control,
- Power allocation

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References(15)

References

冯维, 冯穗力, 丁跃华, 等. 无线多跳网络下基于过时信道状态信息的跨层资源分配[J]. 电子与信息学报, 2014, 36(11): 2750–2755. doi: 10.3724/SP.J.1146.2013.00546

FENG Wei, FENG Suili, DING Yuehua, et al. Cross-layer resource allocation with outdated channel state Information in wireless multi-hop networks[J]. Journal of Electronics &Information Technology, 2014, 36(11): 2750–2755. doi: 10.3724/SP.J.1146.2013.00546

ERYILMAZ A and SRIKANT R. Joint congestion control, routing, and MAC for stability and fairness in wireless networks[J]. IEEE Journal on Selected Areas in Communications, 2006, 24(8): 1514–1524. doi: 10.1109/jsac.2006.879361

石雷, 韩江洪, 石怡, 等. 无线多跳网络下基于干扰管理的高容量跨层优化策略[J]. 通信学报, 2014, 35(12): 89–97. doi: 10.3969/j.issn.1000-436x.2014.12.011

SHI Lei, HAN Jiang hong, SHI Yi, et al. High capacity cross layer optimization strategy for multi-hop wireless network with interference management[J]. Journal on Communications, 2014, 35(12): 89–97. doi: 10.3969/j.issn.1000-436x.2014.12.011

ALHOSAINY A and KUNZ T. Joint Optimal Congestion, Multipath Routing, and Contention Control for Wireless Ad-hoc Networks[J]. EEE Communications Letters, 2017, PP(99): 1–1. doi: 10.1109/lcomm.2017.2739139

MALEKSHAN K R, ZHUANG W. Joint Scheduling and Transmission Power Control in Wireless Ad Hoc Networks[J]. IEEE Transactions on Wireless Communications, 2017, PP(99): 1–1. doi: 10.1109/wcsp.2009.5371646

WEI E, OZDAGLAR A, and JADBABAIE A. A distributed newton method for network utility maximization[C]. 49th IEEE Conference on Decision and Control, Atlanta, USA, 2010: 1816–1821.

LIU Jia and SHERALI H D. A distributed Newton’s method for joint multi-hop routing and flow control: Theory and algorithm[C]. 2012 Proceedings IEEE INFOCOM, Orlando, USA, 2012: 2489–2497.

LIU Jia, SHROFF N B, XIA C, et al. Joint congestion control and routing optimization: an efficient second-order distributed approach[J]. IEEE/ACM Transactions on Networking, 2016, 24(3): 1404–1420. doi: 10.1109/TNET.2015.2415734

YU Hao and NEELY M J. A new backpressure algorithm for joint rate control and routing with vanishing utility optimality gaps and finite queue lengths[C]. IEEE INFOCOM 2017-IEEE Conference on Computer Communications, Orlando, USA, 2017: 1–9.

HAI L, GAO Q, WANG J, et al. Delay-optimal back-pressure routing algorithm for multi-hop wireless networks[J]. IEEE Transactions on Vehicular Technology, 2017, PP(99): 1–1. doi: 10.1109/TVT.2017.2770183

JU H, LIANG B, LI J, et al. Dynamic power allocation for throughput utility maximization in interference-limited networks[J]. IEEE Wireless Communications Letters, 2013, 2(1): 22–25. doi: 10.1109/wcl.2012.100912.120512

NEELY M J. Super-fast delay tradeoffs for utility optimal fair scheduling in wireless networks[J]. IEEE Journal on Selected Areas in Communications, 2006, 24(8): 1489–1501. doi: 10.1109/jsac.2006.879357

HIRIART-URRUTY J B and LEMARÉCHAL C. Convex analysis and minimization algorithms[J]. Grundlehren Der Mathematischen Wissenschaften, 1993, 1185(1): 150–159. doi: 10.1007/978-3-662-06409-2_2

WOŹNICKI Z I. Matrix splitting principles[J]. International Journal of Mathematics and Mathematical Sciences, 2001, 28(5): 251–284. doi: 10.1155/s0161171201007062

NESTEROV I E and NEMIROVSKIĬ A S. Interior point polynomial algorithms in convex programming, SAM[J]. Studies in Applied Mathematics Philadelphia Siam, 1994, 6(4): 344–345. doi: 10.1137/1.9781611970791

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