Skip to main content

Advertisement

SpringerLink
Log in

Adaptive multi-channel allocation for vehicular infrastructure mesh systems

  • Published:
Multimedia Tools and Applications Aims and scope Submit manuscript

Abstract

This paper focuses on a wireless solution for vehicular infrastructure systems. In order to achieve both low cost and high efficiency, infrastructures can be connected to each other in vehicular networks by a wireless link similar to a mesh router in wireless mesh networks (WMNs). However, the existing WMN solutions cannot appropriately support various vehicular applications that require high rate and low latency communications. Therefore, in this paper, we present the design and performance evaluation of an adaptive multi-channel allocation for vehicular infrastructure mesh systems (abbreviated AMCA). In order to meet both high rate and low latency communications, AMCA is designed to provide optimal channel assignment duration for each flow to efficiently utilize multiple non-overlapping channels. The performance evaluation of AMCA is conducted by the QualNet 5.0 simulator under various network scenarios to consider diverse network conditions. Simulation results show that AMCA can achieve higher network throughput and lower average packet delay than other well known wireless solutions.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8
Fig. 9
Fig. 10
Fig. 11
Fig. 12
Fig. 13

Similar content being viewed by others

References

  1. Akyildiz IF, Wang X, Wang W (2005) Wireless mesh networks: a survey. Comput Netw 47:445–487. doi:10.1016/j.comnet.2004.12.001

    Article  MATH  Google Scholar 

  2. Alasmary W, Weihua Z (2010) The mobility impact in IEEE 802.11p infrastructureless vehicular networks. in Proc. IEEE VTC-Fall 1–5. doi: 10.1109/VETECF.2010.5594542

  3. Bianchi G (2000) Performance analysis of the IEEE 802.11 Distributed Coordination Function. IEEE J Sel Areas Commun 18:535–547. doi:10.1109/49.840210

    Article  Google Scholar 

  4. Bruno R, Conti M, Gregori M (2005) Mesh networks: commodity multihop Ad Hoc networks. IEEE Commun 43:123–131. doi:10.1109/MCOM.2005.1404606

    Article  Google Scholar 

  5. Chu IC, Chen PY, Chen WT (2012) An IEEE 802.11p Based Distributed Channel Assignment Scheme Considering Emergency Message Dissemination. in proc. Vehicular Technology Conference (VTC Spring) 1–5. doi: 10.1109/VETECS.2012.6240201

  6. Dar K, Bakhouya M, Gaber J, Wack M (2010) Wireless communication technologies for ITS applications. IEEE Commun Mag 48:156–162. doi:10.1109/MCOM.2010.5458377

    Article  Google Scholar 

  7. Doukha Z, Moussaoui S, Haouari N, Delhoum M (2012) An efficient emergency message dissemination protocol in a vehicular Ad Hoc network. Commun Comput Inf Sci 293:459–469. doi:10.1007/978-3-642-30507-8_39

    Article  Google Scholar 

  8. Ergen M, Varaiya P (2005) Throughput analysis and admission control for IEEE 802.11a. Mob Netw Appl 10:705–706. doi:10.1007/s11036-005-3364-9

    Article  Google Scholar 

  9. Ezell S (2010) Explaining International IT Application Leadership: Intelligent Transportation Systems. ITIF - The Information Technology & Information Foundation

  10. HamzaLup GL, Hua KA, Le M, Peng R (2008) Dynamic plan generation and real-time management techniques for traffic evacuation. IEEE Trans Intell Transp Syst 9:615–624. doi:10.1109/TITS.2008.2006738

    Article  Google Scholar 

  11. IEEE 802.11Wireless LAN Medium Access Control (MAC) and Physical Layer (PHY) Specifications (1999)

  12. Kim EJ, In J, Youm S, Kang CH (2012) Delay attack-resilient clock synchronization for wireless sensor networks. IEICE TRANS INF E95-D:188–191. doi:10.1587/transinf.E95.D.188

    Article  Google Scholar 

  13. Kim EJ, Shon T, Park JJH, Jeong YS (2011) Throughput fairness enhancement using differentiated channel access in heterogeneous sensor networks. Sensors 11:6629–6644. doi:10.3390/s110706629

    Article  Google Scholar 

  14. Kim EJ, Shon T, Park JJH, Kang CH (2012) Latency bounded and energy efficient MAC for wireless sensor networks. IET Commun 6:2120–2127. doi:10.1049/iet-com.2011.0700

    Article  Google Scholar 

  15. Kim EJ, Youm S, Choi HH (2012) Queuing analysis for IEEE 802.11e networks in non-saturation environments. Int J Adv Robot Syst 9:1–9. doi:10.5772/50911

    Google Scholar 

  16. Kim EJ, Youm S, Kang CH (2011) Power-controlled topology optimization and channel assignment for hybrid MAC in wireless sensor networks. IEICE Trans Commun E94-B:2461–2472. doi:10.1587/transcom.E94.B2461

    Article  Google Scholar 

  17. Nieminen J, Janetti R (2011) Delay-throughput analysis of multi-channel MAC protocols in Ad Hoc networks. Eurasip J Wirel Commun Netw. doi:10.1186/1687-1499-2011-108

    Google Scholar 

  18. Qualnet Version 5.0. [Online]. Available: www.scalable-networks.com.

  19. Rawat D, Popescu D, Yan G, Olariu S (2011) Enhancing VANET performance by joint adaptation of transmission power and contention window size. IEEE Trans Parallel Distrib Syst 22:1528–1535. doi:10.1109/TPDS.2011.41

    Article  Google Scholar 

  20. So J, Vaidya N (2004) Multi-Channel MAC for Ad Hoc Networks: Handling Multi-Channel Hidden Terminals Using A Single Transceiver. in Proc. ACM MobiHOC 222–233. doi: 10.1145/989459.989487

  21. Task Group P (2009) IEEE draft amendment to standard for information technology - telecommunications and information exchange between systems - local and metropolitan networks - specific requirements - part 11: Wireless LAN medium access control (MAC) and physical layer (PHY) specifications: Amendment: Wireless access in vehicular environments. IEEE 802.11p Draft 9.0

  22. Uzcategui R, Acosta-Marum G (2009) WAVE: a tutorial. IEEE Commun Mag 47:126–133. doi:10.1109/MCOM.2009.4939288

    Article  Google Scholar 

  23. Ye F, Roy S, Niu Z (2010) Flow oriented channel assignment for multi-radio wireless mesh networks. EURASIP J Wirel Commun Netw. doi:10.1155/2010/930414

    Google Scholar 

  24. Zhang J, Wang FY, Wang K, Lin WH, Xu X, Chen C (2011) Data-driven intelligent transportation systems: a survey. IEEE Trans Intell Transp Syst 12:1624–1639. doi:10.1109/TITS.2011.2158001

    Article  Google Scholar 

Download references

Acknowledgments

This research was supported by Hallym University Research Fund, 2013 (HRF-201309-002).

Author information

Authors and Affiliations

  1. Software R&D Lab., LIG Nex1 Co., Ltd., 333, Pangyo-ro, Bundang-gu, Seongnam-City, Gyeonggi-do, 463-400, South Korea

    Jung-Hyok Kwon

  2. Department of Ubiquitous Computing, Hallym University, 39 Hallymdaehak-gil, Chuncheon-si, Gangwon-do, 200-702, South Korea

    Eui-Jik Kim

Authors
  1. Jung-Hyok Kwon
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Eui-Jik Kim
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Eui-Jik Kim.

Rights and permissions

Reprints and permissions

About this article

Cite this article

Kwon, JH., Kim, EJ. Adaptive multi-channel allocation for vehicular infrastructure mesh systems. Multimed Tools Appl 74, 1593–1609 (2015). https://doi.org/10.1007/s11042-013-1752-x

Download citation

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11042-013-1752-x

Keywords

Search

Navigation