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Wireless Networks
Erschienen in: Wireless Networks 3/2016

01.04.2016

EPTR: expected path throughput based routing protocol for wireless mesh network

verfasst von: Xiaoheng Deng, Lifang He, Qiang Liu, Xu Li, Lin Cai, Zhigang Chen

Erschienen in: Wireless Networks | Ausgabe 3/2016

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Abstract

For effective routing in wireless mesh networks, we proposed a routing metric, expected path throughput (EPT), and a routing protocol, expected path throughput routing protocol (EPTR), to maximize the network throughput . The routing metric EPT is based on the estimated available bandwidth of the routing path, considering the link quality, the inter- and intra-flow interference and the path length. To calculate the EPT of a routing path, we first calculate the expected bandwidth of the link and the clique, and then consider the decay caused by the path length. Based on EPT, a distributed routing protocol EPTR is proposed, aiming to balance the network load and maximize the network throughput. Extensive simulations are conducted to evaluate the performance of the proposed solution. The results show that the proposed EPTR can effectively balance the network load, achieve high network throughput, and out-perform the existing routing protocols with the routing metrics previously proposed for wireless mesh networks.
Vorheriger Artikel LIP: an efficient lightweight iterative positioning algorithm for wireless sensor networks
Nächster Artikel Cross-layered retransmission schemes for TCP-based services

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Fußnoten
1
The SNR is measured from any received frames at the antenna of the receiver before decoding the spread signal [50].
 
2
In this paper, we use the terms bandwidth and throughput interchangeably.
 
3
We use the term link to refer to the logic point-to-point connection between a transmitter and the receiver, and the term wireless channel to refer to the wireless medium that can carry information over certain space.
 
4
To decrease the storage space, the neighbor list excludes the predecessor node and successor node in the known part of the whole path.
 
Literatur
1.
Deng, X., Liu, Q., Cai, L., & Chen, Z. (2013). Channel quality and load aware routing in wireless mesh network. In 2013 IEEE on wireless communications and networking conference (WCNC) (pp. 2068–2073).
2.
Deng, X., Liu, Q., Li, X., Cai, L., & Chen, Z. (2013). A channel quality and load sensitive routing in wireless mesh network. Chinese Journal of Computers, 36(10), 1–11.
3.
Vasilakos, A., Ricudis, C., Anagnostakis, K., Pedryca, W., & Pitsillides, A. (1998, May). Evolutionary-fuzzy prediction for strategic QoS routing in broadband networks. In Fuzzy systems proceedings, 1998. The 1998 IEEE international conference on IEEE world congress on computational intelligence (Vol. 2, pp. 1488–1493).
4.
Busch, C., Kannan, R., & Vasilakos, A. V. (2012). Approximating congestion+ dilation in networks via “Quality of Routing” games. IEEE Transactions on Computers, 61(9), 1270–1283.MathSciNetCrossRef
5.
Woungang, I., Dhurandher, S. K., Anpalagan, A., & Vasilakos, A. V. (2013) . Routing in opportunistic networks. New York: Springer.CrossRefMATH
6.
Li, P., Guo, S., Yu, S., & Vasilakos, A. V. (2012, March). CodePipe: An opportunistic feeding and routing protocol for reliable multicast with pipelined network coding. In 2012 Proceedings IEEE INFOCOM (pp. 100–108).
7.
Li, P., Guo, S., Yu, S., & Vasilakos, A. V. (2014). Reliable multicast with pipelined network coding using opportunistic feeding and routing. IEEE Transactions on Parallel and Distributed Systems, 25(12), 3264–3273.CrossRef
8.
Demestichas, P. P., Stavroulaki, V. A. G., Papadopoulou, L. M., Vasilakos, A. V., & Theologou, M. E. (2004). Service configuration and traffic distribution in composite radio environments. IEEE Transactions on Systems, Man, and Cybernetics, Part C: Applications and Reviews, 34(1), 69–81.CrossRef
9.
Attar, A., Tang, H., Vasilakos, A. V., Yu, F. R., & Leung, V. (2012). A survey of security challenges in cognitive radio networks: Solutions and future research directions. Proceedings of the IEEE, 100(12), 3172–3186.CrossRef
10.
Youssef, M., Ibrahim, M., Abdelatif, M., Chen, L., & Vasilakos, A. V. (2014). Routing metrics of cognitive radio networks: A survey. IEEE Communications Surveys & Tutorials, 16(1), 92–109.CrossRef
11.
Fadlullah, Z. M., Taleb, T., Vasilakos, A. V., Guizani, M., & Kato, N. (2010). DTRAB: Combating against attacks on encrypted protocols through traffic-feature analysis. IEEE/ACM Transactions on Networking (TON), 18(4), 1234–1247.CrossRef
12.
Jing, Q., Vasilakos, A. V., Wan, J., Lu, J., & Qiu, D. (2014). Security of the Internet of Things: Perspectives and challenges. Wireless Networks, 20(8), 2481–2501.CrossRef
13.
Sheng, Z., Yang, S., Yu, Y., Vasilakos, A., Mccann, J., & Leung, K. (2013). A survey on the ietf protocol suite for the internet of things: Standards, challenges, and opportunities. IEEE Wireless Communications, 20(6), 91–98.CrossRef
14.
Yan, Z., Zhang, P., & Vasilakos, A. V. (2014). A survey on trust management for Internet of Things. Journal of Network and Computer Applications, 42, 120–134.CrossRef
15.
Liu, J., Wan, J., Wang, Q., Deng, P., Zhou, K., & Qiao, Y. (2015). A survey on position-based routing for vehicular ad hoc networks. Telecommunication Systems. doi:10.​1007/​s11235-015-9979-7.
16.
Deng, X., He, L., Li, X., Liu, Q., Cai, L., & Chen, Z. (2015). A reliable QoS-aware routing scheme for neighbor area network in smart grid. Peer-to-Peer Networking and Applications, 1–12.
17.
Akyildiz, I. F., Wang, X., & Wang, W. (2005). Wireless mesh networks: A survey. Computer Networks, 47(4), 445–487.CrossRefMATH
18.
Perkins, C., & Bhagwat, P. (1994). Highly dynamic destination-sequenced distance-vector routing (DSDV) for mobile computers (Vol. 24, pp. 234–244). ACM.
19.
Perkins, C., & Royer, E. (1999). Ad-hoc on-demand distance vector routing. In Second IEEE workshop on mobile computing systems and applications, 1999, Proceedings, WMCSA99 (pp. 90–100).
20.
Clausen, T., Dearlove, C., Jacquet, P., & Herberg, U. (2006). The optimized state routing protocol version 2. draft-ietf-manet-olsrv2-00, Work in progress.
21.
Johnson, D. B., & Maltz, D. A. (1996). Dynamic source routing in ad hoc wireless networks. Mobile Computing, 353, 153–181.
22.
Yen, Y. S., Chao, H. C., Chang, R. S., & Vasilakos, A. (2011). Flooding-limited and multi-constrained QoS multicast routing based on the genetic algorithm for MANETs. Mathematical and Computer Modelling, 53(11), 2238–2250.CrossRef
23.
Zhang, X., Zhang, Y., Yan, F., & Vasilakos, A. (2015). Interference-based topology control algorithm for delay-constrained mobile ad hoc networks. IEEE Transactions on Mobile Computing, 14(4), 742–754.CrossRef
24.
Meng, T., Wu, F., Yang, Z., Chen, G., & Vasilakos, A. (2015). Spatial reusability-aware routing in multi-hop wireless networks. IEEE Transactions on Computers. doi:10.​1109/​TC.​2015.​2417543.
25.
Liu, A., Jin, X., Cui, G., & Chen, Z. (2013). Deployment guidelines for achieving maximum lifetime and avoiding energy holes in sensor network. Information Sciences, 230, 197–226.CrossRef
26.
Han, K., Luo, J., Liu, Y., & Vasilakos, A. V. (2013). Algorithm design for data communications in duty-cycled wireless sensor networks: A survey. IEEE Communications Magazine, 51(7), 107–113.CrossRef
27.
Yao, Y., Cao, Q., & Vasilakos, A. V. (2013, October). EDAL: An energy-efficient, delay-aware, and lifetime-balancing data collection protocol for wireless sensor networks. In 2013 IEEE 10th international conference on mobile ad-hoc and sensor systems (MASS) (pp. 182–190).
28.
Xiang, L., Luo, J., & Vasilakos, A. (2011, June). Compressed data aggregation for energy efficient wireless sensor networks. In 2011 8th annual IEEE communications society conference on sensor, mesh and ad hoc communications and networks (SECON) (pp. 46–54).
29.
Liu, L., Song, Y., Zhang, H., Ma, H., & Vasilakos, A. V. (2015). Physarum optimization: A biology-inspired algorithm for the steiner tree problem in networks. IEEE Transactions on Computers, 64(3), 819–832.MathSciNet
30.
Jiang, L., Liu, A., Hu, Y., & Chen, Z. (2015). Lifetime maximization through dynamic ring-based routing scheme for correlated data collecting in WSNs. Computers & Electrical Engineering, 41, 191–215.CrossRef
31.
Liu, Y., Liu, A., & Chen, Z. (2015). Analysis and improvement of send-and-wait automatic repeat-reQuest protocols for wireless sensor networks. Wireless Personal Communications, 81(3), 923–959.CrossRef
32.
Dvir, A., & Vasilakos, A. V. (2011). Backpressure-based routing protocol for DTNs. ACM SIGCOMM Computer Communication Review, 41(4), 405–406.
33.
Vasilakos, A. V., Zhang, Y., & Spyropoulos, T. (Eds.). (2011). Delay tolerant networks: Protocols and applications. Boca Raton: CRC Press.
34.
Spyropoulos, T., Rais, R. N., Turletti, T., Obraczka, K., & Vasilakos, A. (2010). Routing for disruption tolerant networks: Taxonomy and design. Wireless Networks, 16(8), 2349–2370.CrossRef
35.
Liu, J., Wan, J., Wang, Q., Li, D., Qiao, Y., & Cai, H. (2015). A novel energy-saving one-sided synchronous two-way ranging algorithm for vehicular positioning. Mobile Networks and Applications. doi:10.​1007/​s11036-015-0604-5.
36.
Liu, Y., Xiong, N., Zhao, Y., Vasilakos, A. V., Gao, J., & Jia, Y. (2010). Multi-layer clustering routing algorithm for wireless vehicular sensor networks. IET Communications, 4(7), 810–816.CrossRef
37.
Zeng, Y., Xiang, K., Li, D., & Vasilakos, A. V. (2013). Directional routing and scheduling for green vehicular delay tolerant networks. Wireless Networks, 19(2), 161–173.CrossRef
38.
Zhang, Z., Wang, H., Vasilakos, A. V., & Fang, H. (2012). ECG-cryptography and authentication in body area networks. IEEE Transactions on Information Technology in Biomedicine, 16(6), 1070–1078.CrossRef
39.
De Couto, D., Aguayo, D., & Morris, R. (2003). A high-throughput path metric for multi-hop wireless routing. In MobiCom (Ed.) (pp. 134–146). ACM.
40.
Bicket, J., Aguayo, D., & Morris, R. (2005). Architecture and evaluation of an unplanned 802.11 b mesh network. In Proceedings of the 11th annual international conference on mobile computing and networking (pp. 31–42).
41.
Draves, R., Padhye, J., & Zill, B. (2004). Routing in multi-radio, multihop wirelessmesh networks. In MobiCom (Ed.) (pp. 114–128). ACM.
42.
Langar, R., Bouabdallah, N., & Boutaba, R. (2009). Mobility-aware clustering algorithms with interference constraints in wireless mesh networks. Computer Networks, 53(1), 25–44.CrossRefMATH
43.
Salonidis, T., & Garetto, M. (2007). Identifying high throughput paths in 802.11 mesh networks: A model-based approach. In IEEE international conference on network protocols, 2007, ICNP 2007 (pp. 21–30).
44.
Kowalik, K., & Keegan, B. (2007). Rare C resource aware routing for mesh. In IEEE international conference communications 2007, ICC07 (pp. 4931–4936).
45.
Ronghui, H., King-Shan, L., & Jiandong, L. (2012). Hop-by-hop routing in wireless mesh networks with bandwidth guarantees. IEEE Transactions on Mobile Computing, 11(2), 264–277.CrossRef
46.
Sarr, C., Chaudet, C., & Lassous, I. G. (2008). Bandwidth estimation for IEEE 802.11-based ad hoc networks. IEEE Transactions on Mobile Computing, 7(10), 1228–1241.CrossRefMATH
47.
Yaling, Y., & Kravets, R. (2005). Contention-aware admission control for ad hoc networks. IEEE Transactions on Mobile Computing, 4(4), 363–377.CrossRef
48.
Jia, Z., Gupta, R., Walrand, J., & Varaiya, P. (2005). Bandwidth guaranteed routing for ad-hoc networks with interference consideration. In Proceedings of 10th IEEE symposium on computers and communications, 2005, ISCC 2005 (pp. 3–9).
49.
Duarte, P. B., Fadlullah, Z. M., Vasilakos, A. V., & Kato, N. (2012). On the partially overlapped channel assignment on wireless mesh network backbone: A game theoretic approach. IEEE Journal on Selected Areas in Communications, 30(1), 119–127.CrossRef
50.
Del Prado Pavon, J., & Sunghyun, C. (2003. 2003-01-01). Link adaptation strategy for ieee 802.11 wlan via received signal strength measurement. In IEEE international conference on communications, 2003, ICC03 (Vol. 2, pp. 1108–1113).
51.
Fan, Y., Li, J., Xu, K., Chen, H., Lu, X., Dai, Y., et al. (2013). Performance analysis of the ieee 802.11 distributed coordination function. IEEE Journal on Selected Areas in Communications, 21(18), 20529–20543.
52.
Senthilkumar, D., & Krishnan, A. (2010). Throughput analysis of IEEE 802.11 multirate WLANs with collision aware rate adaptation algorithm. International Journal of Automation and Computing, 7(4), 571–577.CrossRef
53.
Gupta, R., & Walrand, J. (2004). Approximating maximal cliques in ad-hoc networks. In 15th IEEE International symposium on personal, indoor and mobile radio communications, 2004, PIMRC 2004 (Vol. 1, pp. 365–369).
54.
Jiang, W., Jiang, W., Liu, S., Liu, S., Zhu, Y., & Zhu, Y., et al. (2007). Optimizing routing metrics for large-scale multi-radio mesh networks (pp. 1550–1553). IEEE.
55.
Bron, C., & Kerbosch, J. (1973). Algorithm 457: Finding all cliques of an undirected graph. Communications of the ACM, 16(9), 575–577.CrossRefMATH
56.
57.
Metadaten
Titel
EPTR: expected path throughput based routing protocol for wireless mesh network
verfasst von
Xiaoheng Deng
Lifang He
Qiang Liu
Xu Li
Lin Cai
Zhigang Chen
Publikationsdatum
01.04.2016
Verlag
Springer US
Erschienen in
Wireless Networks / Ausgabe 3/2016
Print ISSN: 1022-0038
Elektronische ISSN: 1572-8196
DOI
https://doi.org/10.1007/s11276-015-1003-3

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