Abstract
Multipath routing is a burning issue in mobile ad hoc network due to its various advantages over single path routing. Some of these advantages are load balancing, bandwidth aggregation, and fault tolerance. Multipath routing means multiple paths exist between source and destination pair. Many works discussed in section 2 addressed queuing delays, but none of them suggested queuing delay for multiple path deliveries of data in mobile ad hoc network context. In this paper, we have designed a mathematical model to compute delay and throughput for multipath. Our model follow the network of M/M/1 queues, and we have applied Burke’s theorem to calculate the queuing delay of the packet in mobile network scenario. This model can be used to estimate delay and throughput of an individual path. Further, through the analysis the best path for data delivery out of available multiple paths as well as the multipath path can be used simultaneously for data delivery to the destination. Simulation result shows that splitted traffic multiple paths outperform splitted traffic. Therefore, our model is useful for design and analysis of ad hoc network. The simulation work has been carried out in Qualnet simulator.
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Mueller, S., Tsang, R. P., & Ghosal, D. (2003). Multipath routing in mobile ad hoc networks: Issues and challenges. In Proceedings of 11th international symposium modeling, analysis and simulation of computer and telecomm. Systems tutorials (MASCOTS’03), 2003 (pp. 209–234).
Burke, P. J. (1956). The output of a queuing system. Operations Research, 4(6), 699–704.
Stallings, W. Queuing analysis. Last Accessed September, 2014, http://www.cosc.brocku.ca/Offerings/3P96/notes/QueuingAnalysis.pdf.
Chee-Hock, N., & Boon-Hee, S. (2008). Queueing modelling fundamentals: With applications in communication networks, 2nd edn. Hoboken: Wiley. ISBN 978-0-470-51957-8.
Jackson, R. R. P. (1954). Queueing systems with phase type service. Operational Research Quarterly, 5, 109–120. doi:10.2307/3007088.
Cho, W., Kim, D., Kim, T., & Kim, T. (2011). Time delay on-demand multipath routing protocol in mobile ad-hoc networks. In Third international conference on ubiquitous and future networks (ICUFN), June, 2011 (pp. 55–60).
Han, Y., & Makowski, A. (2006). Resequencing delays under multipath routing—Asymptotics in a simple queueing model. In Proceedings of 25th IEEE international conference on computer communications, Barcelona, 2006 (pp. 1–12).
Bisnik, N., & Abouzeid, A. A. (2006). Queuing delay and achievable throughput in random access wireless ad hoc networks. 3rd annual IEEE communications society on sensor and ad hoc communications and networks, 28 September 2006, SECON’06 (Vol. 3, pp. 874–880). doi:10.1109/SAHCN.2006.288575.
Li, P., Fang, Y., Li, J., & Huang, X. (2012). Smooth trade-offs between throughput and delay in mobile ad hoc networks. IEEE Transactions on Mobile Computing, 11(3), 427–438.
Das, D., & Abouzeid, A. A. (2014). Delay analysis of multihop cognitive radio networks using network of virtual priority queues. In IEEE wireless communications and networking conference (WCNC), (to appear), Istanbul, Turkey, April 7–9, 2014.
Qiu, T., Xia, F., Feng, L., Wu, G., & Jin, B. (2011). Queueing theory-based path delay analysis of wireless sensor networks. International Journal on Advances in Electrical and Computer Engineering, 11(2), 3–8.
Ping, L., & Peiyan, Y. (2010). An approach to calculate queue delay in mobile ad hoc networks. In Proceeding of IEEE international conference of information science and management engineering (ISME), Xi’an, China, 2010 (Vol. 2, pp. 190–192).
Zeng, Y., et al. (2013). Directional routing and scheduling for green vehicular delay tolerant networks. Wireless Networks, 19(2), 161–173.
Wang, X., et al. (2012). A survey of green mobile networks: Opportunities and challenges. MONET, 17(1), 4–20.
Li, P., et al. (2012). CodePipe: An opportunistic feeding and routing protocol for reliable multicast with pipelined network coding. INFOCOM, 2012, 100–108.
Li, P., et al. (2014). Reliable multicast with pipelined network coding using opportunistic feeding and routing. IEEE Transactions on Parallel and Distributed Systems, 25(12), 3264–3273.
Song, Y., et al. (2014). A biology-based algorithm to minimal exposure problem of wireless sensor networks. IEEE Transactions on Network and Service Management, 11(3), 417–430.
Liu, L., et al. (2015). Physarum optimization: A biology-inspired algorithm for the steiner tree problem in networks. IEEE Transactions on Computers, 64(3), 819–832.
Liu, Y., et al. (2010). Multi-layer clustering routing algorithm for wireless vehicular sensor networks. IET Communications, 4(7), 810–816.
Busch, C., et al. (2012). Approximating congestion + dilation in networks via “Quality of Routing” games. IEEE Transactions on Computers, 61(9), 1270–1283.
Meng, T., et al. (2015). Spatial reusability-aware routing in multi-hop wireless networks. IEEE TMC. doi:10.1109/TC.2015.2417543.
Dvir, A., et al. (2011). Backpressure-based routing protocol for DTNs. ACM SIGCOMM Computer Communication Review, 41(4), 405–406.
Yen, Y.-S., et al. (2011). Flooding-limited and multi-constrained QoS multicast routing based on the genetic algorithm for MANETs. Mathematical and Computer Modelling, 53(11–12), 2238–2250.
Spyropoulos, T., et al. (2010). Routing for disruption tolerant networks: Taxonomy and design. Wireless Networks, 16(8), 2349–2370.
Vasilakos, A., et al. (2012). Delay tolerant networks: Protocols and applications. Boca Raton: CRC Press.
Youssef, M., et al. (2014). Routing metrics of cognitive radio networks: A survey. IEEE Communications Surveys and Tutorials, 16(1), 92–109.
Woungang, I., et al. (2013). Routing in opportunistic networks. Berlin: Springer.
Zhang, X. M., et al. (2015). Interference-based topology control algorithm for delay-constrained mobile Ad hoc networks. IEEE Transactions on Mobile Computing, 14(4), 742–754.
Duarte, P. B. F., et al. (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.
Attar, A., et al. (2012). A survey of security challenges in cognitive radio networks: Solutions and future research directions. Proceedings of the IEEE, 100(12), 3172–3186.
Marwaha, S., et al. (2004). Evolutionary fuzzy multi-objective routing for wireless mobile ad hoc networks. Evolutionary computation, 2004, CEC2004. Congress on 2, 1964–1971.
Vasilakos, A., et al. (2003). Optimizing QoS routing in hierarchical ATM networks using computational intelligence techniques. Systems, Man, and Cybernetics, Part C: Applications and Reviews, IEEE, 33, 297.
Quan, W., et al. (2014). TB2F: Tree-bitmap and bloom-filter for a scalable and efficient name lookup in content-centric networking. IFIP networking, 2014.
Vasilakos, A. V., et al. (2015). Information centric network: Research challenges and opportunities. Journal of Network and Computer Applications, 52, 1–10.
Yao, Y., et al. (2013). EDAL: An energy-efficient, delay-aware, and lifetime-balancing data collection protocol for wireless sensor networks. In MASS (pp. 182–190).
Mir, N. F. (2006). Computer and communication networks. Chapter 11, Section 11.6, Networks of Queues.
Jain, R. (1991). The art of computer systems performance analysis: Techniques for experimental design, measurement, simulation, and modelling. New York, NY: Wiley-Interscience. ISBN 0471503361.
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Das, I., Lobiyal, D.K. & Katti, C.P. Multipath routing in mobile ad hoc network with probabilistic splitting of traffic. Wireless Netw 22, 2287–2298 (2016). https://doi.org/10.1007/s11276-015-1093-y
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DOI: https://doi.org/10.1007/s11276-015-1093-y