Skip to main content

Advertisement

Log in

Multi-class Multipath Routing Protocol for Low Power Wireless Networks with Heuristic Optimal Load Distribution

  • Published:
Wireless Personal Communications Aims and scope Submit manuscript

Abstract

The distributed nature and dynamic topology of hierarchical low power wireless networks have made them an interesting platform for ubiquitous applications and smart environments. Wireless Sensor and Actuator Networks are a well known example in this area where the nodes collaborate to disseminate data over multi-hop routing trees. Emerging applications like smart grids and internet of things, demand more traffic volumes with QoS requirements, such as delay and reliability. The traditional shortest path routing fails to meet these demands because of producing more congestion, delay, packet loss, and energy consumption along the limited optimal paths. Multipath routing is a promising way to meet both the QoS constraints and lifetime concerns. In this paper we propose a proactive multipath load balancing approach which tries to achieve maximum lifetime by equalizing the traffic rate between the nodes of equal distance from the local sink. The load balancing and QoS provision is achieved through a network flow optimization problem, which is locally solved by a novel Heuristic Optimal Load Distributor. The load distribution is performed over a routing graph produced by a Multi-class Multipath Routing Protocol for Low power and lossy networks (\(\hbox {M}^2\hbox {RPL}\)). The simulation results show the efficiency of the proposed framework, that leads to 30 % increase in lifetime and 10 % decrease in average delay compared to some well known algorithms in the area.

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

Access this article

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

Similar content being viewed by others

References

  1. Kushulnagar, N., Montenegro, G., & Shumacher, C. (2007). Ipv6 over low-power wireless personal area networks (6lowpans): Overview, assumptions, problem statement, and goals (2007). RFC4919.

  2. Xiaonan, W., & Shan, Z. (2013). A hierarchical scheme on achieving all-ip communication between wsn and ipv6 networks. International Journal of Electronics and Communications, 67, 414.

    Article  Google Scholar 

  3. Winter, T., & Thubert, P. (2012). Rpl: Ipv6 routing protocol for low-power and lossy networks (2012). RFC6550.

  4. Hassanein, H., & Luo, J. (2006). In: 2nd IEEE workshop on dependability and security in sensor networks and systems (pp. 54–64). Los Alamitos, CA.

  5. Huang, X., & Fang, Y. (2008). Multiconstrained qos multipath routing in wireless sensor networks. Wireless Networks, 14, 465. doi:10.1007/s11276-006-0731-9.

    Article  Google Scholar 

  6. Li, S., Ma, X., Wang, X., & Tan, M. (2011). Energy-efficient multipath routing in wireless sensor network considering wireless interference. Journal of Control Theory and Applications, 9(1), 127. doi:10.1007/s11768-011-0263-4.

    Article  MathSciNet  Google Scholar 

  7. Teo, J., Ha, Y., & Tham, C. (2008). Interference-minimized multipath routing with congestion control in wireless sensor network for high-rate streaming. IEEE Transactions on Mobile Computing, 7(9), 1124. doi:10.1109/TMC.2008.24.

    Article  Google Scholar 

  8. Sha, K., Gehlot, J., & Greve, R. (2013). Multipath routing techniques in wireless sensor networks: A survey. Wireless Personal Communications, 70(2), 807. doi:10.1007/s11277-012-0723-2.

  9. Eghbali, A. N., & Dehghan, M. (2007). In: Proceedings of the 3rd international conference on Mobile ad-hoc and sensor networks (pp. 44–55) Berlin: Springer, 2007, MSN’07. http://dl.acm.org/citation.cfm?id=1781974.1781982.

  10. Tao, M., Lu, D., & Yang, J. (2012). An adaptive energy-aware multi-path routing protocol with load balance forwireless sensor networks. Wireless Personal Communications, 63, 823.

    Article  Google Scholar 

  11. Karkazis, P., Trakadas, P., Leligou, H., Sarakis, L., Papaefstathiou, I., & Zahariadis, T. (2012). Evaluating routing metric composition approaches for qos differentiation in low power and lossy networks. Wireless Networks, (pp. 1–16). doi:10.1007/s11276-012-0532-2.

  12. Uthra, R., & Raja, S. (2012). Qos routing in wireless sensor networksa survey. ACM Computing Surveys, 45(1), doi:10.1145/2379776.2379785.

  13. Medjiah, S., Ahmed, T., & Asgari, A. (2012). Streaming multimedia over wmsns: An online multipath routing protocol. International Journal of Sensor Networks, 11(1), 10.

    Article  Google Scholar 

  14. Felemban, E., Lee, C., & Ekici, E. (2006). Mmspeed: Multipath multi-speed protocol for qos guarantee of reliability and timeliness in wireless sensor networks. IEEE Transactions on Mobile Computing, 5(6), 738.

    Article  Google Scholar 

  15. Kim, S. (2012). An ant-based multipath routing algorithm for qos aware mobile ad-hoc networks. Wireless Personal Communications, 66, 739. doi:10.1007/s11277-011-0361-0.

    Article  Google Scholar 

  16. Krishna, P., Saritha, V., Vedha, G., Bhiwal, A., & Chawla, A. (2012). Quality-of-service-enabled ant colony-based multipath routing for mobile ad hoc networks. IET Communications, 6(1), 76. doi:10.1049/iet-com.2010.0763.

    Article  MATH  MathSciNet  Google Scholar 

  17. Carballido Villaverde, B., Rea, S., & Pesch, D. (2012). Inrout: A qos aware route selection algorithm for industrial wireless sensor networks. Ad Hoc Networks, 10(3), 458. doi:10.1016/j.adhoc.2011.07.015.

    Article  Google Scholar 

  18. Ronasi, K., Mohsenian-Rad, A., Gopalakrishnan, S., Wong, V., & Schober, R. (2011). Delaythroughput enhancement in wireless networks with multipath routing and channel coding. IEEE Transaction on Vehicular Technology, 60(30), 1116. doi:10.1109/TVT.2010.2103097.

    Article  Google Scholar 

  19. Tulasiraman, P., Chen, J., & Shen, X. (2011). Multipath routing and max-min fair qos provisioning under interference constraints in wireless multihop networks. IEEE Transactions on Parallel and Distributed Systems, 22(5), 716. doi:10.1109/TPDS.2010.145.

    Article  Google Scholar 

  20. Bagula, A. (2010). Modelling and implementation of qos inwireless sensor networks: Amulticonstrained traffic engineeringmodel. EURASIP Journal onWireless Communications and Networking, 2010, doi:10.1155/2010/468737.

  21. Ben-Othman, J., & Yahya, B. (2010). Energy efficient and qos based routing protocol for wireless sensor networks, Journal of Parallel and Distributed Computing, 70(8), 849. doi:10.1016/j.jpdc.2010.02.010. http://www.sciencedirect.com/science/article/pii/S0743731510000341.

  22. Thubert, P. (2012). Objective function zero for the routing protocol for low-power and lossy networks (rpl) (2012). RFC6552.

  23. Bertsekas, D., & Tsitsiklis, J. (1997). Parallel and distributed computation: Numerical methods (Athena Scientific, 1997), chap. 5: Network Flow Problems, (p. 417).

  24. Kwon, O., Oh, H., Lee, Z., Lee, G., Park, Y., & Song, H. (2013). Entire network load-aware cooperative routing algorithm for video streaming over mobile ad hoc networks. Wireless Communications and Mobile Computing, 13, 1135. doi:10.1002/wcm.1169.

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Meisam Nesary Moghadam.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Moghadam, M.N., Taheri, H. & Karrari, M. Multi-class Multipath Routing Protocol for Low Power Wireless Networks with Heuristic Optimal Load Distribution. Wireless Pers Commun 82, 861–881 (2015). https://doi.org/10.1007/s11277-014-2257-2

Download citation

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11277-014-2257-2

Keywords

Navigation