Skip to main content

Advertisement

Log in

Routing protocol over lossy links for ISA100.11a industrial wireless networks

  • Published:
Wireless Networks Aims and scope Submit manuscript

Abstract

This paper proposes novel routing and topology control algorithms for industrial wireless sensor networks (IWSNs) based on the ISA100.11a standard. The proposed algorithms not only reduces energy consumption at the node level but also reduces packet latency at the network level. Using the residual energy and packet reception rate of neighbor nodes, the source node can estimate the highest election weight. Hence, packets are conveyed by a multi-hop forwarding scheme from source nodes to the sink by the optimal path. Furthermore, energy consumption and network latency are minimized using integer linear programming. Simulation results show that the proposed algorithms are fully effective in terms of energy conservation and network latency for IWSNs.

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
Fig. 12

Similar content being viewed by others

References

  1. Ahmed, N., Kanhere, S. S., & Jha, S. (2005). The holes problem in wireless sensor networks: A survey. SIGMOBILE Mobile Computing Communications Review, 9, 4–18.

    Article  Google Scholar 

  2. Akerberg, J., Gidlund, M., & Bjorkman, M. (2011). Future research challenges in wireless sensor and actuator networks targeting industrial automation. In 9th IEEE international conference on industrial informatics (INDIN), pp. 410–415.

  3. Akkaya, K., & Younis, M. (2003). An energy-aware QoS routing protocol for wireless sensor networks. In 23rd international conference on distributed computing systems workshops, pp. 710–715.

  4. Al Agha, K., Bertin, M.-H., Dang, T., Guitton, A., Minet, P., Val, T., et al. (2009). Which wireless technology for industrial wireless sensor networks? The development of OCARI technology. IEEE Transactions on Industrial Electronics, 56(10), 4266–4278.

    Article  Google Scholar 

  5. Ammari, H. M., & Das, S. K. (2005). Trade-off between energy savings and source-to-sink delay in data dissemination for wireless sensor networks. In 8th ACM international symposium on modeling, analysis and simulation of wireless and mobile systems, pp. 126–133.

  6. Aziz, A. A., Sekercioglu, Y. A., Fitzpatrick, P., & Ivanovich, M. (2013). A survey on distributed topology control techniques for extending the lifetime of battery powered wireless sensor networks. IEEE Communications Surveys Tutorials, 15(1), 121–144.

    Article  Google Scholar 

  7. Bicakci, K., Gultekin, H., Tavli, B., & Bagci, I. E. (2011). Maximizing lifetime of event-unobservable wireless sensor networks. Computer Standards & Interfaces, 33(4), 401–410.

    Article  Google Scholar 

  8. Bicakci, K., Bagci, I. E., Tavli, B., & Pala, Z. (2013). Neighbor sensor networks: Increasing lifetime and eliminating partitioning through cooperation. Computer Standards & Interfaces, 35(4), 396–402.

    Article  Google Scholar 

  9. Borghini, M., Cuomo, F., Melodia, T., Monaco, U., & Ricciato, F. (2005). Optimal data delivery in wireless sensor networks in the energy and latency domains. In First international conference on wireless internet, pp. 138–145.

  10. Cerpa, A., Wong, J. L., Kuang, L., Potkonjak, M., & Estrin, D. (2005). Statistical model of lossy links in wireless sensor networks. In 4th International symposium on information processing in sensor, networks, pp. 81–88.

  11. Chilamkurti, N., Zeadally, S., Vasilakos, A., & Sharma, V. (2009). Cross-layer support for energy efficient routing in wireless sensor networks. Journal of Sensors, 2009, 1–9.

    Article  Google Scholar 

  12. Chiwewe, T. M., & Hancke, G. P. (2012). A distributed topology control technique for low interference and energy efficiency in wireless sensor networks. IEEE Transactions on Industrial Informatics, 8(1), 11–19.

    Article  Google Scholar 

  13. Chu, X., & Sethu, H. (2012). Cooperative topology control with adaptation for improved lifetime in wireless ad hoc networks. In IEEE INFOCOM, pp. 262–270.

  14. Deng & Jing. (2009). Multihop/direct forwarding (MDF) for static wireless sensor networks. ACM Transactions on Sensor Networks, 5(4), 35.1–35.25.

  15. Dinh, Nguyen Quoc, & Kim, Dong-Sung. (2012). Performance evaluation of priority CSMA-CA mechanism on ISA100.11a wireless network. Computer Standards & Interfaces, 34(1), 117–123.

    Article  Google Scholar 

  16. Felemban, E., & Lee, C.-G. (2006). MMSPEED: Multipath multi-SPEED protocol for QoS guarantee of reliability and timeliness in wireless sensor networks. IEEE Transactions on Mobile Computing, 5(6), 738–754.

    Article  Google Scholar 

  17. Guo, W., & Zhang, W. (2013). A survey on intelligent routing protocols in wireless sensor networks . Journal of Network and Computer Applications 38, 3–17.

  18. Guo, W., Xiong, N., Vasilakos, A. V., Chen, G., & Cheng, H. (2011). Multi-source temporal data aggregation in wireless sensor networks. Wireless Personal Communications, 56(3), 359–370.

    Article  Google Scholar 

  19. Hasegawa, T., Hayashi, H., Kitai, T., & Sasajima, H. (2011). Industrial wireless standardization scope and implementation of ISA SP100 standard. In SICE annual conference (SICE), pp. 2059–2064.

  20. He, T., Stankovic, J., Lu, C., & Abdelzaher, T. (2003). SPEED: A stateless protocol for real-time communication in sensor networks. In 23rd international conference on distributed computing systems, pp. 46–55.

  21. Hoa, T. D., & Kim, D.-S. (2012). Minimum latency and energy efficiency routing with lossy link awareness in wireless sensor networks. In 9th IEEE international workshop on factory communication systems (WFCS), pp. 75–78.

  22. Ishii, Y. (2009). Exploiting backbone routing redundancy in industrial wireless systems. IEEE Transactions on Industrial Electronics, 56(10), 4288–4295.

    Article  Google Scholar 

  23. Lee, C.-Y., Shiu, L.-C., Lin, F.-T., & Yang, C.-S. (2013). Distributed topology control algorithm on broadcasting in wireless sensor network. Journal of Network and Computer Applications 1–10.

  24. Li, Mo, et al. (2013). A survey on topology control in wireless sensor networks: Taxonomy, comparative study, and open issues. Proceedings of the IEEE, 101(12), 2538–2557.

    Article  Google Scholar 

  25. 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.

    Article  Google Scholar 

  26. Liu, Y., Ni, L., & Chuanping, H. (2012). A generalized probabilistic topology control for wireless sensor networks. IEEE Journal on Selected Areas in Communications, 30(9), 1780–1788.

    Article  Google Scholar 

  27. Pan, Z., Yang, Y., & Gong, D. (2010). Distributed clustering algorithms for lossy wireless sensor networks. In 9th IEEE international symposium on network computing and applications, pp. 36–43.

  28. Petersen, S., & Carlsen, S. (2011). WirelessHART versus ISA100.11a: The format war hits the factory floor. IEEE Industrial Electronics Magazine, 5(4), 23–34.

    Article  Google Scholar 

  29. Quang, P. T. A., & Kim, D.-S. (2012). Enhancing real-time delivery of gradient routing for industrial wireless sensor networks. IEEE Transactions on Industrial Informatics, 8(1), 61–68.

    Article  Google Scholar 

  30. Quang, P. T. A., & Kim, D.-S. (2014). Throughput-aware routing for industrial sensor networks: Application to ISA100.11a. IEEE Transactions on Industrial Informatics, 10(1), 1551–3203.

    Google Scholar 

  31. Seada, K., Zuniga, M., Helmy, A., & Krishnamachari, B. (2004). Energy-efficient forwarding strategies for geographic routing in lossy wireless sensor networks. In 2nd international conference on embedded networked sensor systems, pp. 108–121.

  32. Spyropoulos, T., et al. (2010). Routing for disruption tolerant networks: Taxonomy and design. Wireless networks, 16, 2349–2370.

    Article  Google Scholar 

  33. Tan, D. D., & Kim, D.-S. (2013). Dynamic traffic-aware routing algorithm for multi-sink wireless sensor networks. Wireless Networks, 19(8).

  34. Tan, D. D., Dinh, N. Q., & Kim, D.-S. (2013). GRATA: A gradient-based traffic-aware routing for wireless sensor networks. IET Wireless Sensor Systems, 3(2), 104–111.

  35. Vasilakos, A., et al. (2012). Delay tolerant networks: Protocols and applications. Boca Raton: CRC Press.

    Google Scholar 

  36. Wang, Xiaofei, Vasilakos, Athanasios V., Chen, Min, Liu, Yunhao, & Kwon, Ted Taekyoung. (2012). A survey of green mobile networks: Opportunities and challenges. Mobile Networks and Applications, 17(1), 4–20.

    Article  Google Scholar 

  37. Wei, G., et al. (2011). Prediction-based data aggregation in wireless sensor networks: Combining grey model and Kalman filter. Computer Communications, 34(6), 793–802.

    Article  Google Scholar 

  38. Xiang, L., Luo, J., & Vasilakos, A. (2011). Compressed data aggregation for energy efficient wireless sensor networks. In IEEE Communications society conference on sensor, mesh and ad hoc communications and networks (SECON), pp. 46–54.

  39. Xiao, Y., & Peng, M. (2012). Tight performance bounds of multihop fair access for mac protocols in wireless sensor networks and underwater sensor networks. IEEE Transactions on Mobile Computing, 11(10), 1538–1554.

    Article  Google Scholar 

  40. Yena, Y.-S., Chaob, H.-C., Changd, R.-S., & Vasilakose, A. (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.

    Article  Google Scholar 

  41. Younis, O., & Fahmy, S. (2004). HEED: A hybrid, energy-efficient, distributed clustering approach for ad hoc sensor networks. IEEE Transactions on Mobile Computing, 3, 366–379.

    Article  Google Scholar 

  42. Youssef, M., Ibrahim, M., Abdelatif, M., & Vasilakos, A. V. (2014). Routing metrics of cognitive radio networks: A survey. IEEE Communications Surveys & Tutorials, 16(1), 92–109.

    Article  Google Scholar 

  43. Zeng, Y., et al. (2013). Directional routing and scheduling for green vehicular delay tolerant networks. Wireless networks, 19, 161–173.

    Article  Google Scholar 

  44. Zhang, Y., Li, X., Yang, J., Liu, Y., Xiong, N., & Vasilakos, A. V. (2013). A real-time dynamic key management for hierarchical wireless multimedia sensor network. 67(1), 97–117.

  45. Zuniga, M., & Krishnamachari, B. (2004). Analyzing the transitional region in low power wireless links. In First annual IEEE communications society conference on sensor and ad hoc communications and networks, pp. 517–526.

Download references

Acknowledgments

This research was financially supported by National Research Foundation of Korea (NRF) through the Human Resource Training Project for Regional Innovation 2014 and Basic Science Research Program (NO. 2011-0025409).

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Dong-Seong Kim.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Pham, TL., Kim, DS. Routing protocol over lossy links for ISA100.11a industrial wireless networks. Wireless Netw 20, 2359–2370 (2014). https://doi.org/10.1007/s11276-014-0747-5

Download citation

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11276-014-0747-5

Keywords

Navigation