International Journal of Computer Networks and Applications (IJCNA)

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International Journal of Computer Networks and Applications (IJCNA)

International Journal of Computer Networks and Applications (IJCNA)

Published By EverScience Publications

ISSN : 2395-0455

A Critical Survey on Overhead Control Traffic Reduction Strategies in Software-Defined Wireless Sensor Networking

Author NameAuthor Details

Simon Atuah Asakipaam, Jerry John Kponyo, Justice Owusu Agyemang, Frederick Egyin Appiah-Twum

Simon Atuah Asakipaam[1]

Jerry John Kponyo[2]

Justice Owusu Agyemang[3]

Frederick Egyin Appiah-Twum[4]

[1]Department of Telecommunication Engineering, Kwame Nkrumah University of Science and Technology, Kumasi, Ghana

[2]Department of Telecommunication Engineering, Kwame Nkrumah University of Science and Technology, Kumasi , Ghana

[3]Department of Telecommunication Engineering, Kwame Nkrumah University of Science and Technology, Kumasi, Ghana

[4]Department of Telecommunication Engineering, Kwame Nkrumah University of Science and Technology, Kumasi, Ghana

Cite this Article

DOI: 10.22247/ijcna/2021/207978

Pages : 1 - 10

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Abstract

The rising interest in the Internet of Things has contributed to the rapid deployment of wireless sensor networks (WSNs). However, as a result of the design of the sensor nodes and networks, WSNs exhibit dynamic challenges in mobile and large-scale applications. The nodes are equipped with limited resources and the networks have static architectures. These problems hinder the effective implementation of WSNs. Software-Defined Networking (SDN) is intended to overcome these problems by removing control logic from the data plane and incorporating programmability to allow dynamic management and control of the nodes. Unfortunately, the gains from incorporating SDN into WSNs are diminished by high overhead control traffic, created to discover and maintain a global network topology view, leading to impaired network performance. This paper provides a systematic overview of the software-defined wireless network sensor literature to identify potential gaps and to provide recommendations for future studies.

Index Terms

Software-Defined Wireless Sensor Networks

Topology Discovery Protocol

Minimal Overhead Control Traffic

Energy Consumption

Software-Defined Networking

Reference

  1. 1.
    T. M. C. Nguyen, D. B. Hoang, and Z. Chaczko, “Can SDN Technology Be Transported to Software-Defined WSN/IoT?,” Proc. - 2016 IEEE Int. Conf. Internet Things; IEEE Green Comput. Commun. IEEE Cyber, Phys. Soc. Comput. IEEE Smart Data, iThings-GreenCom-CPSCom-Smart Data 2016, pp. 234–239, 2017.
  2. 2.
    K. M. Modieginyane, B. B. Letswamotse, R. Malekian, and A. M. Abu-Mahfouz, "Software-defined wireless sensor networks application opportunities for efficient network management: A survey," Comput. Electr. Eng., vol. 66, pp. 274–287, 2018.
  3. 3.
    N. Sabor, S. Sasaki, M. Abo-Zahhad, and S. M. Ahmed, “A comprehensive survey on hierarchical-based routing protocols for mobile wireless sensor networks: Review, taxonomy, and future directions,” Wirel. Commun. Mob. Comput., vol. 2017, p. 24, 2017.
  4. 4.
    T. Bala, V. Bhatia, S. Kumawat, and V. Jaglan, "A survey: Issues and challenges in wireless sensor network," Int. J. Eng. Technol., vol. 7, no. 2, pp. 53–55, 2018.
  5. 5.
    L. K. Ketshabetswe, A. M. Zungeru, M. Mangwala, J. M. Chuma, and B. Sigweni, “Heliyon Communication protocols for wireless sensor networks?: A survey and comparison,” Heliyon, vol. 5, no. July 2018, p. e01591, 2019.
  6. 6.
    R. C. A. Alves, D. A. G. Oliveira, G. C. C. F. Pereira, B. C. Albertini, and C. B. Margi, “WS 3 N: Wireless Secure SDN-Based Communication for Sensor Networks,” Secure. Commun. Networks, vol. 2018, 2018.
  7. 7.
    M. Razzaq, D. Devi Ningombam, and S. Shin, "Energy-efficient K-means clustering-based routing protocol for WSN using optimal packet size," Int. Conf. Inf. Netw., vol. 2018-Janua, no. 1, pp. 632–635, 2018.
  8. 8.
    M. J. McGrath, C. N. Scanaill, M. J. McGrath, and C. N. Scanaill, “Sensor Network Topologies and Design Considerations,” in Sensor Technologies, 2013, pp. 79–95.
  9. 9.
    S. Kaur and R. N. Mir, “Energy Efficiency Optimization in Wireless Sensor Network Using Proposed Load Balancing Approach,” Int. J. Comput. Networks Appl., vol. 3, no. 5, p. 1, Oct. 2016.
  10. 10.
    N. Benaouda and A. Lahlouhi, “Ant-based delay-bounded and power-efficient data aggregation in wireless sensor networks,” Int. J. Pervasive Comput. Commun., vol. 15, no. 2, pp. 97–119, Jun. 2019.
  11. 11.
    J. Prajapati and S. C. Jain, “Machine Learning Techniques and Challenges in Wireless Sensor Networks,” in 2018 Second International Conference on Inventive Communication and Computational Technologies (ICICCT), 2018, no. Icicct, pp. 233–238.
  12. 12.
    T. Bakhshi, "State of the art and recent research advances in software-defined networking," Wirel. Commun. Mob. Comput., vol. 2017, p. 36, 2017.
  13. 13.
    M. S. Azizi and M. L. Hasnaoui, "Software-defined networking for energy-efficient wireless sensor network," Proc. - 2019 Int. Conf. Adv. Commun. Technol. Networking, CommNet 2019, p. 7, 2019.
  14. 14.
    F. F. Jurado-lasso, G. S. Member, and K. Clarke, “Performance Analysis of Software-Defined Multihop Wireless Sensor Networks,” IEEE Syst. J., pp. 1–10, 2019.
  15. 15.
    T. Tony and L. Hiryanto, "Software-Defined Wireless Sensor Networks: A Systematic Review, Architecture, and Challenges," IOP Conf. Ser. Mater. Sci. Eng., vol. 852, no. 1, p. 012136, Jul. 2020.
  16. 16.
    O. P. Cloete, A. M. Abu-Mahfouz, and G. P. Hancke, "A review of wireless sensor network localization based on software-defined networking," Proc. IEEE Int. Conf. Ind. Technol., vol. 2019-February, no. February, pp. 1731–1736, 2019.
  17. 17.
    S. Abdipoor, "Software-Defined Wireless Sensor Networks: A Survey," Spec. J. Electron. Comput. Sci., vol. 5, no. 3, pp. 62–64, 2019.
  18. 18.
    H. I. Kobo, A. M. Abu-Mahfouz, and G. P. Hancke, “A Survey on Software-Defined Wireless Sensor Networks: Challenges and Design Requirements,” IEEE Access, vol. 5, no. c, pp. 1872–1899, 2017.
  19. 19.
    N. F. Ali, A. M. Said, K. Nisar, and I. A. Aziz, “A Survey on Software Defined Network Approaches for Achieving Energy Efficiency in Wireless Sensor Network,” 2017 IEEE Conf. Wirel. Sensors, vol. 2018-Janua, pp. 28–33, 2017.
  20. 20.
    D. Sinh, L. V. Le, B. S. P. Lin, and L. P. Tung, “SDN/NFV - A new approach of deploying network infrastructure for IoT,” 2018 27th Wirel. Opt. Commun. Conf. WOCC 2018, pp. 1–5, 2018.
  21. 21.
    M. Ndiaye, G. P. Hancke, and A. M. Abu-Mahfouz, "Software-defined networking for improved wireless sensor network management: A survey," Sensors (Switzerland), vol. 17, no. 5, pp. 1–32, 2017.
  22. 22.
    J. Dalal et al., “A Survey on Software-Defined Networking,” IEEE Commun. Surv. TUTORIALS, vol. 7, no. 2, pp. 72–78, 2018.
  23. 23.
    O. Flauzac, C. Javier Gonzalez Santamaria, F. Nolot, and I. Woungang, "An SDN approach to route massive data flow of sensor networks," Int. J. Commun. Syst., vol. 33, no. 7, p. e4309, May 2020.
  24. 24.
    C. L-system, “Distributed Learning Fractal Algorithm for Optimizing a Centralized Control Topology of Wireless Sensor Network Based on the Hilbert,” Sensors, pp. 1–26, 2019.
  25. 25.
    M. Ndiaye, G. P. Hancke, and A. M. Abu-Mahfouz, "Towards Control Message Quenching for SDWSN?: A State of the Art Overview," South. Africa Telecommun. Networks Appl. Conf. 2019, pp. 360–364, 2019.
  26. 26.
    H. I. Kobo et al., “A Survey on Software-Defined Wireless Sensor Networks: Challenges and Design Requirements,” IEEE Access, vol. 5, no. c, pp. 1872–1899, 2017.
  27. 27.
    J. Kipongo, T. O. Olwal, and A. M. Abu-Mahfouz, "Topology Discovery Protocol for Software-Defined Wireless Sensor Network: Solutions and Open Issues," IEEE Int. Symp. Ind. Electron., vol. 2018-June, pp. 1282–1287, 2018.
  28. 28.
    B. B. Letswamotse, R. Malekian, C. Y. Chen, and K. M. Modieginyane, "Software-defined wireless sensor networks and efficient congestion control," IET Networks, vol. 7, no. 6, pp. 460–464, 2018.
  29. 29.
    L. Galluccio, S. Milardo, G. Morabito, and S. Palazzo, "SDN-WISE: Design, prototyping, and experimentation of a stateful SDN solution for WIreless SEnsor networks," in 2015 IEEE Conference on Computer Communications (INFOCOM), 2015, vol. 26, pp. 513–521.
  30. 30.
    A. Anadiotis et al., “SD-WISE?: A Software-Defined Wireless SEnsor network ",” Elsevier, vol. 159, pp. 84–95, Aug. 2019.
  31. 31.
    S. M. Nasim Abdolmaleki, Mahmood Ahmadi, Hadi Tabatabaee Malazi, “Fuzzy topology discovery protocol for SDN-based wireless sensor networks,” Elsevier, vol. 79, pp. 54–68, 2017.
  32. 32.
    J. Kipongo and E. Esenogho, "Efficient Topology Discovery Protocol for Software-Defined Wireless Sensor Network," Int. J. Electr. Comput. Eng., vol. 9, no. September, p. 19, 2020.
  33. 33.
    T. Theodorou and L. Mamatas, “A Versatile Out-of-Band Software-Defined Networking Solution for the Internet of Things,” IEEE Access, vol. 8, pp. 103710–103733, 2020.
  34. 34.
    S. Tomovic and I. Radusinovic, “Performance analysis of a new SDN-based WSN architecture,” 2015 23rd Telecommun. Forum Telford, pp. 99–102, 2017.
  35. 35.
    R. P. Maria Anthony Sahaya, "Improvement of battery lifetime in the software-defined network using particle swarm optimization based cluster-head gateway switch routing protocol with fuzzy rules," Comput. Intell., p. 22, 2019.
  36. 36.
    H. I. Kobo, G. P. Hancke, A. M. Abu-Mahfouz, and G. P. Hancke, "Towards a distributed control system for software-defined Wireless Sensor Networks," Proc. IECON 2017 - 43rd Annu. Conf. IEEE Ind. Electron. Soc., vol. 2017-Janua, pp. 6125–6130, 2017.
  37. 37.
    L. Peizhe, W. Muqing, L. Wenxing, and Z. Min, “A Game-Theoretic and Energy-Efficient Algorithm in an Improved Software-Defined Wireless Sensor Network,” IEEE Access, vol. 5, pp. 13430–13445, 2017.
  38. 38.
    D. P. V. Neetesh Kumar, "A Green Routing Algorithm for IoT-Enabled Software-Defined Wireless Sensor Network," IEEE Sens. J., vol. 18, no. 22, p. 12, 2018.
  39. 39.
    J. Long and O. Büyüköztürk, “Collaborative duty cycling strategies in energy harvesting sensor networks,” Comput. Civ. Infrastruct. Eng., vol. 35, no. 6, pp. 534–548, Jun. 2020.
  40. 40.
    M. Masood, M. M. Fouad, S. Seyedzadeh, and I. Glesk, "Energy-Efficient Software Defined Networking Algorithm for Wireless Sensor Networks," Transp. Res. Procedia, vol. 40, pp. 1481–1488, 2019.
  41. 41.
    S. Misra, S. Bera, A. M. P., S. K. Pal, and M. S. Obaidat, “Situation-Aware Protocol Switching in Software-Defined Wireless Sensor Network Systems,” IEEE Syst. J., vol. 12, no. 3, pp. 2353–2360, Sep. 2018.
  42. 42.
    B. T. de Oliveira and C. B. Margi, “Distributed control plane architecture for software-defined Wireless Sensor Networks,” in 2016 IEEE International Symposium on Consumer Electronics (ISCE), 2016, pp. 85–86.
  43. 43.
    O. Flauzac, C. Gonzalez, and F. Nolot, “Developing a Distributed Software Defined Networking Testbed for IoT,” Procedia Comput. Sci., vol. 83, pp. 680–684, 2016.
  44. 44.
    M. A. Sahaya Sheela and R. Prabakaran, "Improvement of battery lifetime in the software?defined network using particle swarm optimization based cluster?head gateway switch routing protocol with fuzzy rules," Comput. Intell., vol. 36, no. 2, pp. 813–823, May 2020.
  45. 45.
    R. C. A. Alves, D. A. G. Oliveira, G. A. Nunez Segura, and C. B. Margi, “The Cost of Software-Defining Things: A Scalability Study of Software-Defined Sensor Networks,” IEEE Access, vol. 7, pp. 115093–115108, 2019.
  46. 46.
    T. Theodorou and L. Mamatas, "Software-defined topology control strategies for the Internet of Things," in 2017 IEEE Conference on Network Function Virtualization and Software Defined Networks (NFV-SDN), 2017, vol. 2017-Janua, no. November, pp. 236–241.
  47. 47.
    M. U. Younus, S. U. Islam, and S. W. Kim, "Proposition and Real-Time Implementation of an Energy-Aware Routing Protocol for a Software-Defined Wireless Sensor Network," Sensors, vol. 19, no. 12, p. 2739, Jun. 2019.
  48. 48.
    M. Ndiaye, A. M. Abu-Mahfouz, G. P. Hancke, and B. Silva, “Exploring Control-Message Quenching in SDN-based Management of 6LoWPANs,” in 2019 IEEE 17th International Conference on Industrial Informatics (INDIN), 2019, vol. 2019-July, pp. 890–983.
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