skip to main content
10.1145/3415088.3415115acmotherconferencesArticle/Chapter ViewAbstractPublication PagesiconicConference Proceedingsconference-collections
research-article

Intelligent traffic management algorithm for wireless sensor networks

Published:24 September 2020Publication History

ABSTRACT

Wireless Sensor Networks (WSNs) are used to simplify various real-time applications which include traffic management, humidity, monitoring of the temperature, and pressure by using a wide range of sensor nodes. Sensor nodes are assigned through various resource restrictions such as allocated bandwidth, available memory, and battery power. This research paper demonstrated the packet congestion issue that happens during packet distribution from the source node to destination node. The packet congestion in WSNs is normally caused by Buffer overflow. This leads to the decrement of network throughput, packet drop, and high end-to-end delay during packet transmission from and to different nodes. Therefore, in order to avoid packet congestion in WSNs, an Intelligent Traffic Management (ITM) algorithm is proposed. The proposed ITM algorithm was developed by integrating different algorithms namely: Modified Neural Network Wavelet Congestion Control (MNNWCC) algorithm and Tree-based Congestion Control (TACC) algorithm. The simulation is performed using the Network Simulator 2 (NS-2) simulation platform. The simulation results showed that the proposed ITM algorithm improves the network throughput by 97.1 %, reduce packet drop by 32%, and end-to-end delay minimized by 27% when compared with MNNWCC algorithm and TACC algorithm.

References

  1. F. K. Shaikh and S. Zeadally, "Energy harvesting in wireless sensor networks: A comprehensive review," Renewable and Sustainable Energy Reviews, vol. 55, pp. 1041--1054, 2016.Google ScholarGoogle ScholarCross RefCross Ref
  2. T. E. Mathonsi and O. P. Kogeda, "Implementing wireless network performance optimization for Small and Medium Enterprises," in Science, Computing and Telecommunications (PACT), 2014 Pan African Conference on, 2014, pp. 68--73.Google ScholarGoogle Scholar
  3. O. A. Osanaiye, A. S. Alfa, and G. P. Hancke, "Denial of service defence for resource availability in wireless sensor networks," IEEE Access, vol. 6, pp. 6975--7004, 2018.Google ScholarGoogle ScholarCross RefCross Ref
  4. Y. H. Robinson, E. G. Julie, S. Balaji, and A. Ayyasamy, "Energy aware clustering scheme in wireless sensor network using neuro-fuzzy approach," Wireless Personal Communications, vol. 95, pp. 703--721, 2017. Google ScholarGoogle ScholarDigital LibraryDigital Library
  5. J. R. Srivastava and T. Sudarshan, "Energy-efficient cache node placement using genetic algorithm in wireless sensor networks," Soft Computing, vol. 19, pp. 3145--3158, 2015. Google ScholarGoogle ScholarDigital LibraryDigital Library
  6. S. Arora and S. Singh, "Node localization in wireless sensor networks using butterfly optimization algorithm," Arabian Journal for Science and Engineering, vol. 42, pp. 3325--3335, 2017.Google ScholarGoogle ScholarCross RefCross Ref
  7. M. Vecchio and R. López-Valcarce, "Improving area coverage of wireless sensor networks via controllable mobile nodes: A greedy approach," Journal of network and computer applications, vol. 48, pp. 1--13, 2015. Google ScholarGoogle ScholarDigital LibraryDigital Library
  8. R. P. Narayanan, T. V. Sarath, and V. V. Vineeth, "Survey on motes used in wireless sensor networks: Performance & parametric analysis," Wireless Sensor Network, vol. 8, p. 51, 2016.Google ScholarGoogle ScholarCross RefCross Ref
  9. P. Mohanty and M. R. Rabat, "Energy efficient structure-free data aggregation and delivery in WSN," Egyptian Informatics Journal, vol. 17, pp. 273--284, 2016.Google ScholarGoogle ScholarCross RefCross Ref
  10. A. Phamila and R. Amutha, "Energy-efficient low bit rate image compression in wavelet domain for wireless image sensor networks," Electronics Letters, vol. 51, pp. 824--826, 2015.Google ScholarGoogle ScholarCross RefCross Ref
  11. K. S. Yadav and M. Tamboli, "Defending Against Path-Based Denial of Service Attack in Wireless Sensor Network," in International Conference on Examination in Modern Technology and Engineering (ICEMTE), 2017, pp. 46--51.Google ScholarGoogle Scholar
  12. P. Aimtongkham, T. G. Nguyen, and C. So-In, "Congestion control and prediction schemes using Fuzzy logic system with adaptive membership function in wireless sensor networks," Wireless Communications and Mobile Computing, vol. 2018, 2018.Google ScholarGoogle Scholar
  13. F. Tian, X. Long, and W. Liao, "Design of Smart home System Based on Basic Radio Frequency Wireless Sensor Network," International Journal of Online and Biomedical Engineering (iJOE), vol. 14, pp. 126--136, 2018.Google ScholarGoogle ScholarCross RefCross Ref
  14. R. A. Alhanani, J. Abouchabaka, and R. Najat, "CDS-MIP: CDS-based Multiple Itineraries Planning for mobile agents in a wireless sensor network," International Journal of Communication Networks and Information Security, vol. 11, pp. 202--211, 2019.Google ScholarGoogle Scholar
  15. N. Mittal, U. Singh, R. Salgotra, and M. Bansal, "An energy-efficient stable clustering approach using fuzzy-enhanced flower pollination algorithm for WSNs," Neural Computing and Applications, pp. 1--21, 2019.Google ScholarGoogle Scholar
  16. M. Jeelani, S. Kumar, and A. Zafar, "Trust Based Approaches of Intrusion Detection Architecture for Wireless Sensor Networks: A Survey," International Journal of Advanced Research in Computer and Communication Engineering, vol. 7, pp. 107--114, 2018.Google ScholarGoogle ScholarCross RefCross Ref
  17. T. SujeethaDevi and L. Bhagyalakshmi, "Cluster based energy efficien joint routing algorithm for delay minimization in wireless sensor networks," International Journal of Pure and Applied Mathematics, vol. 119, pp. 307--313, 2018.Google ScholarGoogle Scholar
  18. H. Mohapatra and A. K. Rath, "Fault-tolerant mechanism for wireless sensor network," IET Wireless Sensor Systems, 2019.Google ScholarGoogle Scholar
  19. F. Khan, A. Yahya, M. A. Jan, J. Chuma, Z. Tan, and K. Hussain, "A Quality of Service-Aware Secured Communication Scheme for Internet of Things-Based Networks," Sensors, vol. 19, p. 4321, 2019.Google ScholarGoogle ScholarCross RefCross Ref
  20. F. Yunus, N.-S. N. Ismail, S. H. Ariffin, and S. Syed-Yusof, "A Rate Control Model of MPEG-4 Encoder for Video Transmission over Wireless Sensor Network," International Journal of Communication Networks and Information Security, vol. 11, pp. 42--51, 2019.Google ScholarGoogle Scholar
  21. J. Lu, L. Feng, J. Yang, M. M. Hassan, A. Alelaiwi, and I. Humar, "Artificial agent: The fusion of artificial intelligence and a mobile agent for energy-efficient traffic control in wireless sensor networks," Future Generation Computer Systems, vol. 95, pp. 45--51, 2019.Google ScholarGoogle ScholarCross RefCross Ref
  22. K. Singh, K. Singh, and A. Aziz, "Congestion control in wireless sensor networks by hybrid multi-objective optimization algorithm," Computer Networks, vol. 138, pp. 90--107, 2018.Google ScholarGoogle ScholarCross RefCross Ref
  23. K. Thangaramya, K. Kulothungan, R. Logambigai, M. Selvi, S. Ganapathy, and A. Kannan, "Energy aware cluster and neuro-fuzzy based routing algorithm for wireless sensor networks in IoT," Computer Networks, vol. 151, pp. 211--223, 2019.Google ScholarGoogle ScholarDigital LibraryDigital Library
  24. A. Chhabra, V. Vashishth, A. Khanna, D. K. Sharma, and J. Singh, "An energy efficient routing protocol for wireless internet-of-things sensor networks," arXiv preprint arXiv:1808.01039, 2018.Google ScholarGoogle Scholar
  25. R. S. Krishnan, E. G. Julie, Y. H. Robinson, R. Kumar, M. Abdel-Basset, and P. H. Thong, "A new algorithm for high power node multicasting in wireless sensor networks," IEEE Access, vol. 7, pp. 38584--38592, 2019.Google ScholarGoogle ScholarCross RefCross Ref
  26. J. Bhola, S. Soni, and G. K. Cheema, "Genetic algorithm based optimized leach protocol for energy efficient wireless sensor networks," Journal of Ambient Intelligence and Humanized Computing, vol. 11, pp. 1281--1288, 2020.Google ScholarGoogle ScholarCross RefCross Ref
  27. A. H. Sodhro, Z. Luo, G. H. Sodhro, M. Muzamal, J. J. Rodrigues, and V. H. C. de Albuquerque, "Artificial Intelligence based QoS optimization for multimedia communication in IoV systems," Future Generation Computer Systems, vol. 95, pp. 667--680, 2019.Google ScholarGoogle ScholarDigital LibraryDigital Library
  28. M. I. Alipio, A. G. A. Co, M F. C. Hilario, and C. M. C. Pama, "SDN-Enabled Value-Based Traffic Management Mechanism in Resource-Constrained Sensor Devices," in 2019 International Conference on Information Networking (ICOIN), 2019, pp. 248--253.Google ScholarGoogle ScholarCross RefCross Ref
  29. J. Abdullah, M. Hussien, N. Alduais, M. Husni, and A. Jamil, "Data Reduction Algorithms based on Computational Intelligence for Wireless Sensor Networks Applications," in 2019 IEEE 9th Symposium on Computer Applications & Industrial Electronics (ISCAIE), 2019, pp. 166--171.Google ScholarGoogle Scholar
  30. J. Wang, L. Zuo, J. Shen, B. Li, and S. Lee, "Multiple mobile sink-based routing algorithm for data dissemination in wireless sensor networks," Concurrency and Computation: Practice and Experience, vol. 27, pp. 2656--2667, 2015. Google ScholarGoogle ScholarDigital LibraryDigital Library
  31. J. Song and L.-m. Li, "Packet scheduling algorithms in wireless networks," JOURNAL-CHINA INSTITUTE OF COMMUNICATIONS, vol. 24, pp. 42--48, 2003.Google ScholarGoogle Scholar
  32. D. M. Chiu, M. Kadansky, J. Provino, J. Wesley, H.-P. Bischof, and H. Zhu, "A congestion control algorithm for tree-based reliable multicast protocols," in Proceedings. Twenty-First Annual Joint Conference of the IEEE Computer and Communications Societies, 2002, pp. 1209--1217.Google ScholarGoogle Scholar

Index Terms

  1. Intelligent traffic management algorithm for wireless sensor networks

        Recommendations

        Comments

        Login options

        Check if you have access through your login credentials or your institution to get full access on this article.

        Sign in
        • Published in

          cover image ACM Other conferences
          ICONIC '20: Proceedings of the 2nd International Conference on Intelligent and Innovative Computing Applications
          September 2020
          341 pages
          ISBN:9781450375580
          DOI:10.1145/3415088

          Copyright © 2020 ACM

          Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

          Publisher

          Association for Computing Machinery

          New York, NY, United States

          Publication History

          • Published: 24 September 2020

          Permissions

          Request permissions about this article.

          Request Permissions

          Check for updates

          Qualifiers

          • research-article

          Acceptance Rates

          ICONIC '20 Paper Acceptance Rate45of72submissions,63%Overall Acceptance Rate45of72submissions,63%

        PDF Format

        View or Download as a PDF file.

        PDF

        eReader

        View online with eReader.

        eReader