Skip to main content
SpringerLink
Log in

MMF Clustering: A On-demand One-hop Cluster Management in MANET Services Executing Perspective

  • Published:
Wireless Personal Communications Aims and scope Submit manuscript

Abstract

Mobile Ad-hoc Network (MANET) consists of a group of mobile nodes that communicate without any infrastructure. The dynamic nature and intrinsic complexity of MANET have made it a network with high topological variability. It is highly desirable to find methods that bring this complexity under control quickly. Controlling this complexity makes communication between nodes more durable, resource utilization more efficient, and the quality of required services from the environment higher. Since clustering is one of the most common methods for overcoming flat structures with many nodes, researchers have always looked for practical algorithms for clustering in MANET. Therefore, in this research, an attempt has been made to provide a method for clustering nodes in this environment to make the clusters more stable. To achieve more stable clusters, parameters for header selection are considered that reduce the need to change the header in each cluster. Also, in addition to creating new clusters if necessary, by constantly monitoring the performance of existing clusters, as far as possible, these clusters are reorganized and reconfigured to have more stable clusters in the environment. The simulation results show that creating more stable clusters in MANET leads to more efficient node resources and higher service quality than existing methods.

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

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

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

Availability of data and materials

The datasets used and analyzed during the current study are available from the corresponding author on reasonable request.

References

  1. Cooper, C. (2012). Apples cook: 172 million post-PC devices in the last year,'' CNET, New York, NY, USA, Tech. Rep., Mar.

  2. Ashwin, M., Kamalraj, S., & Azath, M. (2016). Weighted clustering trust model for mobile Ad Hoc networks. Wireless Personal Communication, 94(4), 1–10.

    Google Scholar 

  3. Chen, I. R., & Guo, J. (2015). Hierarchical trust management of community of interest groups in mobile ad hoc networks. Ad Hoc Networks, 33, 154–167.

    Article  Google Scholar 

  4. Xu, L., Wang, J., Liu, Y., Shi, W., & Gulliver, T. A. (2018). Outage performance for IDF relaying mobile cooperative networks. Mobile Networks & Applications, 23(6), 1496–1501.

    Article  Google Scholar 

  5. Tarique, M., Tepe, K. E., Adibi, S., & Erfani, Sh. (2009). Survey of multipath routing protocols for mobile ad hoc networks. Journal of Network and Computer Applications, 32(6), 1125–1143.

    Article  Google Scholar 

  6. Waluyo, A. B., Taniar, D., Rahayu, W., & Srinivasan, B. (2017). Trustworthy data delivery in mobile P2P network. Journal of Computer and System Sciences, 86, 33–48.

    Article  MathSciNet  Google Scholar 

  7. Bhardwaj, A., Al-Turjman, F., Kumar, M., Stephan, T., & Mostarda, L. (2020). Capturing-the-invisible (CTI): behavior-based attacks recognition in iot-oriented industrial control systems. IEEE Access, 8, 104956–104966.

    Article  Google Scholar 

  8. Singh, A. K., Alshehri, M., Bhushan, S., Kumar, M., Alfarraj, O., & Pardarshani, K. R. (2021). Secure and energy efficient data transmission model for WSN. Intelligent Automation & Soft Computing, 27(3), 761–769.

    Article  Google Scholar 

  9. Waluyo, A. B., Taniar, D., Rahayu, W., Aikebaier, A., Takizawa, M., & Srinivasan, B. (2013). Mobile peer-to-peer data dissemination in wireless ad-hoc networks. Information Sciences, 230, 3–20.

    Article  MathSciNet  Google Scholar 

  10. IEEE 802.15 Working Group for WPAN. (2011). from http://www.ieee802.org/15/.

  11. Wireless LAN Medium Access Control (MAC) and Physical Layer (PHY) Specifications (2007). IEEE Standard 802.11, IEEE Computer Society.

  12. Ryu, JH., Song, S., Cho, DH. (2001). New clustering schemes for energy conservation in two-tiered mobile ad-hoc networks. ICC 2001 IEEE International Conference on Communications, 862_866.

  13. Lacuesta, R., Penalver, L., Fernandez-Sanz, L., Lloret, j., Garcia, M. (2009). Software Requirements for Ubiquitous Ad Hoc Mobile Networks: An Example of a Bluetooth Application. International Conference on Software Engineering Advances. IEEE, 179–184.

  14. Arunachalam, A., & Sornil, O. (2015). Issues of implementing random walk and gossip based resource discovery protocols in P2P MANETs & suggestions for improvement. Procedia Computer Science, 57, 509–518.

    Article  Google Scholar 

  15. Sarma, A. D., Molla, A. R., & Pandurangan, G. (2015). Efficient random walk sampling in distributed networks. Journal of Parallel and Distributed Computing, 77, 84–94.

    Article  Google Scholar 

  16. Pu, I. M., Stamate, D., & Shen, Y. (2014). Improving time-efficiency in blocking expanding ring search for mobile ad hoc networks. Journal of Discrete Algorithms, 24, 59–67.

    Article  MathSciNet  Google Scholar 

  17. Xu, D., Nahrstedt, K., Wichadakul, D. (2001). QoS-Aware Discovery of Wide-Area Distributed Services. Proceedings First IEEE/ACM International Symposium on CLUSTER Computing and the Grid, 92–99.

  18. Liang, J. C., Chen, J. C., & Zhang, T. (2011). An adaptive low-overhead resource discovery protocol for mobile ad-hoc networks. Wireless Networks, 17(2), 437–452.

    Article  Google Scholar 

  19. Hongyan, M., Yujie, Z., Xiangwu, M. (2014). A path tracking search algorithm based on the credibility of node service ability. IEEE Conference on Wireless Communications and Networking, 3385– 3389.

  20. Liu, H., & Zhang, X. (2017). Efficient resource search mechanism in selfish mobile peer-to-peer network. Journal of system simulation, 29(5), 1093–1102.

    Google Scholar 

  21. Mondal, A., Madria, SK., Kitsuregawa, M. (2006). CLEAR: An Efficient Context and Location-Based Dynamic Replication Scheme for Mobile-P2P Networks. 17th International Conference on Database and Expert Systems Applications, Springer-Verlag, 399–408.

  22. Kantere, V., Tsoumakos, D., Sellis, T., & Roussopoulos, N. (2009). GrouPeer: dynamic clustering of P2P databases. Information Systems, 34(1), 62–86.

    Article  Google Scholar 

  23. Seddiki, M., & Benchaïba, M. (2016). 2P-lookup: popularity and proximity based P2P lookup mechanism over MANETs. Journal of Network and Computer Applications, 71, 181–193.

    Article  Google Scholar 

  24. Gupta, P., & Kumar, P. R. (2000). The capacity of wireless networks. IEEE Transactions on Information Theory, 46(2), 388–404.

    Article  MathSciNet  Google Scholar 

  25. Hong, X., Xu, K., & Gerla, M. (2002). Scalable routing protocols for mobile ad hoc networks. IEEE Network, 16(4), 11–21.

    Article  Google Scholar 

  26. Xu, K., Hong, X., Gerla, M., (2002). An ad hoc network with mobile backbones. IEEE International Conference on Communications (ICC), 3138_3143.

  27. Belding-Royer, E. M. (2002). Hierarchical routing in ad hoc mobile networks. Wireless Communications and Mobile Computing, 2(5), 515–532.

    Article  Google Scholar 

  28. Perkins, CE., (2001). Ad Hoc Networking. Reading, MA, USA, Addison-Wesley.

  29. Basagni, S., Chlamtac, I., (1997). A Generalized Clustering Algorithm for Peer-to-Peer Networks. in Workshop Algorithmic Aspects of Communication, 1–15.

  30. Ergenç, D., Eksert, L., & Onur, E. (2019). Dependability-based clustering in mobile Ad-Hoc networks. Ad Hoc Networks, 93, 101926.

    Article  Google Scholar 

  31. Yang, Z., Wu, W., Chen, Y., Lin, X., Chen, X., (2018). Navigation Route Based Stable Clustering for Vehicular Ad Hoc Networks. International Conference on Communications and Networking in China, 552–562.

  32. Han, T., Zhang, L., Pirbhulal, S., Wu, W., & de Albuquerque, V. H. C. (2019). A novel cluster head selection technique for edge-computing based IoMT systems. Computer Networks, 158, 114–122.

    Article  Google Scholar 

  33. Chaudhry, Ch., & Tapaswi, Sh. (2018). Optimized power control and efficient energy conservation for topology management of MANET with an adaptive Gabriel graph. Computers & Electrical Engineering, 72, 1021–1036.

    Article  Google Scholar 

  34. Nabar, K., & Kadambi, G. (2018). Affinity propagation-driven Distributed clustering approach to tackle greedy heuristics in mobile Ad-hoc networks. Computers and Electrical Engineering, 71, 988–1011.

    Article  Google Scholar 

  35. Bhushan, Sh., Kumar, M., Kumar, P., Stephan, Th., Shankar, A., & Liu, P. (2021). FAJIT: a fuzzy-based data aggregation technique for energy efficiency in wireless sensor network. Complex & Intelligent Systems, 7, 997–1007.

    Article  Google Scholar 

  36. Rao, M., & Singh, N. (2018). Energy efficient QoS aware hierarchical KF-MAC routing protocol in manet. Wireless Personal Communications, 101(2), 635–645.

    Article  Google Scholar 

  37. Ahmad, M., Hameed, A., Ullah, F., Wahid, I., Rehman, S. U., & Khattak, H. A. (2018). A bio-inspired clustring in mobile adhoc networks for internet of things based on honey bee and genetic algorithm. Journal of Ambient Intelligence and Humanized Computing, 11, 4347–4361.

    Article  Google Scholar 

  38. Meng, X., & Deng, Y. (2019). A time-aware resource search strategy with the ant colony optimization in MANETs. Peer-to-Peer Networking and Applications, 12(5), 1013–1027.

    Article  Google Scholar 

  39. Chithaluru, P., Al-Turjman, F., Kumar, M., & Stephan, Th. (2020). I-AREOR: An energy-balanced clustering protocol for implementing green IoT in smart cities. Sustainable Cities and Society, 61(8), 102254.

    Article  Google Scholar 

  40. Srivastava, Sh., Saxena, S., Buyya, R., Kumar, M., Shankar, A., & Bhushan, B. (2021). CGP: Cluster-based gossip protocol for dynamic resource environment in cloud. Simulation Modelling Practice and Theory, 108, 102275.

    Article  Google Scholar 

  41. Das, S., Chatterjee, M., & Turgut, D. (2002). WCA: a weighted clustering algorithm for mobile Ad Hoc networks. Cluster Computing., 5(2), 193–204.

    Article  Google Scholar 

Download references

Acknowledgements

The authors are grateful to all study participants.

Funding

This research received no specific grant from any funding agency in the public, commercial, or not-for-profit sectors.

Author information

Authors and Affiliations

  1. Department of Computer Engineering and Information Technology, Payame Noor University, Tehran, Iran

    Reza Sookhtsaraei & Mohammad Saber Iraji

  2. Department of Computer Engineering, Allameh Mohaddes Nouri University, Noor, Iran

    Mohsen Nejadkheirallah

  3. Department of Computer Engineering, University of Tabriz, Tabriz, Iran

    Mohammad Saber Iraji

Authors
  1. Reza Sookhtsaraei
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Mohsen Nejadkheirallah
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Mohammad Saber Iraji
    View author publications

    You can also search for this author in PubMed Google Scholar

Contributions

Iraji and sokhtsaraei suggested the algorithm for image analysis; sokhtsaraei implemented it and analyzed the experimental results; Tanha provided clinical guidance; Iraji, sokhtsaraei, and Nejadkheirallah consulted the obtained result. All authors read and approved the final manuscript.

Corresponding author

Correspondence to Mohammad Saber Iraji.

Ethics declarations

Conflicts of interest

The authors declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Ethical Approval

This article does not contain any data, or other information from studies or experimentation, with the involvement of human or animal subjects.

Consent for Publication

Agreed by the authors.

Additional information

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Sookhtsaraei, R., Nejadkheirallah, M. & Iraji, M.S. MMF Clustering: A On-demand One-hop Cluster Management in MANET Services Executing Perspective. Wireless Pers Commun 125, 1973–2002 (2022). https://doi.org/10.1007/s11277-022-09643-9

Download citation

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11277-022-09643-9

Keywords

Search

Navigation