Skip to content
2000
  1. Home
  2. A-Z Publications
  3. International Journal of Sensors Wireless Communications and Control
  4. Fast Track Articles
  5. Fast Track Article
image of An Optimized Transmission Mechanism for Mitigating Jamming Attacks in Multi-Hop Wireless Networks

Abstract

Aim

To address the vulnerability of Multi-Hop Wireless Network Systems (MHWNs) to jamming attacks and propose an effective solution to maintain communication integrity and Quality of Service (QoS).

Background

In MHWNs, the open-access nature makes them susceptible to jamming attacks, which disrupt communication by interfering with authenticated nodes in the wireless medium. Existing methods primarily focus on tracking and countering jammers but lack effectiveness in preventing communication disruptions.

Objective

The objective of this study is to introduce a novel algorithm, Optimized Transmission Mechanism (OTM), to mitigate the impact of jamming attacks on MHWNs. OTM aims to optimize node handover and packet routing to bypass jammed areas, ensuring uninterrupted packet transmission and preserving QoS.

Methods

The proposed OTM algorithm determines the optimal transmission route based on radio transmitter location and connection quality. It prioritizes routes with the highest connection quality to maintain QoS even in jammed conditions. Additionally, it incorporates mechanisms for packet redirection away from jammed areas to ensure successful transmission.

Results

Evaluation of the Extended Optimized Transmission Mechanism (EOTM) demonstrates significant improvements in packet delivery performance compared to existing algorithms. The enhanced algorithm effectively mitigates the impact of jamming attacks, ensuring reliable communication and preserving QoS in MHWNs.

Conclusion

The proposed OTM algorithm presents a promising approach to counter-jamming attacks in MHWNs by dynamically routing packets to avoid jammed areas and maintain communication integrity. The results highlight the effectiveness of EOTM in improving packet delivery performance and ensuring uninterrupted communication in the face of jamming threats.

© 2024 Bentham Science Publishers
Loading

Article metrics loading...

/content/journals/swcc/10.2174/0122103279296253240919060429
2024-12-26
2025-01-31

  • From This Site

    /content/journals/swcc/10.2174/0122103279296253240919060429
    dcterms_title,dcterms_subject,pub_keyword
    -contentType:Contributor -contentType:Concept -contentType:Institution
    10
    5
Loading full text...

Full text loading...

References

  1. Wang T. Wei X. Hu F. Fan J. Mobile jammer localization and tracking in multi-hop wireless network. J. Ambient Intell. Humaniz. Comput. 2018 15 2 1239 1250 10.1007/s12652‑018‑0708‑4
    [Google Scholar]
  2. He S. Li Q. Khishe M. Salih Mohammed A. Mohammadi H. Mohammadi M. The optimization of nodes clustering and multi-hop routing protocol using hierarchical chimp optimization for sustainable energy efficient underwater wireless sensor networks. Wirel. Netw. 2024 30 1 233 252 10.1007/s11276‑023‑03464‑9
    [Google Scholar]
  3. Wong A.W.L. Goh S.L. Hasan M.K. Fattah S. Multi-hop and mesh for LoRa networks: Recent advancements, issues, and recommended applications. ACM Comput. Surv. 2024 56 6 1 43 10.1145/3638241
    [Google Scholar]
  4. Liu H. Yang Z. Zhao N. Gu Y. Yuen C. Interference-Aware Multi-Hop Routing in UAV Networks: A Harmonic Function-Based Potential Field Approach. IEEE Inter. Things J. 2024 99 1 10.3390/books978‑3‑03928‑606‑5
    [Google Scholar]
  5. Zungeru A.M. Ang L.M. Seng K.P. Classical and swarm intelligence based routing protocols for wireless sensor networks: A survey and comparison. J. Netw. Comput. Appl. 2012 35 5 1508 1536 10.1016/j.jnca.2012.03.004
    [Google Scholar]
  6. Liu H. Yang Z. Zhao N. Gu Y. Yuen C. Interference-Aware Multi-Hop Routing in UAV Networks: A Harmonic Function-Based Potential Field Approach. IEEE Internet Things J. 2024
    [Google Scholar]
  7. Chee-Yee Chong Kumar S.P. Sensor networks: Evolution, opportunities, and challenges. Proc. IEEE 2003 91 8 1247 1256 10.1109/JPROC.2003.814918
    [Google Scholar]
  8. Rault T. Bouabdallah A. Challal Y. Energy efficiency in wireless sensor networks: A top-down survey. Comput. Netw. 2014 67 104 122 10.1016/j.comnet.2014.03.027
    [Google Scholar]
  9. Faheem M. Abbas M.Z. Tuna G. Gungor V.C. EDHRP: Energy efficient event driven hybrid routing protocol for densely deployed wireless sensor networks. J. Netw. Comput. Appl. 2015 58 309 326 10.1016/j.jnca.2015.08.002
    [Google Scholar]
  10. Faheem M. Gungor V.C. Energy efficient and QoS-aware routing protocol for wireless sensor network-based smart grid applications in the context of industry 4.0. Appl. Soft Comput. 2018 68 910 922 10.1016/j.asoc.2017.07.045
    [Google Scholar]
  11. Shah S.B. Zhe C. Yin F. Khan I.U. Begum S. Faheem M. Khan F.A. 3D weighted centroid algorithm & RSSI ranging model strategy for node localization in WSN based on smart devices. Sustain Cities Soc. 2018 39 298 308 10.1016/j.scs.2018.02.022
    [Google Scholar]
  12. Fadel E. Faheem M. Gungor V.C. Nassef L. Akkari N. Malik M.G.A. Almasri S. Akyildiz I.F. Spectrum-aware bio-inspired routing in cognitive radio sensor networks for smart grid applications. Comput. Commun. 2017 101 106 120 10.1016/j.comcom.2016.12.020
    [Google Scholar]
  13. Faheem M. Cagri Gungor V. Capacity and spectrum-aware communication framework for wireless sensor network-based smart grid applications. Comput. Stand. Interfaces 2017 53 48 58 10.1016/j.csi.2017.03.003
    [Google Scholar]
  14. Faheem M. Shah S.B.H. Butt R.A. Raza B. Anwar M. Ashraf M.W. Ngadi M.A. Gungor V.C. Smart grid communication and information technologies in the perspective of Industry 4.0: Opportunities and challenges. Comput. Sci. Rev. 2018 30 1 30 10.1016/j.cosrev.2018.08.001
    [Google Scholar]
  15. Saleem M. Di Caro G.A. Farooq M. Swarm intelligence based routing protocol for wireless sensor networks: Survey and future directions. Inf. Sci. 2011 181 20 4597 4624 10.1016/j.ins.2010.07.005
    [Google Scholar]
  16. Buttyan L. Hubaux J.P. Enforcing service availability in mobile ad-hoc WANs. 2000 First Annual Workshop on Mobile and Ad Hoc Networking and Computing. 11-11 August 2000, Boston, MA, USA, 2000, pp. 87-96. 10.1109/MOBHOC.2000.869216
    [Google Scholar]
  17. MacKenzie A.B. Wicker S.B. Game theory in communications: motivation, explanation, and application to power control. GLOBECOM'01. IEEE Global Telecommunications Conference (Cat. No.01CH37270) 25-29 November 2001, San Antonio, TX, USA, 2001, pp. 821-826. 10.1109/GLOCOM.2001.965533
    [Google Scholar]
  18. Zia M.T. Qureshi F.F. Shah S.S. Energy Efficient Cognitive Radio MAC Protocols for Adhoc Network: A Survey. 2013 UKSim 15th International Conference on Computer Modelling and Simulation 10-12 April 2013, Cambridge, UK, 2013, pp. 140-143. 10.1109/UKSim.2013.96
    [Google Scholar]
  19. Joshi G.P. Acharya S. Kim S.W. A MAC protocol for CR-WSN without a dedicated common control channel. Int. J. Distrib. Sens. Netw. 2015 11 3 982408 10.1155/2015/982408
    [Google Scholar]
  20. Bonnet P. Gehrke J. Seshadri P. “Querying the physical world,” IEEE personal. Communications 2000 7 5 10 15
    [Google Scholar]
  21. Gul O.M. Erkmen A.M. Kantarci B. UAV-driven sustainable and quality-aware data collection in robotic wireless sensor networks. Intern.Things J. 2022 9 24 25150 25164 10.1109/JIOT.2022.3195677
    [Google Scholar]
  22. Gul O.M. Erkmen A.M. Energy-Efficient Cluster-Based Data Collection by a UAV with a Limited-Capacity Battery in Robotic Wireless Sensor Networks. Sensors (Basel) 2020 20 20 5865 10.3390/s20205865 33081344
    [Google Scholar]
  23. Jayalakshmi R. Baranidharan B. Santhi B. Attribute based spanning tree construction for data aggregation in heterogeneous wireless sensor networks. Indian J. Sci. Technol. 2014 7 is5 76 79 10.17485/ijst/2014/v7sp5.18
    [Google Scholar]
  24. Chandrakasan A. Amirtharajah R. Design considerations for distributed microsensor systems. Proceedings of the IEEE 1999 Custom Integrated Circuits Conference (Cat. No.99CH36327) 19-19 May 1999, San Diego, CA, USA, 1999, pp. 279-286. 10.1109/CICC.1999.777291
    [Google Scholar]
  25. Yu S. Zhang B. Li C. Mouftah H. Routing protocols for wireless sensor networks with mobile sinks: a survey. IEEE Commun. Mag. 2014 52 7 150 157 10.1109/MCOM.2014.6852097
    [Google Scholar]
  26. Yan J. Zhou M. Ding Z. Recent advances in energy-efficient routing protocols for wireless sensor networks: A review. IEEE Access 2016 4 5673 5686 10.1109/ACCESS.2016.2598719
    [Google Scholar]
  27. Yetgin H. Cheung K.T.K. El-Hajjar M. Hanzo L. A survey of network lifetime maximization techniques in wireless sensor networks. IEEE Commun. Surv. Tutor. 2017 19 2 828 854 10.1109/COMST.2017.2650979
    [Google Scholar]
  28. Zungeru A.M. Ang L.M. Seng K.P. A formal mathematical framework for modeling and simulation of wireless sensor network environments utilizing the hill-building behavior of termites. Simulation 2013 89 5 589 615 10.1177/0037549712466706
    [Google Scholar]
  29. More A. Raisinghani V. A survey on energy efficient coverage protocols in wireless sensor networks. Journal of King Saud University - Computer and Information Sciences 2017 29 4 428 448 10.1016/j.jksuci.2016.08.001
    [Google Scholar]
  30. Emans B. Additive white Gaussian noise (AWGN). 2012 Available from: wikipedia.org/wiki/Additive_white_Gaussian_noise(accessed on 20-8-2024)
  31. Moreno R. Robles-Gómez A. Bermúdez A. Casado R. SensGrid: modeling and simulation for wireless sensor grids. Simulation 2012 88 8 972 987 10.1177/0037549711434180
    [Google Scholar]
  32. Rawat D.B. Zhao Y. Yan G. Song M. CRAVE: Cognitive radio enabled vehicular communications in heterogeneous networks 2013 IEEE Radio and Wireless Symposium 20-23 January 2013, Austin, TX, USA, 2013, pp. 190-192. 10.1109/RWS.2013.6486684
    [Google Scholar]
  33. Mitola J. Maguire G.Q. Cognitive radio: making software radios more personal. IEEE Personal Commun. 1999 6 4 13 18
    [Google Scholar]
  34. Yang Y. Lambert F. Divan D. A survey on technologies for implementing sensor networks for power delivery systems 2007 IEEE Power Engineering Society General Meeting 24-28 June 2007, Tampa, FL, USA, 2007, pp. 1-8. 10.1109/PES.2007.386289
    [Google Scholar]
  35. Maitra T. Roy S. A comparative study on popular MAC protocols for mixed Wireless Sensor Networks: From implementation viewpoint. Comput. Sci. Rev. 2016 22 107 134 10.1016/j.cosrev.2016.09.004
    [Google Scholar]
  36. Anastasi G. Conti M. Di Francesco M. Passarella A. Energy conservation in wireless sensor networks: A survey. Ad Hoc Netw. 2009 7 3 537 568 10.1016/j.adhoc.2008.06.003
    [Google Scholar]
  37. Akyildiz I.F. Weilian Su Sankarasubramaniam Y. Cayirci E. A survey on sensor networks. IEEE Commun. Mag. 2002 40 8 102 114 10.1109/MCOM.2002.1024422
    [Google Scholar]
  38. Ye W. Heidemann J. Estrin D. An energy-efficient MAC protocol for wireless sensor networks 2002
    [Google Scholar]
  39. Polastre J. Hill J. Culler D. Versatile low power media access for wireless sensor networks Proceedings of the 2nd international conference on Embedded networked sensor systems November 3-5, 2004, Baltimore, USA, pp. 95-107. 10.1145/1031495.1031508
    [Google Scholar]
  40. Liu Z. Liu H. Xu W. Chen Y. Wireless jamming localization by exploiting nodes’ hearing ranges International Conference on Distributed Computing in Sensor Systems Berlin, Heidelberg, pp. 348-361. 10.1007/978‑3‑642‑13651‑1_25
    [Google Scholar]
  41. 2019 Available from:https://en.wikipedia.org/wiki/Friis(accessed on 20-8-2024)
  42. Johnson D.B. Maltz D.A. Broch J. DSR: The dynamic source routing protocol for multi-hop wireless ad hoc networks. Ad Hoc Netw. 2001 5 1 139 172
    [Google Scholar]
  43. Royer E.M. Perkins C.E. Ad-hoc on-demand distance vector routing. Proceedings of the 2nd IEEE Workshop on Mobile Computing Systems and Applications 25-26 February 1999, New Orleans, LA, USA, 1999, pp. 90-100.
    [Google Scholar]
  44. Leung R. Liu J. MP-DSR: a QoS-aware multi-path dynamic source routing protocol for wireless ad-hoc networks 26th Annual IEEE Conference on Local Computer Networks 14-16 November 2001, Tampa, FL, USA, 2001, pp. 132-141. 10.1109/LCN.2001.990778
    [Google Scholar]
/content/journals/swcc/10.2174/0122103279296253240919060429
Loading
An Optimized Transmission Mechanism for Mitigating Jamming Attacks in Multi-Hop Wireless Networks
Bentham Science Publishers ; https://doi.org/10.2174/0122103279296253240919060429
/content/journals/swcc/10.2174/0122103279296253240919060429
/content/journals/swcc/10.2174/0122103279296253240919060429
Loading

Data & Media loading...


  • Article Type:     Research Article
Keywords: Quality of Service (QoS) ; jamming Attacks ; Multi-Hop Wireless Networks (MHWNs) ; HHacket reouting ; Optimized Transmission Mechanism (OTM) ; denial-of-service (DoS) Attacks ; communication integrity ; node handover

Most Cited Most Cited RSS feed

This is a required field
Please enter a valid email address
Approval was a Success
Invalid data
An Error Occurred
Approval was partially successful, following selected items could not be processed due to error
Please enter a valid_number test