Skip to main content
SpringerLink
Log in

Red Deer algorithm based social trust based congestion control in ad hoc social networks

  • Published:
Applied Intelligence Aims and scope Submit manuscript

Abstract

An ad hoc social network (ASNET) explores social connectivity among users of mobile devices which is becoming a main essential forms of internet today. In this ASNET, the security and congestion control is considered as the main issues which degrades the performance of the system. Conventional congestion control and security enhancement methods of ASNETs are do not behave properly in congestion environments and attack conditions. To address this issue, a priority with congestion control based hybrid algorithm with security technique is proposed and designed. The proposed scheduling algorithm exploits the social popularity of sensor nodes to prioritize complete incoming flows which completely reduce the congestion problems in the system. Trap door protocol and Zero knowledge proof protocols are combined which are used to improve the security of the ASNETs networks. Two main objective functions are considered to improve the performance of the network such as congestion control and security enhancement. The congestion control is achieved by optimal scheduling scheme which is attained by applying proposed Red Deer Algorithm (RDA). The proposed method is executed by MATLAB simulator and performances are compared with existing methods such as Atom Search Optimization (ASO), Emperor Penguin Optimization (EPO), Firefly Algorithm (FA), and Particle Swarm Optimization (PSO) algorithm respectively. The performance metrics are delay, drop, throughput, energy consumption, network lifetime, over-head and delivery ratio are determined and compared with the proposed method.

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
Fig. 12
Fig. 13
Fig. 14
Fig. 15

Similar content being viewed by others

References

  1. Sharma V, Kumar M (2017) Adaptive congestion control scheme in mobile ad-hoc networks. Peer-to-Peer Network Appl 10(3):633–657. https://doi.org/10.1007/s12083-016-0507-7

    Article  Google Scholar 

  2. Liu Y, Wang K, Guo H, Lu Q, Sun Y (2017) Social-aware computing based congestion control in delay tolerant networks. Mobile Networks Appl 22(2):174–185. https://doi.org/10.1007/s11036-016-0759-8

    Article  Google Scholar 

  3. Li L, Wang W, Gao Z (2020) Driver’s social relationship based clustering and transmission in vehicle ad hoc networks (VANETs). Electronics 9(2):298. https://doi.org/10.3390/electronics9020298

    Article  Google Scholar 

  4. Arif M (2020) Wang G, (2020) cloud-based service oriented architecture for social vehicular ad hoc network communications. Int J Comm Networks Distributed Syst 24(2):143–166. https://doi.org/10.1504/IJCNDS.2020.104746

    Article  Google Scholar 

  5. Zhou Y, Shi Y, Chen S (2020) Capacity and delay analysis for large social-aware Mobile ad hoc wireless networks. Appl Sci (Switzerland) 10(5):1719. https://doi.org/10.3390/app10051719

    Article  Google Scholar 

  6. Gulati N, Kaur P (2020) A game theoretic approach for conflict resolution in argumentation enabled social IoT networks. Ad Hoc Netw 107:102222. https://doi.org/10.1016/j.adhoc.2020.102222

    Article  Google Scholar 

  7. Liaqat H, Ali A, Qadir J, Bashir A, Bilal M, Majeed F (2019) Socially-aware congestion control in ad-hoc networks: current status and the way forward. Futur Gener Comput Syst 97:634–660. https://doi.org/10.1016/j.future.2019.02.017

    Article  Google Scholar 

  8. Oubbati O, Atiquzzaman M, Lorenz P, Tareque M, Hossain M (2019) Routing in flying ad hoc networks: survey, constraints, and future challenge perspectives. IEEE Access 7:81057–81105. https://doi.org/10.1109/ACCESS.2019.2923840

    Article  Google Scholar 

  9. Guo M, Xiao M (2019) MSSN: an attribute-aware transmission algorithm exploiting node similarity for opportunistic social networks. Information (Switzerland) 10(10):299. https://doi.org/10.3390/info10100299

    Article  Google Scholar 

  10. Wu J, Chen Z, Zhao M (2019) Information cache management and data transmission algorithm in opportunistic social networks. Wirel Netw 25(6):2977–2988. https://doi.org/10.1007/s11276-018-1691-6

    Article  Google Scholar 

  11. Mohaisen A, Tran H, Chandra A, Kim Y (2013) Trustworthy distributed computing on social networks. IEEE Trans Serv Comput 7(3):333–345. https://doi.org/10.1109/TSC.2013.56

    Article  Google Scholar 

  12. Liaqat H, Yang Q, Ahmed A, Xu Z, Qiu T, Xia F (2014) A social popularity aware scheduling algorithm for ad-hoc social networks. In 2014 11th international joint conference on computer science and software engineering: "human factors in computer science and software engineering" - e-science and high performance computing: eHPC. JCSSE 2014:28–33. https://doi.org/10.1109/JCSSE.2014.6841837

    Article  Google Scholar 

  13. Xiao M, Wu J, Huang L, Cheng R, Wang Y (2016) Online task assignment for crowdsensing in predictable mobile social networks. IEEE Trans Mob Comput 16(8):2306–2320. https://doi.org/10.1109/TMC.2016.2616473

    Article  Google Scholar 

  14. Bhoi U, Ramanuj P (2013) Enhanced max-min task scheduling algorithm in cloud computing. Int J Appl Innov Eng Manag (IJAIEM) 2(4):259–264

    Google Scholar 

  15. Li J, Peng J, Cao X, Li H (2011) A task scheduling algorithm based on improved ant colony optimization in cloud computing environment. Energy Procedia 13:6833–6840. https://doi.org/10.1016/j.egypro.2011.12.386

    Article  Google Scholar 

  16. Zhu J, Jiang X, Yu Y, Jin G, Chen H, Li X, Qu L (2020) An efficient priority-driven congestion control algorithm for data center networks. China. Communications 17(6):37–50. https://doi.org/10.23919/JCC.2020.06.004

    Article  Google Scholar 

  17. Wang N, Huang S, Peng Y, Wang G (2020) A routing strategy with energy optimisation based on community in mobile social networks. Int J Comput Sci Eng 21(2):234–248. https://doi.org/10.1504/ijcse.2020.10027431

    Article  Google Scholar 

  18. Liaqat H, Xia F, Ma J, Yang L, Ahmed A (2015) Asabere N, (2015) social-similarity-aware TCP with collision avoidance in ad hoc social networks. IEEE Syst J 9(4):1273–1284. https://doi.org/10.1109/JSYST.2014.2305191

    Article  Google Scholar 

  19. Zhuang W, Chen M, Wei X, Li H (2020) Social-aware resource allocation based on cluster formation and matching theory in D2D Underlaying cellular networks. KSII Trans Int Inform Syst 14(5):1984–2002. https://doi.org/10.3837/tiis.2020.05.007

    Article  Google Scholar 

  20. Xi Y, Yeh E (2008) Node-based optimal power control, routing, and congestion control in wireless networks. IEEE Trans Inf Theory 54(9):4081–4106. https://doi.org/10.1109/TIT.2008.928299

    Article  MathSciNet  MATH  Google Scholar 

  21. Xia F, Liaqat H, Ahmed A, Liu L, Ma J, Huang R, Tolba A (2016) User popularity-based packet scheduling for congestion control in ad-hoc social networks. J Comput Syst Sci 82(1):93–112. https://doi.org/10.1016/j.jcss.2015.07.002

    Article  MathSciNet  Google Scholar 

  22. Wu D, Liu B, Yang Q, Wang R (2020) Social-aware cooperative caching mechanism in mobile social networks. J Netw Comput Appl 149:102457. https://doi.org/10.1016/j.jnca.2019.102457

    Article  Google Scholar 

  23. Major W, Buchanan W, Ahmad J (2020) An authentication protocol based on chaos and zero knowledge proof. Nonlinear Dynamics 99(4):3065–3087. https://doi.org/10.1007/s11071-020-05463-3

    Article  Google Scholar 

  24. Fathollahi-Fard A, Hajiaghaei-Keshteli M, Tavakkoli-Moghaddam R (2020) Red deer algorithm (RDA): a new nature-inspired meta-heuristic. Soft Computing, Soft Computing 24(19):14637–14665. https://doi.org/10.1007/s00500-020-04812-z

    Article  Google Scholar 

  25. Fathollahi-Fard A, Ahmadi A, Sajadieh M, (2020) An efficient modified Red Deer algorithm to solve a truck scheduling problem considering time windows and deadline for Trucks' departure. Evolutionary computation in scheduling, 137-167, https://doi.org/10.1002/9781119574293.ch6

  26. Zhao W, Wang L, Zhang Z (2019) Atom search optimization and its application to solve a hydrogeologic parameter estimation problem. Knowl-Based Syst 163:283–304. https://doi.org/10.1016/j.knosys.2018.08.030

    Article  Google Scholar 

  27. Dhiman G, Kumar V (2018) Emperor penguin optimizer: a bio-inspired algorithm for engineering problems. Knowl-Based Syst 159:20–50. https://doi.org/10.1016/j.knosys.2018.06.001

    Article  Google Scholar 

  28. Song P, Chu S, Pan J, Yang H (2020) Phasmatodea population evolution algorithm and its application in length-changeable incremental extreme learning machine. In proceedings of 2nd international conference on industrial artificial intelligence (IAI). https://doi.org/10.1109/IAI50351.2020.9262236

  29. Meng Z, Pan J, Xu H (2016) QUasi-affine TRansformation evolutionary (QUATRE) algorithm: a cooperative swarm based algorithm for global optimization. Knowl-Based Syst 109:104–121. https://doi.org/10.1016/j.knosys.2016.06.029

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. PSNA College of Engineering and Technology, Dindigul, TamilNadu, India

    S. Pushpalatha

  2. PSNA College of Engineering and Technology, Dindigul, TamilNadu, India

    T. Hemalatha

Authors
  1. S. Pushpalatha
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. T. Hemalatha
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to S. Pushpalatha.

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

Pushpalatha, S., Hemalatha, T. Red Deer algorithm based social trust based congestion control in ad hoc social networks. Appl Intell 52, 17668–17683 (2022). https://doi.org/10.1007/s10489-022-03265-1

Download citation

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s10489-022-03265-1

Keywords

Search

Navigation