Article Sidebar

Download
PDF
Statistic
Read Counter : 141 Download : 46

Main Article Content

Abstract

Experimental evaluation is central to MANET research, yet performance claims are often derived from studies that use heterogeneous and inconsistently reported evaluation setups, limiting cross-study comparability, reproducibility, and interpretability. This paper presents a PRISMA-guided systematic review of MANET evaluation practice published between 1 January 2020 and 12 August 2025, using an evidence-mapping and meta-research synthesis approach. Twenty studies were analyzed using a structured extraction template capturing evaluation orientation, experimental platform, mobility and scenario configuration, baseline selection, metric portfolios, and energy modeling practices. Methodological rigor was assessed using explicit indicators for validation reporting, statistical analysis reporting, and reproducibility support, with a derived rigor score summarizing reporting strength across studies and over time. The results provide study-attributed evidence maps and diagnostic summaries that quantify dominant evaluation orientations, heterogeneity in evaluation stacks, and uneven disclosure of reproducibility-critical details. The paper derives a practitioner-oriented checklist that specifies minimum reporting and evaluation design elements needed to support transparent and comparable MANET experiments. Future research should develop and validate community-aligned reporting and benchmarking standards that reduce evaluation-stack ambiguity and strengthen cross-study synthesis in MANET research.  

Keywords

MANET Systematic review PRISMA Evaluation methodology Reproducibility Reporting completeness

Article Details

How to Cite
Ami-Narh, J. T., Agor, A. D., Tanye, H. A. ., Okantey, M. ., Banning, L. A. ., & Oberko, P. S. K. . (2026). MANET studies as experimental artifacts: a PRISMA-guided review of contemporary evaluation orientation, reporting completeness and reproducibility . Future Technology, 5(2), 138–147. Retrieved from https://fupubco.com/futech/article/view/519
Download Citation
Endnote/Zotero/Mendeley (RIS)
BibTeX
Bookmark and Share

References

  1. Camp T, Boleng J, Davies V. A survey of mobility models for ad hoc network research. Wiley Online Library 2002;2:483–502. https://doi.org/10.1002/WCM.72.
  2. Kurkowski S, Camp T, Colagrosso M. MANET simulation studies: the incredibles. Mobile Computing and Communications Review 2005;9:50–61. https://doi.org/10.1145/1096166.1096174.
  3. Al Ajrawi S, Tran B. Mobile wireless ad-hoc network routing protocols comparison for real-time military application. Spatial Information Research 2023 32:1 2023;32:119–29. https://doi.org/10.1007/S41324-023-00535-Z.
  4. Agor AD, Aziale LK, Banaseka FK, Owusu-Agyemang K, Brown SA, Partey BT. Trust and adaptiveness enhancements to PRFDRA for secure metaheuristic path selection in MANETs. Future Technology 2025;5:168–79. https://doi.org/10.55670/fpll.futech.5.1.15.
  5. Agor AD, Ami-Narh JT, Banning LA, Brown SA, Elliot MAA, Tanye HA. Hybridizing Intelligent Water Drops and River Formation Dynamics for Optimal Routing Path Selection with Minimum Energy in MANETs. Journal of Artificial Intelligence and Technology 2025:1–9. https://doi.org/10.37965/JAIT.2025.0575.
  6. Agor AD, Oberko PSK, Dotse SK, Partey BT, Aboagye-Darko D, Tapany EJ. A Descriptive Systematic Review of Contemporary MANET Security Research: Themes, Design Structures, and Reporting Rigor. Future Technology 2026;5:59–70. https://doi.org/10.55670/fpll.futech.5.2.7.
  7. Vitek J, Kalibera T. Repeatability, reproducibility, and rigor in systems research. Proceedings of the ninth ACM international conference on Embedded software, Taipei, Taiwan: ACM; 2011, p. 33–8. https://doi.org/10.1145/2038642.2038650.
  8. Hernandez JA, Colom M. Reproducible research policies and software/data management in scientific computing journals: a survey, discussion, and perspectives. Frontiers in Computer Science 2025;6:1–25. https://doi.org/10.3389/FCOMP.2024.1491823/FULL.
  9. Younis ZA, Abdulazeez AM, Zeebaree SSRM, Zebari RR, Zeebaree DQ. Mobile Ad Hoc Network in Disaster Area Network Scenario; A Review on Routing Protocols. International Journal of Online and Biomedical Engineering 2021;17:49–75. https://doi.org/10.3991/ijoe.v17i03.16039.
  10. Bushnaq OM, Chaaban A, Al-Naffouri TY. The Role of UAV-IoT Networks in Future Wildfire Detection. IEEE Internet of Things Journal 2021;8:16984–99. https://doi.org/10.1109/JIOT.2021.3077593.
  11. Dhall R, Dhongdi S. Review of protocol stack development of flying ad-hoc networks for disaster monitoring applications. Archives of Computational Methods in Engineering 2022;30:37–68. https://doi.org/10.1007/s11831-022-09791-y.
  12. Paredes WD, Kaushal H, Vakilinia I, Prodanoff Z. Lora technology in flying ad hoc networks: A survey of challenges and open issues. Sensors 2023;23:1–25. https://doi.org/10.3390/s23052403.
  13. Quy VK, Nam VH, Linh DM, Ban NT, Han ND. Communication Solutions for Vehicle Ad-hoc Network in Smart Cities Environment: A Comprehensive Survey. Wireless Personal Communications 2022;122:2791–815. https://doi.org/10.1007/s11277-021-09030-w.
  14. Quy VK, Nam VH, Linh DM, Ngoc LA. Routing Algorithms for MANET-IoT Networks: A Comprehensive Survey. Wireless Personal Communications 2022;125:3501–25. https://doi.org/10.1007/s11277-022-09722-x.
  15. Alqarni MA. Secure UAV adhoc network with blockchain technology. PLOS ONE 2024;19:e0302513. https://doi.org/10.1371/JOURNAL.PONE.0302513.
  16. Kumar S, Tiwari A, Ahirwar Y, Kumar G, Arafat MY. The Rise of UAV-Based Smart Surveillance: A Systematic Review of Trends and Technologies. IEEE Access 2025;13:181553–75. https://doi.org/10.1109/ACCESS.2025.3621736.
  17. Younes O. Modelling and performance analysis of mobile ad hoc networks. New Castle University, 2013.
  18. Dube P, Walingo T. Performance analysis of an adaptive OFDMA-based CSMA/CA scheme on a wireless network. IET Communications 2020;14:3480–9. https://doi.org/10.1049/IET-COM.2019.1078.
  19. Boukerche A, Turgut B, Aydin N, Ahmad MZ, Bölöni L, Turgut D. Routing protocols in ad hoc networks: A survey. Computer Networks 2011;55:3032–80. https://doi.org/10.1016/J.COMNET.2011.05.010.
  20. Liu J, Singh S. ATCP: TCP for mobile ad hoc networks. IEEE Journal on Selected Areas in Communications 2001;19:1300–15. https://doi.org/10.1109/49.932698.
  21. Zhai H, Chen X, Fang Y. Improving transport layer performance in multihop ad hoc networks by exploiting MAC layer information. IEEE Transactions on Wireless Communications, vol. 6, IEEE; 2007, p. 1692–701. https://doi.org/10.1109/TWC.2007.360371.
  22. Agor AD, Asante M, Hayfron-Acquah JB, Ami-Narh JT, Aziale LK, Peasah KO. A power-aware river formation dynamics routing algorithm for enhanced longevity in MANETs. International Journal of Computer Networks and Applications 2024;11:274–89. https://doi.org/10.22247/ijcna/2024/17.
  23. Agor AD, Asante M, Hayfron-Acquah JB, Peasah KO, Agangiba M, Elliot MAA, et al. Power-aware intelligent water drops routing algorithm for best path selection in MANETs. International Journal of Communication Networks and Information Security 2024;16:1–13.
  24. Goswami C, Shieh C, Chakrabarti P. Energy-aware power and rate control in MANETs using adaptive game theory and grey wolf optimization. Future Technology 2025;04:29–44. https://doi.org/10.55670/fpll.futech.4.3.4.
  25. Hasan N, Mishra A, Ray AK. Fuzzy logic based cross-layer design to improve Quality of Service in Mobile ad-hoc networks for Next-gen Cyber Physical System. Engineering Science and Technology, an International Journal 2022;35:101099. https://doi.org/10.1016/J.JESTCH.2022.101099.
  26. Malyadri N, Ramakrishna M, Nandalike R, Chavan P, Supreeth S, Dayananda P, et al. A predictive energy-efficient adaptive routing methodology for Mobile Ad hoc Networks. The Institute of Engineering and Technology Networks 2025;14:1–16. https://doi.org/10.1049/ntw2.70001.
  27. Sudha MN, Balamurugan V, Lai WC, Divakarachari PB. Sustainable Multipath Routing for Improving Cross-Layer Performance in MANET Using an Energy Centric Tunicate Swarm Algorithm. Sustainability 2022, Vol 14, Page 13925 2022;14:13925. https://doi.org/10.3390/SU142113925.
  28. Chandravanshi K, Soni G, Mishra DK. Design and Analysis of an Energy-Efficient Load Balancing and Bandwidth Aware Adaptive Multipath N-Channel Routing Approach in MANET. IEEE Access 2022;10:110003–25. https://doi.org/10.1109/ACCESS.2022.3213051.
  29. Rajeshkumar G, Kumar MV, Kumar KS, Bhatia S, Mashat A, Dadheech P. An Improved Multi-Objective Particle Swarm Optimization Routing on MANET. Computer Systems Science and Engineering 2023;44:1187–200. https://doi.org/10.32604/csse.2023.026137.
  30. Nagarajan G, Simpson S V., Venkatachalam K, Alrasheedi AF, Askar SS, Abouhawwash M, et al. A Novel Edge-Based Trust Management System for the Smart City Environment Using Eigenvector Analysis. Journal of Healthcare Engineering 2022;2022:5625897. https://doi.org/10.1155/2022/5625897.
  31. Patil M, Umate R, Chawhan M, Madankar A, Neole B. Energy efficient adaptive clustering with QoS-aware CBRP and grey wolf optimization clustering algorithm for mobile ad-hoc network (MANET). Discover Computing 2025;2025:1–44. https://doi.org/10.1007/s10791-025-09685-0.
  32. Rehman A, Haseeb K, Kolivand H, Saba T, Al-Khasawneh MA, Ahmad S, et al. Immersive Embedded Consumer Model Leveraging AI with Zero-Trust Architecture for Cyber-Physical System. IEEE Transactions of Computer Electronics 2025. https://doi.org/10.1109/TCE.2025.3554095.
  33. Haridas S, Rama Prasath A. Bi-fitness swarm optimizer: Blockchain assisted secure swarm intelligence routing protocol for manet. Indian Journal of Computer Science and Engineering 2021;12:1442–58. https://doi.org/10.21817/indjcse/2021/v12i5/211205158.
  34. Veeraiah N, Alotaibi Y, Alghamdi S, Thatavarti S. A novel gradient boosted energy optimization model (GBEOM) for MANET. Computer Systems and Engineering 2023;46:637–57. https://doi.org/10.32604/csse.2023.034224.
  35. Gopala Krishnan C, Nishan AH, Gomathi S, Aravind Swaminathan G. Energy and Trust Management Framework for MANET using Clustering Algorithm. Wireless Personal Communications 2022;122:1267–81. https://doi.org/10.1007/S11277-021-08948-5/METRICS.
  36. Yilmaz K, Kara R, Katircioglu F. Energy-Efficient Hybrid Adaptive Clustering for Dynamic MANETs. IEEE Access 2025;13:51319–31. https://doi.org/10.1109/ACCESS.2025.3552232.
  37. Hande JY, Sadiwala R. Optimization of energy consumption and routing in MANET using Artificial Neural Network. Journal of Integrated Science and Technology 2024;12:1–7.
  38. Krishnamoorthy VK, Izonin I, Subramanian S, Shandilya SK, Velayutham S, Munichamy TR, et al. Energy Saving Optimization Technique-Based Routing Protocol in Mobile Ad-Hoc Network with IoT Environment. Energies 2023, Vol 16, Page 1385 2023;16:1385. https://doi.org/10.3390/EN16031385.
  39. Kumar RV, Gopal D, Nishok VS, Senthilkumaran B. Hybris-E2: A Novel Routing Protocol for Energy Efficiency and Load Balancing in MANETs. International Journal of Communication Systems 2025;38:e70093. https://doi.org/10.1002/DAC.70093;JOURNAL:JOURNAL:10991131B;PAGE:STRING:ARTICLE/CHAPTER.
  40. Sethi A, Bhandari G. Scalable Optimized Link State Heuristic in Cross-Layering with QoS for NGN. International Journal of Scientific and Technology Research 2020;9:4538–41.
  41. Chen Y, Liu W. MAC Layer Energy Consumption and Routing Protocol Optimization Algorithm for Mobile Ad Hoc Networks. Complexity 2021;2021. https://doi.org/10.1155/2021/6687189.

Most read articles by the same author(s)