Journal of Computing and Natural Science

Assessing the Viability of Performance Evaluation Methods in Network Research

Journal of Computing and Natural Science

Received On : 25 December 2022

Revised On : 30 April 2023

Accepted On : 30 July 2023

Published On : 05 January 2024

Volume 04, Issue 01

Pages : 020-030


Ad-hoc networks are to networks that are spontaneously and temporarily established without requiring any pre-existing infrastructure. These networks are often characterized by self-organization and may be spontaneously established to simplify communication across devices. Wireless Sensor Networks (WSNs) consist of diminutive, energy-efficient devices known as sensors, which are strategically placed in different settings to gather and send data without the need for physical connections. WSNs are often used for the purpose of monitoring and collecting data from the surrounding environment. This study focuses on the assessment of performance in network research, especially in the domains of Ad-Hoc and WSN. The analysis focuses on papers from renowned conferences in various domains and scrutinizes the validation methodologies used by authors. Simulations are the predominant approach used for performance assessment, with MATLAB being the favored simulator. Experimental verification is also carried out, but the articles lack comprehensive information, which poses a challenge for replicating the experiments. In general, a minuscule proportion of publications provide replicable results.


Ad Hoc Wireless Networks, Ad-Hoc Networks, Wireless Sensor Networks, Low-Rate Wireless Personal Area Networks, Infrared and Radio Frequency.

  1. S. Chakrabarti and A. Mishra, “QoS issues in ad hoc wireless networks,” IEEE Communications Magazine, vol. 39, no. 2, pp. 142–148, Jan. 2001, doi: 10.1109/35.900643.
  2. E. H. Callaway et al., “Home networking with IEEE 802.15.4: a developing standard for low-rate wireless personal area networks,” IEEE Communications Magazine, vol. 40, no. 8, pp. 70–77, Aug. 2002, doi: 10.1109/mcom.2002.1024418.
  3. T. Camp, J. Boleng, and V. Davies, “A survey of mobility models for ad hoc network research,” Wireless Communications and Mobile Computing, vol. 2, no. 5, pp. 483–502, Aug. 2002, doi: 10.1002/wcm.72.
  4. S.-Y. Ni, Y. Tseng, Y. Chen, and J. Sheu, “The broadcast storm problem in a mobile ad hoc network,” Wireless Networks, Aug. 1999, doi: 10.1145/313451.313525.
  5. N. Shacham, “Hierarchical organization for large, dynamic radio networks.,” Sri, Jan. 1988, [Online]. Available:
  6. N. Gower, “Effects of Forward Error Correction (FEC) on SURAN (Survivable, Adaptive Networks) Protocol,” Feb. 1987. doi: 10.21236/ada182632.
  7. D. Hemanand, N. P. G. Bhavani, S. Ayub, M. W. Ahmad, S. Narayanan, and A. Haldorai, “Multilayer vectorization to develop a deeper image feature learning model,” Automatika, vol. 64, no. 2, pp. 355–364, Dec. 2022, doi: 10.1080/00051144.2022.2157946.
  8. Z. Li, D. Yang, Z. Li, C. Han, and G. Xie, “Mobile Content Hosting Infrastructure in China: A View from a Cellular ISP,” in Lecture Notes in Computer Science, 2018, pp. 100–113. doi: 10.1007/978-3-319-76481-8_8.
  9. Kheriya. F. Alhaddar, H. Bishi, Somya. H. Alshepane, and M. Elfituri, “Direct Sequence Spread Spectrum Technique for Multi-User Communication System Application,” 2021 IEEE 1st International Maghreb Meeting of the Conference on Sciences and Techniques of Automatic Control and Computer Engineering MI-STA, May 2021, doi: 10.1109/mi-sta52233.2021.9464450.
  10. K. Dostert, “Frequency-hopping spread-spectrum modulation for digital communications over electrical power lines,” IEEE Journal on Selected Areas in Communications, vol. 8, no. 4, pp. 700–710, May 1990, doi: 10.1109/49.54466.
  11. R. Valadas, A. P. M. Tavares, A. M. De Oliveira Duarte, A. Moreira, and C. T. Lomba, “The infrared physical layer of the IEEE 802.11 standard for wireless local area networks,” IEEE Communications Magazine, vol. 36, no. 12, pp. 107–112, Jan. 1998, doi: 10.1109/35.735887.
  12. A. Kanjanavapastit and B. Landfeldt, “An analysis of a modified point coordination function in IEEE 802.11,” 14th IEEE Proceedings on Personal, Indoor and Mobile Radio Communications, 2003. PIMRC 2003., Jul. 2004, doi: 10.1109/pimrc.2003.1260411.
  13. J. W. Robinson and T. S. Randhawa, “Saturation throughput analysis of IEEE 802.11E Enhanced Distributed Coordination function,” IEEE Journal on Selected Areas in Communications, vol. 22, no. 5, pp. 917–928, Jun. 2004, doi: 10.1109/jsac.2004.826929.
  14. N. Madtha et al., “Detection of side-channel communication in ad hoc networks using request to send (RTS) messages,” 2014 IEEE 27th Canadian Conference on Electrical and Computer Engineering (CCECE), May 2014, doi: 10.1109/ccece.2014.6901144.
  15. K. Dwivedi, U. Kaliyaperumal Subramanian, J. Kuruvilla, A. Thomas, D. Shanthi, and A. Haldorai, “Time-series data prediction problem analysis through multilayered intuitionistic fuzzy sets,” Soft Computing, vol. 27, no. 3, pp. 1663–1671, Apr. 2022, doi: 10.1007/s00500-022-07053-4.
  16. J. Yick, B. Mukherjee, and D. Ghosal, “Wireless sensor network survey,” Computer Networks, vol. 52, no. 12, pp. 2292–2330, Aug. 2008, doi: 10.1016/j.comnet.2008.04.002.
  17. P. Piazza et al., “Underwater photogrammetry in Antarctica: long-term observations in benthic ecosystems and legacy data rescue,” Polar Biology, vol. 42, no. 6, pp. 1061–1079, Apr. 2019, doi: 10.1007/s00300-019-02480-w.
  18. H. Kopnina, “Anthropocentrism: Problem of Human-Centered Ethics in Sustainable Development goals,” in Encyclopedia of the UN sustainable development goals, 2019, pp. 1–9. doi: 10.1007/978-3-319-71065-5_105-1.
  19. M. Mehić, O. Maurhart, S. Raß, and M. Vozňák, “Implementation of quantum key distribution network simulation module in the network simulator NS-3,” Quantum Information Processing, vol. 16, no. 10, Aug. 2017, doi: 10.1007/s11128-017-1702-z.
  20. G. Sakellari and G. Loukas, “A survey of mathematical models, simulation approaches and testbeds used for research in cloud computing,” Simulation Modelling Practice and Theory, vol. 39, pp. 92–103, Dec. 2013, doi: 10.1016/j.simpat.2013.04.002.


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Cite this article

Sim Sze Yin and Yoni Danieli, “Assessing the Viability of Performance Evaluation Methods in Network Research”, Journal of Computing and Natural Science, vol.4, no.1, pp. 020-030, January 2024. doi: 10.53759/181X/JCNS202404003.


© 2024 Sim Sze Yin and Yoni Danieli. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.