This is an unedited manuscript accepted for publication and provided as an Article in Press for early access at the author’s request. The article will undergo copyediting, typesetting, and galley proof review before final publication. Please be aware that errors may be identified during production that could affect the content. All legal disclaimers of the journal apply.
Arnav Dubey,
Avnish Soni,
Binit Behl,
- Student, Department of Computer Science and Engineering, Greater Noida Institute of Technology (Affiliated to Guru Gobind Singh Indraprastha University), Greater Noida, Uttar Pradesh, India
- Student, Department of Computer Science and Engineering, Greater Noida Institute of Technology (Affiliated to Guru Gobind Singh Indraprastha University), Greater Noida, Uttar Pradesh, India
- Student, Department of Computer Science and Engineering, Greater Noida Institute of Technology (Affiliated to Guru Gobind Singh Indraprastha University), Greater Noida, Uttar Pradesh, India
Abstract
The paradigm shift towards Distributed Edge Computing (DEC) has changed the entire world of the Internet of Things (IoT) connectivity to its core and has spawned the need to implement robust Asynchronous Random Access (ARA) protocols to deal with the contention between a huge range of diverse devices that are constrained by their resources. While there is now extensive optimization of these protocols in contemporary research for channel efficiency (throughput, latency, and collision probability), there is a critical gap in understanding that exists in the detailed design of these protocols in edge hardware. This disconnect has often lead to protocols that though theoretically efficient, have created processing overhead that is prohibitive for both accelerating battery depletion and creating processing bottlenecks on low power edge nodes. In order to compensate with this, an intelligent Complexity-Performance Tradeoff Model, by taking into the evaluation framework of MAC layer protocols the principle of Software Science, Halstead Metrics, is presented in this paper. A novel mathematical utility function is formed to make correlations between protocol complexity indicators (Volume, Difficulty, Effort) and measurable system performance parameters to establish the Pareto frontier for optimal selection. Through extensive stochastic simulation in different network densities, traffic loads and device capabilities, we show that software complexity is non-linear and has a diminishing relationship with network performance. Our analysis shows a definite optimal “sweet spot” where the protocol complexity is good enough to deal with the contention effectively while not having too much computation costs. This framework helps network architects to do complexity aware performance engineering, supporting adaptive protocols selection and automatic optimization. Ultimately this research yields a basis model for the software-hardware co-design of next generation edge networks, guaranteeing that communication efficiency is enabled without having to sacrifice the sustainability and reliability of the network of the underlying edge infrastructure, thus paving the way for standardized complexity aware MAC protocol specifications in 5G-Advanced and 6G systems.
Keywords: Random Access Protocols, Halstead’s Metrics, Edge Computing, Software Complexity, Distributed Systems
References
- IBM DevOps Test Embedded. Ibm.com. 2026. Available from: https://www.ibm.com/docs/en/ devops-test-embedded/9.0.0?topic=metrics-halstead
- Varga A. Discrete event simulation system. InProc. of the European Simulation Multiconference ( ’2001) 2001 J n (Vol. 17, . 7).
- GeeksforGeeks. Multiple Access Protocols in Computer Network. GeeksforGeeks. 2018. Available from: https://www.geeksforgeeks.org/computer-networks/multiple-access-protocols-in-computer network/ .
- Young M. The Technical Writer’s Handbook. Mill Valley, CA, USA: Univ. Science. 1989.
- Metcalfe RM, Boggs DR. Ethernet: Distributed packet switching for local computer networks. Communications of the ACM. 1976 Jul 1;19(7):395-404.
- Eason G, Noble B, Sneddon IN. On certain integrals of Lipschitz-Hankel type involving products of Bessel functions. Philosophical Transactions of the Royal Society of London. Series A, Mathematical and Physical Sciences. 1955 Apr 19;247(935):529-51.
- Abramson N. The ALOHA system: Another alternative for computer communications. In Proceedings of the November 17-19, 1970, fall joint computer conference 1970 Nov 17 (pp. 281- 285).
- A treatise on electricity and magnetism: Maxwell, James Clerk, 1831-1879: Free Download, Borrow, and Streaming: Internet Archive. Internet Archive. 2026. Available from: https://archive.org/details/electricandmagne01maxwrich/page/n7/mode/2up
- Abramson N. The ALOHA system: Another alternative for computer communications. In Proceedings of the November 17-19, 1970, fall joint computer conference 1970 Nov 17 (pp. 281- 285).
- Lincoln CR. Software Metrics: A Guide to Planning, Analysis, and Application. Software Quality Professional. 2004 Dec 1;7(1):50.
- Kleinrock L, Tobagi F. Packet switching in radio channels: Part I-carrier sense multiple-access modes and their throughput-delay characteristics. IEEE transactions on Communications. 1975 Dec 31;23(12):1400-16.
- Jiang L, Walrand J. A distributed CSMA algorithm for throughput and utility maximization in wireless networks. IEEE/ACM transactions on networking. 2009 Nov 24;18(3):960-72.
Journal of Software Engineering Tools & Technology Trends
| Volume | 13 | |
| 02 | ||
| Received | 24/06/2026 | |
| Accepted | 05/07/2026 | |
| Published | 18/08/2026 | |
| Publication Time | 55 Days |