Citation

Ejaz, Muhammad Abdullah and Ramasamy, R Kanesaraj and Rajendran, Venushini and Jamal, Shamsuriani Md. and Hamzah, Faizal Amri (2026) Implementation of a Runtime Performance Evaluation Framework for Edge Computing on Raspberry Pi 4. In: 3rd IEEE International Conference on Trends in Quantum Computing and Emerging Business Technologies, TQCEBT 2026, 9 April 2026 - 11 April 2026, Pune.

Text 6.pdf - Published Version Restricted to Repository staff only Download (492kB)

Abstract

Edge computing plays a critical role in Internet of Things (IoT) systems, where the choice of runtime environment can directly affect application speed, responsiveness, and reliability on resource-constrained devices. This study presents a comparative performance evaluation of Node.js and Python 3.9.2 on the Raspberry Pi 4 Model B, a widely used edge computing platform. Controlled experiments were conducted across four representative workload categories: CPU-bound processing, file and network I/O, memory operations, and socket communication. These workloads were selected to reflect common computational demands in IoT edge applications. The results show that Node.js outperformed Python in computation-intensive tasks, achieving up to 11 times faster execution in recursive processing and nearly 3 times higher throughput in HTTP request handling, largely due to its just-in-time compilation and non-blocking event-driven architecture. In contrast, Python demonstrated superior performance in socket-based communication, recording approximately 3 times lower latency in synchronous echo tests. The findings were validated through repeated trials and statistical analysis, with significance confirmed at p < 0.01. Overall, this study provides practical benchmark evidence to support runtime selection for IoT edge systems, helping developers and system designers choose the most suitable platform based on workload characteristics.

Item Type:	Conference or Workshop Item (Paper)
Uncontrolled Keywords:	Edge Computing, Internet of Thing
Subjects:	Q Science > QA Mathematics > QA71-90 Instruments and machines > QA75.5-76.95 Electronic computers. Computer science
Divisions:	Faculty of Computing and Informatics (FCI)
Depositing User:	Ms Rosnani Abd Wahab
Date Deposited:	30 Oct 2026 00:43
Last Modified:	30 Oct 2026 00:43
URII:	http://shdl.mmu.edu.my/id/eprint/17012

Downloads

Edit (login required)