A Comprehensive Performance Evaluation of a Wi-Fi-Based Wireless Sensor Network Using Raspberry Pi and ESP8266 Under Multi-Rate Traffic Conditions
DOI:
https://doi.org/10.65405/m5hagm61Keywords:
Wireless Sensor Networks, ESP8266, Wi-Fi, Raspberry Pi, Internet of Things, Edge Computing, Performance Evaluation.Abstract
In modern Internet of Things environments, Wireless Sensor Networks (WSNs) have become an essential element. particularly, in local monitoring for distributed sensing applications. Smart homes, environmental observation systems, industrial sites, and even small healthcare setups are examples of these applications. In most cases, these networks have traditionally relied on low-power technologies such as ZigBee and Bluetooth Low Energy because those protocols were built with constrained devices in mind. Still, the growing availability of inexpensive Wi-Fi-enabled microcontrollers, especially ESP8266-based boards, has made Wi-Fi a more realistic option for small and medium sensor deployments.
This paper presents an experimental evaluation of a Wi-Fi-based WSN built around a Raspberry Pi gateway configured as a dedicated wireless access point and three ESP8266-based WEMOS D1 R1 sensor nodes. The system was tested under several traffic reporting intervals, namely 1 s, 5 s, and 10 s, and also under a controlled same-channel interference condition. The evaluation focuses on end-to-end latency, packet delivery ratio, throughput, jitter, received signal strength indicator, and gateway resource usage in terms of CPU and memory consumption.
The results suggest that Wi-Fi can support highly reliable sensor communication when reporting intervals are moderate, with packet delivery ratio remaining above 99% in the less aggressive cases. Also, more fast in the reporting will introduce greater channel contention and noticeably less stable timing behavior. Under interference, performance degrades further, particularly in latency and delivery reliability. Taken together, the findings suggest that Wi-Fi is a practical option for small-scale sensor networks, though clearly not without trade-offs. The study also provides a reproducible testbed and grounded deployment insights for edge-based IoT sensing systems.
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