Performance Evaluation of 5G Networks using Fixed, Adaptive and Threshold based Duty Cycle Adjustment for Wireless Sensor Networks

Abstract

Wireless Sensor Networks (WSNs) hold immense potential for diverse applications, ranging from environmental monitoring to industrial automation. In the context of the impending 5G revolution, the convergence of WSNs and 5G networks offers new possibilities for efficient data transmission and communication. A crucial aspect of WSNs is duty cycling, where sensor nodes alternate between active and sleep modes to conserve energy. This research delves into the performance evaluation of three distinct duty cycles adjustment strategies Fixed, Adaptive, and Threshold-based in the context of 5G-enabled WSNs. In this study, we design and simulate an experimental framework that integrates the dynamics of 5G networks and the nuanced behaviors of WSNs. The Fixed Duty Cycle strategy adheres to a predefined duty cycle, while the Adaptive Duty Cycle strategy dynamically adjusts duty cycles based on real-time data rate observations. The Threshold-based Duty Cycle strategy, on the other hand, leverages a threshold to determine the appropriate duty cycle adjustment. Through extensive simulations and analysis, we assess these strategies across multiple performance metrics, including energy efficiency, packet delivery ratio, data rate, and throughput. The obtained results reveal nuanced trade-offs among the strategies, offering insights into their suitability for various application scenarios. Our findings underscore the importance of context-aware duty cycle adaptation in optimizing the performance of 5G-enabled WSNs, while respecting the energy constraints inherent to sensor nodes. This research contributes to the growing body of knowledge in the realm of 5G-WSN convergence and offers practical insights for designers, engineers, and researchers seeking to harness the full potential of these technologies. By comprehensively evaluating the implications of duty cycle adjustment strategies, this work contributes to advancing the efficiency and applicability of 5G networks in the realm of Wireless Sensor Networks.