Integrating Mobile Technologies with Energy Harvesting for Disaster Detection in Underwater Wireless Sensor Networks Using Stochastic Network Calculus

Christhu Raj M. R.; Vignesh S. R.; Rajeev Sukumaran

doi:10.3991/ijim.v20i03.60127

Authors

Christhu Raj M. R. SRM Institute of Science and Technology, Chengalpattu, India
Vignesh S. R. SRM Institute of Science and Technology, Chengalpattu, India https://orcid.org/0000-0002-5339-9065
Rajeev Sukumaran SRM Institute of Science and Technology, Chengalpattu, India

DOI:

https://doi.org/10.3991/ijim.v20i03.60127

Keywords:

Mobile Technologies, Mobile-Assisted Disaster Detection, Underwater Wireless Sensor Networks (UWSNs), Energy Harvesting Systems, Temperature-Aware Stochastic Network Calculus (T-SNC), Adaptive Routing for Mobile Sensing, Mobile-Enabled Early Warning Systems

Abstract

Underwater wireless sensor networks (UWSNs) are critical for monitoring environmentally sensitive areas, and operation of such networks is however, very much energy constrained. Conventional deterministic methods do not accurately capture the random and time-varying properties of the underwater acoustic environment. This paper presents a novel routing paradigm, temperature-aware SNC for underwater wireless sensor networks (T-SNC UWSN), which is the combination of stochastic network calculus (SNC) with temperature-based analysis and piezoelectric energy harvesting (PEH) and mobile approaches to improve network flexibility and robustness. Variation in temperature affects the efficiency of energy harvesting and has an immediate impact on power availability at the sensor nodes as well, indicating the occurrence of such underwater catastrophes as seismic events or tsunamis. By incorporating the temperature fluctuation into the SNC model, our model is capable of precisely revealing thermal influence on harvested energy and network stability, which enables efficient adaptive routing and enhanced disaster detection. The performance is analysed through simulations on packet delivery ratio (PDR), end-to-end delay, network throughput and path loss. It is demonstrated that SNC with temperature-aware modelling and mobile technologies manages to improve energy sustainability and disaster preparedness as well as the robustness of the network in unforeseen aquatic environments. This probabilistic model is helpful to practical systems of energy-efficient UWSNs, early warning systems, mobility-assisted monitoring, climate-resilience solutions and so forth.

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