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Energy Harvesting Cognitive Radio Wireless Sensor Networks (EHCRWSNs) have emerged as a promising technology for sustainable and reliable wireless communication by integrating energy harvesting capabilities with dynamic spectrum access. However, maintaining network stability and reliable data transmission remains challenging due to fluctuating harvested energy, limited battery capacity, dynamic spectrum availability, and unexpected sensor node failures. Existing energy-aware routing approaches primarily consider residual energy and current network conditions, which may result in inefficient route selection, premature node depletion, increased transmission delay, and frequent network disconnections. To address these challenges, this paper proposes a Predictive Energy-Neutrality-Aware Adaptive Routing (PENAR) mechanism that jointly considers future energy availability, spectrum availability, and node failure conditions during route selection. The proposed mechanism estimates the energy requirements and harvested energy of sensor nodes to identify energy-neutral routing opportunities. Furthermore, spectrum-aware route selection is incorporated to select suitable communication paths based on available licensed spectrum and primary user activity. A proactive node failure recovery mechanism is also introduced to identify energy-depleted or potentially failing nodes and establish alternative routing paths to maintain network connectivity. The proposed approach aims to improve energy utilization, extend network lifetime, enhance packet delivery reliability, and reduce end-to-end communication delay. Its performance will be evaluated through simulation by comparing it with existing energy-efficient routing protocols using metrics such as residual energy, energy consumption, network lifetime, packet delivery ratio, end-to-end delay, and primary user collision probability. The proposed mechanism is expected to provide an adaptive and energy-efficient routing solution for reliable communication in EHCRWSN environments.
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M Kumutha (2026) studied this question.
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