High Value of Information Guided Data Enhancement for Heterogeneous Underwater Wireless Sensor Networks

Ensuring the freshness of high Value Information (VoI) data has a significant practice meaning for marine observations and emergencies. The traditional forward method with an auv-aid is used to ensure VoI data. However, methods suffer from two issues: insufficient throughput random forwarding cluster heads (CHs). AUV (Autonomous Underwater Vehicle) limited energy cannot meet demand generation Low packets compete channels, resulting in low freshness. To address above issues, we propose Data Access Channel Scheme based on High (DACS-HVOI), which suitable prioritizing transmission VoI. First, according level VoI, are divided into K classes, that collected forwarded by defined as highest K+1 class. Second, prior knowledge network, Markov chain algorithm-based employed predict nodes should preferentially use channel, avoid conflict between Third, stochastic fluid theory, multilevel queueing system CHs constructed forwarding. Last, compared state-of-art protocols, experimental simulation shows proposed scheme latency network throughput, while improving high-VoI ensuring priority packets.