Storage Capabilities in Underwater Wireless Sensor Networks for Energy Balancing and Channel Alignment

Abstract

Underwater sensor node overflow occurs when large amount of sensory data is already stored and it is unavailable to obtain new data when an event happens. This misalignment tends to partitioning of individual node from networks in reporting information to sink. Resilience of individual node to recover from overflow considering channel and storage capabilities is needed. This work tries to avoid unnecessary transmission of the overloaded node. The contemporaneous work of storage and transmission is stated to improve energy efficiency in the desired work using DBR Bayesian network. Two slice Bayesian network is constructed for every node for calculating conditional probability distribution to resurrect links. Number of transmission is being improved considering the facilitation of nodes storage and transit duration reducing the overall energy consumption of a node by constraining unnecessary transmissions.