Abstract
An intrabody nanonetwork (IBNN) is composed of nanoscale (NS) devices, implanted inside the human body for collecting diverse physiological information for diagnostic and treatment purposes. The unique constraints of these NS devices in terms of energy, storage and computational resources are the primary challenges in the effective designing of routing protocols in IBNNs. Our proposed work explicitly considers these limitations and introduces a novel energy-efficient routing scheme based on a fuzzy logic and bio-inspired firefly algorithm. Our proposed fuzzy logic-based correlation region selection and bio-inspired firefly algorithm based nano biosensors (NBSs) nomination jointly contribute to energy conservation by minimizing transmission of correlated spatial data. Our proposed fuzzy logic-based correlation region selection mechanism aims at selecting those correlated regions for data aggregation that are enriched in terms of energy and detected information. While, for the selection of NBSs, we proposed a new bio-inspired firefly algorithm fitness function. The fitness function considers the transmission history and residual energy of NBSs to avoid exhaustion of NBSs in transmitting invaluable information. We conduct extensive simulations using the Nano-SIM tool to validate the in-depth impact of our proposed scheme in saving energy resources, reducing end-to-end delay and improving packet delivery ratio. The detailed comparison of our proposed scheme with different scenarios and flooding scheme confirms the significance of the optimized selection of correlated regions and NBSs in improving network lifetime and packet delivery ratio while reducing the average end-to-end delay.
Highlights
The introduction of wireless technology in the healthcare environment is an effort to provide significant convenience and accessibility
From the contributions brought by the firefly algorithm in Wireless Sensor Networks (WSNs), we comprehend that the incorporation of a bio-inspired firefly algorithm in intrabody nanonetwork (IBNN) ensures a higher probability of achieving low-complexity energy-efficient data routing
A novel energy-efficient routing protocol is proposed that explicitly considers the constraints of Nano Biosensors (NBSs) in providing continuous healthcare, diagnostics and treatments
Summary
The introduction of wireless technology in the healthcare environment is an effort to provide significant convenience and accessibility. The presented work is an effort towards realizing energy-efficient communication for prolonging the lifetime of IBNNs. In this work, we have considered the well-known fact that sensor node consumes their maximum energy during data transmission. Algorithm is a meta-heuristic algorithm inspired by the flashing pattern and behavior of fireflies; it determines the optimum solution with low complexity that supports in realizing the goal of low energy consumption during the data collection in IBNNs. The main contributions of our proposed work are underlined as: In this work, we proposed a new FLBDS selection mechanism for correlated region selection. Our proposed FLBDS technique ensures the selection of those correlation regions for data aggregation that has updated information and maximum residual energy. We proposed a novel bio-inspired firefly algorithm selection mechanism for evading spatial correlation in the reported data.
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