Abstract
An Intrabody Nanonetwork (IBNN) is constituted by nanoscale devices that are implanted inside the human body for monitoring of physiological parameters for disease diagnosis and treatment purposes. The extraordinary accuracy and precision of these nanoscale devices in cellular level disease diagnosis and drug delivery are envisioned to advance the traditional healthcare system. However, the feature constraints of these nanoscale devices, such as inadequate energy resources, topology-unawareness, and limited computational power, challenges the development of energy-efficient routing protocol for IBNNs. The presented work concentrates on the primary limitations and responsibilities of IBNNs and designs a routing protocol that incorporates characteristics of Exponential Weighted Moving Average (EWMA) Based Opportunistic Data Transmission (EWMA-ODT) and Artificial Colony Algorithm Based Query Response Transmission (ABC-QRT) approaches for efficiently handling the routing challenges of IBNNs. In EWMA-ODT, the moving Nano Biosensors (NBSs) employ the EWMA method attributes to aggregate detected data by assigning high weightage to the recent detected information. Later, the aggregated data is transmitted to the Nano Router (NR) when the direct data transmission opportunity is available, the reception of aggregated briefs NR about the condition of the network after the last successful interaction with minimum energy consumption. Whereas, the ABC-QRT approach introduces the ABC algorithm for the selection of those optimal NBSs that have maximum fitness value for satisfying the data transmission demand of the external healthcare system with minimal traffic overhead. The simulation results validate that the joint contribution of these approaches enhances IBNNs lifetime and reduces end-to-end delay as compared to the flooding scheme.
Highlights
The advancement of nanotechnology has boosted the development of nanoscale devices [1], which are remarkably transforming medicine and the healthcare system
EXPONENTIAL WEIGHTED MOVING AVERAGE AND ARTIFICIAL BEE COLONY ALGORITHM FOR DESIGNING ENERGY CONSERVING ROUTING SCHEME we provide a detailed demonstration of our proposed routing scheme, including system architecture, network model, and a comprehensive description of the proposed routing protocol
We have performed a comparison of our proposed scheme with the Exponential Weighted Moving Average (EWMA)-ODT and ABC-QRT approaches to evaluate the individual performance impact of these approaches on the performance of various simulation metrics used for performance evaluation
Summary
The advancement of nanotechnology has boosted the development of nanoscale devices [1], which are remarkably transforming medicine and the healthcare system. The proposed novel routing scheme explicitly concentrates on the challenges of IBNNs by taking into account the fundamental disparity between the communication load and limited available resources of NBSs. In line with the vast applicability of bio-inspired solutions such as swarm intelligence algorithms for low energy and computational devices [15]–[17], they have been used in various applications, including energy-efficient clustering [18]–[20], node localization [21], [22], and improved data collection [23] in wireless sensor networks.
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a call
