Bio-Inspired Nanorouter Mobility Model for Energy Efficient Data Collection in Intrabody Nanonetwork

The spatially distributed nanosensors move through the body for detecting different physiological information which is collected by the nanorouter for further disease diagnosis and treatment. The presented study addresses the primary challenge of data collection with minimum energy consumption by proposing a novel approach that exploits the moving nature of Intrabody nanonetwork. The adaptive and self-organized mobility of nanorouter is achieved by employing Particle Swarm Optimization (PSO) model. The PSO based nanorouter mobility model covers how efficiently data is collected from the targeted event area. Efficient collection of data encompasses aggregating data from a maximum number of nodes to ensure a certain level of data accuracy as well as without consuming significant energy resources. The simulation results validate that nanorouter mobility assists in prolonging network lifetime as well as data collection from the maximum number of deployed nanonodes also guarantees increased reliability and accuracy of detected information.