Algorithms for molecular communication networks
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Bio-sensors are becoming an integral part of our everyday life, implicitly and explicitly. The natural sensing mechanism and advancements in synthetic biology has made bacteria as potential candidates for building bio-sensors. The successful operation and availability of biological circuits and components for data processing makes bacteria strong candidates to use as computing machines. Currently bio-sensors, including bacterial sensors are used purely for sensing; information from each sensor is processed independently off-line, leading to processing delays, manual errors and concerns on bio-compatibility. In this dissertation, we focus on the communication between bio-sensors in a bionetwork. A bionetwork can foray into domains that are unreachable using current technologies. Such a network of bacterial(bio) sensors differs significantly from traditional electromagnetic communication due to the devices used, the channel, the medium/environment and the application. We identify three unique characteristics of bacterial networks that differentiates it from traditional networks viz., computational complexity, delay, and asymmetry that demands a fundamental redesign of communication algorithms. We developed practical and efficient communication algorithms to be implemented on bacterial transceivers. Each of these algorithms identifies the constraint of the network and leverages the opportunities provided by the system to achieve high throughput efficiency.