Gelecek nesil ağlar için biyolojik esinli iletişim teorileri ve teknikleri

Recent developments in macro, micro, and nanoscale communication technologies stimulatethe researchers to devise a next-generation network vision. In this vision, next-generationnetwork architectures are expected to enable the users to efficiently transmit and receive vastamount of information anywhere and anytime through any kind of communication devicesfrom a tiny nanosensor node that operates in a human body for a healthcare application toa base station that is used as a spectrum broker to coordinate the spectrum accesses of unlicensedusers. However, the realization of the next-generation network vision brings manycrucial challenges that must be addressed. In particular, the centralized control of the nextgenerationnetwork architectures is not a practical solution. Instead, the next-generationnetwork architectures and communication protocols must have the capabilities of scalability,self-organization, self-adaptation, and survivability. On the other hand, the biologicalsystems in nature intrinsically have these capabilities. For example, insects in a colony cooperativelyaccomplish many complex tasks required for their vital functionalities withoutany need for a central control. Furthermore, natural nanoscale networks such as immunesystem and bacteria colonies employs incredible nanoscale communication phenomena, e.g.,quorum sensing of bacteria, that can be used to devise efficient nanoscale communicationparadigms for nanoscale next-generation networks. Hence, the natural biological systemsmay give great inspiration to develop the communication network models and techniquesfor the next-generation communication networks. The objective of this thesis is to developthe bio-inspired communication techniques for the dierent next-generation networks andprovide communication theoretical analyses for some of these networks. More specifically,Distributed Node and Rate Selection (DNRS) algorithm is first proposed for wireless sensornetworks (WSN) using the principles of natural immune system. Then, BiologicallyinspiredSpectrum Sharing (BIOSS) algorithm is introduced for cognitive radio networks(CRN), which is based on the adaptive task allocation model in insect colonies. Next, immunesystem-inspired Evolutionary Opportunistic Spectrum Access (ESA) protocol is presented forcognitive radio ad hoc networks. Homeostasis-inspired Autonomous Communication (HAC)protocol is introduced for wireless audio sensor networks (WASN). Based on the prey modelin foraging theory, bio-inspired cross-layer (BIOX) communication and coordination protocolis described for wireless sensor and vehicular actor networks (WSAN). Then, BiologicalForaging-inspired Communication (BFC) algorithm is introduced for the energy-efficient andspectrum-aware communication requirements in Intermittently-connected Mobile CognitiveRadio ad hoc Networks (IMCRN). An information theoretical approach is given for capacityof a molecular communication channel between two nanomachines. Using the stochasticmodel of molecular reactions in biochemical systems, a realistic channel model and a deterministiccapacity expression are given for point-to-point, broadcast, and multiple-accessmolecular communication channels. Then, Mobile Ad hoc Molecular Nanonetwork (MAMNET)with electrochemical communication is modeled and analyzed. Molecular Array-basedCommunication (MARCO) scheme is given for nanonetworks. The concept of body areananonetworks (BAN2) with molecular communication is introduced for future nanomedicineapplications. Finally, the concept of Carbon Nanotube-based nanoscale Ad hoc Networks(CANET) is described for future nanotechnology applications.