03979cam a2200577Ii 4500 ocn919317951 OCoLC 20190328114812.0 m o d cr cnu|||unuuu 150828s2015 enk ob 001 0 eng d N$T eng rda pn N$T YDXCP N$T IDEBK CDX OPELS EBLCP OCLCF FEM VGM OCLCQ MERUC BUF U3W D6H AU@ OCLCQ WYU TKN 968038279 969076076 9780081004654 (electronic bk.) 0081004656 (electronic bk.) 9781785480218 (OCoLC)919317951 (OCoLC)968038279 (OCoLC)969076076 TK5105.5 COM 013000 bisacsh COM 014000 bisacsh COM 018000 bisacsh COM 067000 bisacsh COM 032000 bisacsh COM 037000 bisacsh COM 052000 bisacsh 004.6 23 C�amara, Daniel, author. Bio-Inspired Networking / [electronic resource] Daniel C�amara. London : ISTE Press Ltd. ; Kidlington, Oxford : Elsevier Ltd., 2015. 1 online resource text txt rdacontent computer c rdamedia online resource cr rdacarrier text file rda Vendor-supplied metadata. Includes bibliographical references and index. Bio-inspired techniques are based on principles, or models, of biological systems. In general, natural systems present remarkable capabilities of resilience and adaptability. In this book, we explore how bio-inspired methods can solve different problems linked to computer networks. Machine generated contents note: ch. 1 Evolution and Evolutionary Algorithms -- 1.1. Brief introduction to evolution -- 1.2. Mechanisms of evolution -- 1.2.1. DNA code -- 1.2.2. Mutation -- 1.2.3. Sexual reproduction and recombination -- 1.2.4. Natural selection -- 1.2.5. Genetic drift -- 1.3. Artificial evolution -- 1.3.1. The basic process -- 1.3.2. Limitations -- 1.4. Applications on networks -- 1.4.1.Network positioning -- 1.4.2. Routing -- 1.4.3. Other works -- 1.5. Further reading -- 1.6. Bibliography -- ch. 2 Chemical Computing -- 2.1. Artificial chemistry -- 2.2. Applications on networks -- 2.2.1. Data dissemination -- 2.2.2. Routing -- 2.3. Further reading -- 2.4. Bibliography -- ch. 3 Nervous System -- 3.1. Nervous system hierarchy -- 3.1.1. Central nervous system -- 3.1.2. Peripheral nervous system -- 3.2. The neuron -- 3.3. The neocortex -- 3.4. Speed and capacity -- 3.5. Artificial neural networks -- 3.5.1. The perceptron -- 3.5.2. Interconnecting perceptrons -- 3.5.3. Learning process. Note continued: 3.5.4. The backpropagation algorithm -- 3.6. Applications on networks -- 3.6.1. ANN in intrusion detection systems -- 3.6.2. Fault detection -- 3.6.3. Routing -- 3.7. Further reading -- 3.8. Bibliography -- ch. 4 Swarm Intelligence (SI) -- 4.1. Ant colony optimization -- 4.2. Applications on networks -- 4.2.1. Ants colony on routing -- 4.2.2. Ants colony on intrusion detection -- 4.3. Particle swarm optimization -- 4.4. Applications on networks -- 4.4.1. Particle swarm on node positioning -- 4.4.2. Particle swarm on intrusion detection -- 4.5. Further reading -- 4.6. Bibliography. Computer networks. COMPUTERS Computer Literacy. bisacsh COMPUTERS Computer Science. bisacsh COMPUTERS Data Processing. bisacsh COMPUTERS Hardware General. bisacsh COMPUTERS Information Technology. bisacsh COMPUTERS Machine Theory. bisacsh COMPUTERS Reference. bisacsh Computer networks. fast (OCoLC)fst00872297 Electronic books. ScienceDirect http://www.sciencedirect.com/science/book/9781785480218 247148 247148