Ipek Abasikeles (28 results)

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Paperback. Condition: Brand New. 136 pages. 8.66x5.91x0.31 inches. In Stock.

Taschenbuch. Condition: Neu. Performance Improvement Of The 2D Broadcast-based DSM Systems | By Message Operations | Ipek Abasikeles (u. a.) | Taschenbuch | 136 S. | Englisch | 2013 | LAP LAMBERT Academic Publishing | EAN 9783659462498 | Verantwortliche Person für die EU: BoD - Books on Demand, In de Tarpen 42, 22848 Norderstedt, info[at]bod[dot]de | Anbieter: preigu.…

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Taschenbuch. Condition: Neu. Deep Learning in Ad-Hoc Wireless Networks | Gokhan Altan (u. a.) | Taschenbuch | Studies in Big Data | v | Englisch | 2026 | Springer | EAN 9783031860775 | Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg, juergen[dot]hartmann[at]springer[dot]com | Anbieter: preigu. …

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Taschenbuch. Condition: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -A DSM system on 2D broadcast-based optical architecture is simulated by using OPNET Modeler and the performance of the system is improved by message priority and combining techniques under different traffic patterns, including uniform, hot region and bit permutations. The simulated system contains 64 nodes. Each node has a server that processes directory, cache and processor messages, two output channels and two input queues, one for horizontal and the other for vertical dimension. Scenarios are run to measure average network response time, average input waiting time and average channel waiting time for varying values of DSM parameters. The results show that combining reduces average channel waiting time between 13% and 29%, while priority reduces average input waiting time between 7% and 43% on average. With the application of message priority and combining, between 7% and 40% performance increase for average network response time has gained. 136 pp. Englisch.…

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Taschenbuch. Condition: Neu. This item is printed on demand - Print on Demand Titel. Neuware -A DSM system on 2D broadcast-based optical architecture is simulated by using OPNET Modeler and the performance of the system is improved by message priority and combining techniques under different traffic patterns, including uniform, hot region and bit permutations. The simulated system contains 64 nodes. Each node has a server that processes directory, cache and processor messages, two output channels and two input queues, one for horizontal and the other for vertical dimension. Scenarios are run to measure average network response time, average input waiting time and average channel waiting time for varying values of DSM parameters. The results show that combining reduces average channel waiting time between 13% and 29%, while priority reduces average input waiting time between 7% and 43% on average. With the application of message priority and combining, between 7% and 40% performance increase for average network response time has gained.VDM Verlag, Dudweiler Landstraße 99, 66123 Saarbrücken 136 pp. Englisch.…

Taschenbuch. Condition: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - A DSM system on 2D broadcast-based optical architecture is simulated by using OPNET Modeler and the performance of the system is improved by message priority and combining techniques under different traffic patterns, including uniform, hot region and bit permutations. The simulated system contains 64 nodes. Each node has a server that processes directory, cache and processor messages, two output channels and two input queues, one for horizontal and the other for vertical dimension. Scenarios are run to measure average network response time, average input waiting time and average channel waiting time for varying values of DSM parameters. The results show that combining reduces average channel waiting time between 13% and 29%, while priority reduces average input waiting time between 7% and 43% on average. With the application of message priority and combining, between 7% and 40% performance increase for average network response time has gained.…

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Buch. Condition: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -This book presents innovative applications of deep learning techniques in wireless ad-hoc networks, addressing critical challenges such as trust, routing, traffic management, and intrusion detection. By combining advanced AI models with real-world network scenarios, the chapters explore novel solutions for improving network reliability, security, and efficiency. Readers benefit from a multidisciplinary approach that bridges deep learning and wireless communication, offering both theoretical insights and practical frameworks. Targeting researchers, engineers, and graduate students, this work serves as a valuable resource for understanding and implementing deep learning strategies to optimize modern wireless systems. Whether improving IoT networks, securing controller area networks, or enabling smart mobility, the book provides actionable knowledge on Deep Learning applications for solving current and future challenges in ad-hoc wireless networks. 132 pp. Englisch.…

Taschenbuch. Condition: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -This book presents innovative applications of deep learning techniques in wireless ad-hoc networks, addressing critical challenges such as trust, routing, traffic management, and intrusion detection. By combining advanced AI models with real-world network scenarios, the chapters explore novel solutions for improving network reliability, security, and efficiency. Readers benefit from a multidisciplinary approach that bridges deep learning and wireless communication, offering both theoretical insights and practical frameworks. Targeting researchers, engineers, and graduate students, this work serves as a valuable resource for understanding and implementing deep learning strategies to optimize modern wireless systems. Whether improving IoT networks, securing controller area networks, or enabling smart mobility, the book provides actionable knowledge on Deep Learning applications for solving current and future challenges in ad-hoc wireless networks. 132 pp. Englisch.…

Buch. Condition: Neu. This item is printed on demand - Print on Demand Titel. Neuware -This book presents innovative applications of deep learning techniques in wireless ad-hoc networks, addressing critical challenges such as trust, routing, traffic management, and intrusion detection. By combining advanced AI models with real-world network scenarios, the chapters explore novel solutions for improving network reliability, security, and efficiency. Readers benefit from a multidisciplinary approach that bridges deep learning and wireless communication, offering both theoretical insights and practical frameworks. Targeting researchers, engineers, and graduate students, this work serves as a valuable resource for understanding and implementing deep learning strategies to optimize modern wireless systems. Whether improving IoT networks, securing controller area networks, or enabling smart mobility, the book provides actionable knowledge on Deep Learning applications for solving current and future challenges in ad-hoc wireless networks.Springer-Verlag KG, Sachsenplatz 4-6, 1201 Wien 132 pp. Englisch.…

Taschenbuch. Condition: Neu. This item is printed on demand - Print on Demand Titel. Neuware -This book presents innovative applications of deep learning techniques in wireless ad-hoc networks, addressing critical challenges such as trust, routing, traffic management, and intrusion detection. By combining advanced AI models with real-world network scenarios, the chapters explore novel solutions for improving network reliability, security, and efficiency. Readers benefit from a multidisciplinary approach that bridges deep learning and wireless communication, offering both theoretical insights and practical frameworks. Targeting researchers, engineers, and graduate students, this work serves as a valuable resource for understanding and implementing deep learning strategies to optimize modern wireless systems. Whether improving IoT networks, securing controller area networks, or enabling smart mobility, the book provides actionable knowledge on Deep Learning applications for solving current and future challenges in ad-hoc wireless networks. 132 pp. Englisch.…

Condition: New. Print on Demand.

Condition: New. PRINT ON DEMAND.

Taschenbuch. Condition: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - This book presents innovative applications of deep learning techniques in wireless ad-hoc networks, addressing critical challenges such as trust, routing, traffic management, and intrusion detection. By combining advanced AI models with real-world network scenarios, the chapters explore novel solutions for improving network reliability, security, and efficiency. Readers benefit from a multidisciplinary approach that bridges deep learning and wireless communication, offering both theoretical insights and practical frameworks. Targeting researchers, engineers, and graduate students, this work serves as a valuable resource for understanding and implementing deep learning strategies to optimize modern wireless systems. Whether improving IoT networks, securing controller area networks, or enabling smart mobility, the book provides actionable knowledge on Deep Learning applications for solving current and future challenges in ad-hoc wireless networks.…

Buch. Condition: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - This book presents innovative applications of deep learning techniques in wireless ad-hoc networks, addressing critical challenges such as trust, routing, traffic management, and intrusion detection. By combining advanced AI models with real-world network scenarios, the chapters explore novel solutions for improving network reliability, security, and efficiency. Readers benefit from a multidisciplinary approach that bridges deep learning and wireless communication, offering both theoretical insights and practical frameworks. Targeting researchers, engineers, and graduate students, this work serves as a valuable resource for understanding and implementing deep learning strategies to optimize modern wireless systems. Whether improving IoT networks, securing controller area networks, or enabling smart mobility, the book provides actionable knowledge on Deep Learning applications for solving current and future challenges in ad-hoc wireless networks.…

Condition: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Die Leistung von drei verzeichnisbasierten Cache-Kohaerenz-Protokollen Die strikte Anforderung-Antwort-, Interventionsweiterleitung und Antwortweiterleitung werden ueber eine Simulation auf dem SOME-Bus ausgewertet, einem Glasfaserverbindungsnetzwerk, das DS.…