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Evolutionary Algorithms for Mobile Ad Hoc Networks (Nature-Inspired Computing Series) - Hardcover

 
9781118341131: Evolutionary Algorithms for Mobile Ad Hoc Networks (Nature-Inspired Computing Series)

Synopsis

Describes how evolutionary algorithms (EAs) can be used to identify, model, and minimize day-to-day problems that arise for researchers in optimization and mobile networking

Mobile ad hoc networks (MANETs), vehicular networks (VANETs), sensor networks (SNs), and hybrid networks―each of these require a designer’s keen sense and knowledge of evolutionary algorithms in order to help with the common issues that plague professionals involved in optimization and mobile networking.

This book introduces readers to both mobile ad hoc networks and evolutionary algorithms, presenting basic concepts as well as detailed descriptions of each. It demonstrates how metaheuristics and evolutionary algorithms (EAs) can be used to help provide low-cost operations in the optimization process―allowing designers to put some “intelligence” or sophistication into the design. It also offers efficient and accurate information on dissemination algorithms, topology management, and mobility models to address challenges in the field.

Evolutionary Algorithms for Mobile Ad Hoc Networks:

  • Instructs on how to identify, model, and optimize solutions to problems that arise in daily research
  • Presents complete and up-to-date surveys on topics like network and mobility simulators
  • Provides sample problems along with solutions/descriptions used to solve each, with performance comparisons
  • Covers current, relevant issues in mobile networks, like energy use, broadcasting performance, device mobility, and more

Evolutionary Algorithms for Mobile Ad Hoc Networks is an ideal book for researchers and students involved in mobile networks, optimization, advanced search techniques, and multi-objective optimization.

"synopsis" may belong to another edition of this title.

About the Author

BERNABÉ DORRONSORO, PHD, earned his PhD in computer science from the University of Málaga (Spain) in 2007. His main research interests include metaheuristics and mobile networks, among others.

PATRICIA RUIZ, PHD, earned her PhD in computer science at the University of Luxembourg and her degree in telecommunication engineering from the University of Málaga (Spain).

GRÉGOIRE DANOY, PHD, earned his PhD from University of St Etienne (Ecole des Mines) on the optimization of real-world problems using co-evolutionary genetic algorithms, including topology management problems in mobile ad hoc networks.

YOANN PIGNÉ, PHD, obtained his PhD from the University of Le Havre, France, on Modelling and Processing Dynamic Graphs, Applications to Mobile Ad Hoc Networks.

PASCAL BOUVRY, PHD, earned his PhD in computer science from the University of Grenoble (INPG), France, in 1994.

From the Back Cover

Describes how evolutionary algorithms (EAs) can be used to identify, model, and minimize day-to-day problems that arise for researchers in optimization and mobile networking

Mobile ad hoc networks (MANETs), vehicular networks (VANETs), sensor networks (SNs), and hybrid networks―each of these require a designer’s keen sense and knowledge of evolutionary algorithms in order to help with the common issues that plague professionals involved in optimization and mobile networking.

This book introduces readers to both mobile ad hoc networks and evolutionary algorithms, presenting basic concepts as well as detailed descriptions of each. It demonstrates how metaheuristics and evolutionary algorithms (EAs) can be used to help provide low-cost operations in the optimization process―allowing designers to put some “intelligence” or sophistication into the design. It also offers efficient and accurate information on dissemination algorithms, topology management, and mobility models to address challenges in the field.

Evolutionary Algorithms for Mobile Ad Hoc Networks:

  • Instructs on how to identify, model, and optimize solutions to problems that arise in daily research
  • Presents complete and up-to-date surveys on topics like network and mobility simulators
  • Provides sample problems along with solutions/descriptions used to solve each, with performance comparisons
  • Covers current, relevant issues in mobile networks, like energy use, broadcasting performance, device mobility, and more

Evolutionary Algorithms for Mobile Ad Hoc Networks is an ideal book for researchers and students involved in mobile networks, optimization, advanced search techniques, and multi-objective optimization.

From the Inside Flap

Describes how evolutionary algorithms (EAs) can be used to identify, model, and minimize day-to-day problems that arise for researchers in optimization and mobile networking

Mobile ad hoc networks (MANETs), vehicular networks (VANETs), sensor networks (SNs), and hybrid networks—each of these require a designer’s keen sense and knowledge of evolutionary algorithms in order to help with the common issues that plague professionals involved in optimization and mobile networking.

This book introduces readers to both mobile ad hoc networks and evolutionary algorithms, presenting basic concepts as well as detailed descriptions of each. It demonstrates how metaheuristics and evolutionary algorithms (EAs) can be used to help provide low-cost operations in the optimization process—allowing designers to put some “intelligence” or sophistication into the design. It also offers efficient and accurate information on dissemination algorithms, topology management, and mobility models to address challenges in the field.

Evolutionary Algorithms for Mobile Ad Hoc Networks:

  • Instructs on how to identify, model, and optimize solutions to problems that arise in daily research
  • Presents complete and up-to-date surveys on topics like network and mobility simulators
  • Provides sample problems along with solutions/descriptions used to solve each, with performance comparisons
  • Covers current, relevant issues in mobile networks, like energy use, broadcasting performance, device mobility, and more

Evolutionary Algorithms for Mobile Ad Hoc Networks is an ideal book for researchers and students involved in mobile networks, optimization, advanced search techniques, and multi-objective optimization.

"About this title" may belong to another edition of this title.

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Hardcover. Condition: new. Hardcover. Describes how evolutionary algorithms (EAs) can be used to identify, model, and minimize day-to-day problems that arise for researchers in optimization and mobile networking Mobile ad hoc networks (MANETs), vehicular networks (VANETs), sensor networks (SNs), and hybrid networkseach of these require a designers keen sense and knowledge of evolutionary algorithms in order to help with the common issues that plague professionals involved in optimization and mobile networking. This book introduces readers to both mobile ad hoc networks and evolutionary algorithms, presenting basic concepts as well as detailed descriptions of each. It demonstrates how metaheuristics and evolutionary algorithms (EAs) can be used to help provide low-cost operations in the optimization processallowing designers to put some intelligence or sophistication into the design. It also offers efficient and accurate information on dissemination algorithms, topology management, and mobility models to address challenges in the field. Evolutionary Algorithms for Mobile Ad Hoc Networks: Instructs on how to identify, model, and optimize solutions to problems that arise in daily researchPresents complete and up-to-date surveys on topics like network and mobility simulatorsProvides sample problems along with solutions/descriptions used to solve each, with performance comparisonsCovers current, relevant issues in mobile networks, like energy use, broadcasting performance, device mobility, and more Evolutionary Algorithms for Mobile Ad Hoc Networks is an ideal book for researchers and students involved in mobile networks, optimization, advanced search techniques, and multi-objective optimization. This comprehensive guide describes how evolutionary algorithms (EA) may be used to identify, model, and optimize day-to-day problems that arise for researchers in optimization and mobile networking. Shipping may be from multiple locations in the US or from the UK, depending on stock availability. Seller Inventory # 9781118341131

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