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portada Cloud-Based Big Data Analytics in Vehicular Ad-Hoc Networks
Type
Physical Book
Language
Inglés
Pages
300
Format
Hardcover
Dimensions
27.9 x 21.6 x 2.1 cm
Weight
1.08 kg.
ISBN13
9781799827641

Cloud-Based Big Data Analytics in Vehicular Ad-Hoc Networks

Rao, Ram Shringar ; Singh, Nanhay ; Kaiwartya, Omprakash (Author) · Engineering Science Reference · Hardcover

Cloud-Based Big Data Analytics in Vehicular Ad-Hoc Networks - Rao, Ram Shringar ; Singh, Nanhay ; Kaiwartya, Omprakash

Physical Book

£ 291.96

  • Condition: New
Origin: U.S.A. (Import costs included in the price)
It will be shipped from our warehouse between Tuesday, July 02 and Friday, July 12.
You will receive it anywhere in United Kingdom between 1 and 3 business days after shipment.

Synopsis "Cloud-Based Big Data Analytics in Vehicular Ad-Hoc Networks"

Vehicular traffic congestion and accidents remain universal issues in today's world. Due to the continued growth in the use of vehicles, optimizing traffic management operations is an immense challenge. To reduce the number of traffic accidents, improve the performance of transportation systems, enhance road safety, and protect the environment, vehicular ad-hoc networks have been introduced. Current developments in wireless communication, computing paradigms, big data, and cloud computing enable the enhancement of these networks, equipped with wireless communication capabilities and high-performance processing tools. Cloud-Based Big Data Analytics in Vehicular Ad-Hoc Networks is a pivotal reference source that provides vital research on cloud and data analytic applications in intelligent transportation systems. While highlighting topics such as location routing, accident detection, and data warehousing, this publication addresses future challenges in vehicular ad-hoc networks and presents viable solutions. This book is ideally designed for researchers, computer scientists, engineers, automobile industry professionals, IT practitioners, academicians, and students seeking current research on cloud computing models in vehicular networks.

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