東華大學圖書館 |

Language: English

Help

回圖書館首頁

手機版館藏查詢

Back

Switch To: Labeled | MARC Mode | ISBD

Dynamic resource management in servi...

Zhuang, Weihua.

Linked to FindBook

Google Book

Amazon

博客來

Dynamic resource management in service-oriented core networks

Record Type:	Electronic resources : Monograph/item
Title/Author:	Dynamic resource management in service-oriented core networks/ by Weihua Zhuang, Kaige Qu.
Author:	Zhuang, Weihua.
other author:	Qu, Kaige.
Published:	Cham :Springer International Publishing : : 2021.,
Description:	xii, 173 p. :ill. (some col.), digital ;24 cm.
Contained By:	Springer Nature eBook
Subject:	Wireless communication systems - Management. -
Online resource:	https://doi.org/10.1007/978-3-030-87136-9
ISBN:	9783030871369

Dynamic resource management in service-oriented core networks
Zhuang, Weihua.

Dynamic resource management in service-oriented core networks[electronic resource] /by Weihua Zhuang, Kaige Qu. - Cham :Springer International Publishing :2021. - xii, 173 p. :ill. (some col.), digital ;24 cm. - Wireless networks,2366-1445. - Wireless networks..

This book provides a timely and comprehensive study of dynamic resource management for network slicing in service-oriented fifth-generation (5G) and beyond core networks. This includes the perspective of developing efficient computation resource provisioning and scheduling solutions to guarantee consistent service performance in terms of end-to-end (E2E) data delivery delay. Based on a simplified M/M/1 queueing model with Poisson traffic arrivals, an optimization model for flow migration is presented to accommodate the large-timescale changes in the average traffic rates with average E2E delay guarantee, while addressing a trade-off between load balancing and flow migration overhead. To overcome the limitations of Poisson traffic model, the authors present a machine learning approach for dynamic VNF resource scaling and migration. The new solution captures the inherent traffic patterns in a real-world traffic trace with non-stationary traffic statistics in large timescale, predicts resource demands for VNF resource scaling, and triggers adaptive VNF migration decision making, to achieve load balancing, migration cost reduction, and resource overloading penalty suppression in the long run. Both supervised and unsupervised machine learning tools are investigated for dynamic resource management. To accommodate the traffic dynamics in small time granularities, the authors present a dynamic VNF scheduling scheme to coordinate the scheduling among VNFs of multiple services, which achieves network utility maximization with delay guarantee for each service. Researchers and graduate students working in the areas of electrical engineering, computing engineering and computer science will find this book useful as a reference or secondary text. Professionals in industry seeking solutions to dynamic resource management for 5G and beyond networks will also want to purchase this book.

ISBN: 9783030871369

Standard No.: 10.1007/978-3-030-87136-9doiSubjects--Topical Terms:

875431
Wireless communication systems
--Management.

LC Class. No.: TK5103.2 / .Z48 2021

Dewey Class. No.: 621.38215

Dynamic resource management in service-oriented core networks
LDR:02935nmm 22003255a 4500 001 2258690
003 DE-He213
005 20211103221833.0
006 m d
007 cr nn 008maaau
008 220422s2021 sz s 0 eng d
020 $a 9783030871369 $q (electronic bk.)
020 $a 9783030871352 $q (paper)
024 7 $a 10.1007/978-3-030-87136-9 $2 doi
035 $a 978-3-030-87136-9
040 $a GP $c GP
041 0 $a eng
050 4 $a TK5103.2 $b .Z48 2021
072 7 $a UKN $2 bicssc
072 7 $a COM075000 $2 bisacsh
072 7 $a UKN $2 thema
082 0 4 $a 621.38215 $2 23
090 $a TK5103.2 $b .Z63 2021
100 1 $a Zhuang, Weihua. $3 1258327
245 1 0 $a Dynamic resource management in service-oriented core networks $h [electronic resource] / $c by Weihua Zhuang, Kaige Qu.
260 $a Cham : $b Springer International Publishing : $b Imprint: Springer, $c 2021.
300 $a xii, 173 p. : $b ill. (some col.), digital ; $c 24 cm.
490 1 $a Wireless networks, $x 2366-1445
520 $a This book provides a timely and comprehensive study of dynamic resource management for network slicing in service-oriented fifth-generation (5G) and beyond core networks. This includes the perspective of developing efficient computation resource provisioning and scheduling solutions to guarantee consistent service performance in terms of end-to-end (E2E) data delivery delay. Based on a simplified M/M/1 queueing model with Poisson traffic arrivals, an optimization model for flow migration is presented to accommodate the large-timescale changes in the average traffic rates with average E2E delay guarantee, while addressing a trade-off between load balancing and flow migration overhead. To overcome the limitations of Poisson traffic model, the authors present a machine learning approach for dynamic VNF resource scaling and migration. The new solution captures the inherent traffic patterns in a real-world traffic trace with non-stationary traffic statistics in large timescale, predicts resource demands for VNF resource scaling, and triggers adaptive VNF migration decision making, to achieve load balancing, migration cost reduction, and resource overloading penalty suppression in the long run. Both supervised and unsupervised machine learning tools are investigated for dynamic resource management. To accommodate the traffic dynamics in small time granularities, the authors present a dynamic VNF scheduling scheme to coordinate the scheduling among VNFs of multiple services, which achieves network utility maximization with delay guarantee for each service. Researchers and graduate students working in the areas of electrical engineering, computing engineering and computer science will find this book useful as a reference or secondary text. Professionals in industry seeking solutions to dynamic resource management for 5G and beyond networks will also want to purchase this book.
650 0 $a Wireless communication systems $x Management. $3 875431
650 0 $a Adaptive routing (Computer network management) $3 3531383
650 1 4 $a Computer Communication Networks. $3 775497
650 2 4 $a Wireless and Mobile Communication. $3 3338159
650 2 4 $a Machine Learning. $3 3382522
700 1 $a Qu, Kaige. $3 3531382
710 2 $a SpringerLink (Online service) $3 836513
773 0 $t Springer Nature eBook
830 0 $a Wireless networks. $3 2162432
856 4 0 $u https://doi.org/10.1007/978-3-030-87136-9
950 $a Computer Science (SpringerNature-11645)