語系:
繁體中文
English
說明(常見問題)
登入
回首頁
切換:
標籤
|
MARC模式
|
ISBD
QoS-Aware Virtual Network Embedding
~
SpringerLink (Online service)
QoS-Aware Virtual Network Embedding
紀錄類型:
書目-語言資料,印刷品 : Monograph/item
正題名/作者:
QoS-Aware Virtual Network Embedding/ by Chunxiao Jiang, Peiying Zhang.
作者:
Jiang, Chunxiao.
其他作者:
Zhang, Peiying.
面頁冊數:
X, 401 p. 1 illus.online resource. :
Contained By:
Springer Nature eBook
標題:
Artificial Intelligence. -
電子資源:
https://doi.org/10.1007/978-981-16-5221-9
ISBN:
9789811652219
QoS-Aware Virtual Network Embedding
Jiang, Chunxiao.
QoS-Aware Virtual Network Embedding
[electronic resource] /by Chunxiao Jiang, Peiying Zhang. - 1st ed. 2021. - X, 401 p. 1 illus.online resource.
Chapter 1. Introduction -- Chapter 2. Introduction of security requirements in VNE -- Chapter 3. Security Aware Virtual Network Embedding Algorithm using Information Entropy TOPSIS -- Chapter 4. Security-Aware Virtual Network Embedding Algorithm based on Reinforcement Learning -- Chapter 5. VNE Solution for Network Differentiated QoS and Security Requirements From the Perspective of Deep Reinforcement Learning -- Chapter 6. Resource Management and Security Scheme of ICPSs and IoT Based on VNE Algorithm -- Chapter 7. Description of service-aware requirements in VNE -- Chapter 8. Virtual Network Embedding based on Modified Genetic Algorithm -- Chapter 9. VNE-HPSO Virtual Network Embedding Algorithm based On Hybrid Particle Swarm Optimization -- Chapter 10. Topology based Reliable Virtual Network Embedding from a QoE Perspective -- Chapter 11. "DSCD Delay Sensitive Cross-Domain Virtual Network Embedding Algorithm" -- Chapter 12."A Multi-Domain Virtual Network Embedding Algorithm with Delay Prediction" -- Chapter 13. "Description of energy consumption requirements in VNE" -- Chapter 14. A"Multi-objective Enhanced Particle Swarm Optimization in Virtual Network Embedding" -- Chapter 15. "Incorporating Energy and Load Balance into Virtual Network Embedding Process" -- Chapter 16. "IoV Scenario Implementation of a Bandwidth Aware Algorithm in Wireless Network Communication Mode" -- Chapter 17. Description of load balance in VNE -- Chapter 18."A Multi-Domain VNE Algorithm based on Load Balancing in the IoT Networks" -- Chapter 19."Virtual Network Embedding based on Computing, Network and Storage Resource Constraints" -- Chapter 20. Virtual Network Embedding using Node Multiple Metrics based on Simplified ELECTRE Method -- Chapter 21."VNE Strategy based on Chaotic Hybrid Flower Pollination Algorithm Considering Multi-criteria Decision Making" -- Chapter 22. Conclusion.
As an important future network architecture, virtual network architecture has received extensive attention. Virtual network embedding (VNE) is one of the core services of network virtualization (NV). It provides solutions for various network applications from the perspective of virtual network resource allocation. The Internet aims to provide global users with comprehensive coverage. The network function requests of hundreds of millions of end users have brought great pressure to the underlying network architecture. VNE algorithm can provide effective support for the reasonable and efficient allocation of network resources, so as to alleviate the pressure off the Internet. At present, a distinctive feature of the Internet environment is that the quality of service (QoS) requirements of users are differentiated. Different regions, different times, and different users have different network function requirements. Therefore, network resources need to be reasonably allocated according to users' QoS requirements to avoid the waste of network resources. In this book, based on the analysis of the principle of VNE algorithm, we provide a VNE scheme for users with differentiated QoS requirements. We summarize the common user requirements into four categories: security awareness, service awareness, energy awareness, and load balance, and then introduce the specific implementation methods of various differentiated QoS algorithms. This book provides a variety of VNE solutions, including VNE algorithms for single physical domain, VNE algorithms for across multiple physical domains, VNE algorithms based on heuristic method, and VNE algorithms based on machine learning method.
ISBN: 9789811652219
Standard No.: 10.1007/978-981-16-5221-9doiSubjects--Topical Terms:
646849
Artificial Intelligence.
LC Class. No.: TK1-9971
Dewey Class. No.: 621.382
QoS-Aware Virtual Network Embedding
LDR
:04886nam a22003975i 4500
001
1058031
003
DE-He213
005
20211203200938.0
007
cr nn 008mamaa
008
220103s2021 si | s |||| 0|eng d
020
$a
9789811652219
$9
978-981-16-5221-9
024
7
$a
10.1007/978-981-16-5221-9
$2
doi
035
$a
978-981-16-5221-9
050
4
$a
TK1-9971
072
7
$a
TJK
$2
bicssc
072
7
$a
TEC041000
$2
bisacsh
072
7
$a
TJK
$2
thema
082
0 4
$a
621.382
$2
23
100
1
$a
Jiang, Chunxiao.
$4
aut
$4
http://id.loc.gov/vocabulary/relators/aut
$3
1226039
245
1 0
$a
QoS-Aware Virtual Network Embedding
$h
[electronic resource] /
$c
by Chunxiao Jiang, Peiying Zhang.
250
$a
1st ed. 2021.
264
1
$a
Singapore :
$b
Springer Singapore :
$b
Imprint: Springer,
$c
2021.
300
$a
X, 401 p. 1 illus.
$b
online resource.
336
$a
text
$b
txt
$2
rdacontent
337
$a
computer
$b
c
$2
rdamedia
338
$a
online resource
$b
cr
$2
rdacarrier
347
$a
text file
$b
PDF
$2
rda
505
0
$a
Chapter 1. Introduction -- Chapter 2. Introduction of security requirements in VNE -- Chapter 3. Security Aware Virtual Network Embedding Algorithm using Information Entropy TOPSIS -- Chapter 4. Security-Aware Virtual Network Embedding Algorithm based on Reinforcement Learning -- Chapter 5. VNE Solution for Network Differentiated QoS and Security Requirements From the Perspective of Deep Reinforcement Learning -- Chapter 6. Resource Management and Security Scheme of ICPSs and IoT Based on VNE Algorithm -- Chapter 7. Description of service-aware requirements in VNE -- Chapter 8. Virtual Network Embedding based on Modified Genetic Algorithm -- Chapter 9. VNE-HPSO Virtual Network Embedding Algorithm based On Hybrid Particle Swarm Optimization -- Chapter 10. Topology based Reliable Virtual Network Embedding from a QoE Perspective -- Chapter 11. "DSCD Delay Sensitive Cross-Domain Virtual Network Embedding Algorithm" -- Chapter 12."A Multi-Domain Virtual Network Embedding Algorithm with Delay Prediction" -- Chapter 13. "Description of energy consumption requirements in VNE" -- Chapter 14. A"Multi-objective Enhanced Particle Swarm Optimization in Virtual Network Embedding" -- Chapter 15. "Incorporating Energy and Load Balance into Virtual Network Embedding Process" -- Chapter 16. "IoV Scenario Implementation of a Bandwidth Aware Algorithm in Wireless Network Communication Mode" -- Chapter 17. Description of load balance in VNE -- Chapter 18."A Multi-Domain VNE Algorithm based on Load Balancing in the IoT Networks" -- Chapter 19."Virtual Network Embedding based on Computing, Network and Storage Resource Constraints" -- Chapter 20. Virtual Network Embedding using Node Multiple Metrics based on Simplified ELECTRE Method -- Chapter 21."VNE Strategy based on Chaotic Hybrid Flower Pollination Algorithm Considering Multi-criteria Decision Making" -- Chapter 22. Conclusion.
520
$a
As an important future network architecture, virtual network architecture has received extensive attention. Virtual network embedding (VNE) is one of the core services of network virtualization (NV). It provides solutions for various network applications from the perspective of virtual network resource allocation. The Internet aims to provide global users with comprehensive coverage. The network function requests of hundreds of millions of end users have brought great pressure to the underlying network architecture. VNE algorithm can provide effective support for the reasonable and efficient allocation of network resources, so as to alleviate the pressure off the Internet. At present, a distinctive feature of the Internet environment is that the quality of service (QoS) requirements of users are differentiated. Different regions, different times, and different users have different network function requirements. Therefore, network resources need to be reasonably allocated according to users' QoS requirements to avoid the waste of network resources. In this book, based on the analysis of the principle of VNE algorithm, we provide a VNE scheme for users with differentiated QoS requirements. We summarize the common user requirements into four categories: security awareness, service awareness, energy awareness, and load balance, and then introduce the specific implementation methods of various differentiated QoS algorithms. This book provides a variety of VNE solutions, including VNE algorithms for single physical domain, VNE algorithms for across multiple physical domains, VNE algorithms based on heuristic method, and VNE algorithms based on machine learning method.
650
2 4
$a
Artificial Intelligence.
$3
646849
650
2 4
$a
Computer Communication Networks.
$3
669310
650
1 4
$a
Communications Engineering, Networks.
$3
669809
650
0
$a
Artificial intelligence.
$3
559380
650
0
$a
Computer communication systems.
$3
1115394
650
0
$a
Electrical engineering.
$3
596380
700
1
$a
Zhang, Peiying.
$e
author.
$1
https://orcid.org/0000-0002-0990-5581
$4
aut
$4
http://id.loc.gov/vocabulary/relators/aut
$3
1363571
710
2
$a
SpringerLink (Online service)
$3
593884
773
0
$t
Springer Nature eBook
776
0 8
$i
Printed edition:
$z
9789811652202
776
0 8
$i
Printed edition:
$z
9789811652226
776
0 8
$i
Printed edition:
$z
9789811652233
856
4 0
$u
https://doi.org/10.1007/978-981-16-5221-9
912
$a
ZDB-2-SCS
912
$a
ZDB-2-SXCS
950
$a
Computer Science (SpringerNature-11645)
950
$a
Computer Science (R0) (SpringerNature-43710)
筆 0 讀者評論
多媒體
評論
新增評論
分享你的心得
Export
取書館別
處理中
...
變更密碼[密碼必須為2種組合(英文和數字)及長度為10碼以上]
登入