An efficient virtualized network function deployment scheme for service function chain using deep Q‐network

计算机科学 服务质量 能源消耗 虚拟网络 计算机网络 虚拟化 体验质量 分布式计算 云计算 操作系统 生态学 生物
作者
Weicheng Wu,Shang‐Juh Kao,Fu‐Min Chang
出处
期刊:International Journal of Communication Systems [Wiley]
卷期号:35 (6) 被引量:3
标识
DOI:10.1002/dac.5084
摘要

Summary Virtualized network functions (VNFs) are virtualized network services running on the network functions virtualization infrastructure in order to replace physical hardware. Integrating with software defined networking and network functions virtualization, internet service providers (ISPs) can chain VNFs together, called service function chain (SFC), to provide various network service demands with virtual links. Many studies have proposed for the VNFs deployment under different objectives, for example, energy, delay, quality of service (QoS), and quality of experience (QoE). From the aspects of both ISPs and customers, both energy consumption and QoE are the primary concerns for the purpose of operating expense reduction and users' satisfaction. This paper proposes a QoS/QoE/energy‐aware deep Q‐network (DQN)‐based scheme, called DQN‐QQE for VNFs deployment under the consideration of both energy consumption and QoE requirement with QoS constraints. The reward of the proposed scheme is formulated by the Weber‐Fechner law and the exponential interdependency of QoE and QoS (IQX) hypothesis. Afterwards, we compared the proposed DQN‐QQE to the QoS/QoE‐aware approach DQN‐Q2‐SFC, brute force, and randomness in terms of energy, QoE, error rate, and processing time. The simulation results revealed that DQN‐QQE is more stable and is better than DQN‐Q2‐SFC and randomness approach in terms of energy, QoE, and error rate. The average processing time and energy consumption of the proposed DQN‐QQE was 43% and 11% less than DQN‐Q2‐SFC, respectively. Although brute force approach is better than others in terms of energy, QoE, and error rate, the processing time of brute force approach is nearly 20 times larger than the proposed DQN‐QQE.
最长约 10秒,即可获得该文献文件

科研通智能强力驱动
Strongly Powered by AbleSci AI
更新
PDF的下载单位、IP信息已删除 (2025-6-4)

科研通是完全免费的文献互助平台,具备全网最快的应助速度,最高的求助完成率。 对每一个文献求助,科研通都将尽心尽力,给求助人一个满意的交代。
实时播报
星期八发布了新的文献求助10
刚刚
星星要睡觉啦完成签到 ,获得积分10
2秒前
6秒前
minmin完成签到,获得积分10
7秒前
胖胖玩啊玩完成签到 ,获得积分10
7秒前
May完成签到,获得积分10
8秒前
CodeCraft应助LL爱读书采纳,获得10
8秒前
8秒前
8秒前
9秒前
11秒前
12秒前
lin发布了新的文献求助10
12秒前
14秒前
15秒前
蔡宇滔发布了新的文献求助10
15秒前
16秒前
17秒前
WWWUBING完成签到,获得积分10
19秒前
笑点低的元枫完成签到 ,获得积分10
19秒前
Marilyn完成签到 ,获得积分10
20秒前
BHI完成签到 ,获得积分10
21秒前
21秒前
tramp应助那天再也不见采纳,获得10
21秒前
yuliuism完成签到,获得积分10
23秒前
24秒前
drift完成签到,获得积分10
26秒前
28秒前
蔡宇滔完成签到,获得积分10
28秒前
田様应助热心市民小张采纳,获得10
28秒前
温冰雪应助kami采纳,获得10
29秒前
hayden发布了新的文献求助30
30秒前
lm发布了新的文献求助10
31秒前
32秒前
天天快乐应助利物鸟贝拉采纳,获得30
33秒前
鱼蛋丸子完成签到,获得积分10
33秒前
彭于晏应助兔兔要睡觉采纳,获得10
33秒前
小薇薇爱做梦完成签到,获得积分10
36秒前
36秒前
Aippan发布了新的文献求助10
37秒前
高分求助中
The Mother of All Tableaux Order, Equivalence, and Geometry in the Large-scale Structure of Optimality Theory 2400
Ophthalmic Equipment Market by Devices(surgical: vitreorentinal,IOLs,OVDs,contact lens,RGP lens,backflush,diagnostic&monitoring:OCT,actorefractor,keratometer,tonometer,ophthalmoscpe,OVD), End User,Buying Criteria-Global Forecast to2029 2000
Optimal Transport: A Comprehensive Introduction to Modeling, Analysis, Simulation, Applications 800
Official Methods of Analysis of AOAC INTERNATIONAL 600
ACSM’s Guidelines for Exercise Testing and Prescription, 12th edition 588
T/CIET 1202-2025 可吸收再生氧化纤维素止血材料 500
Interpretation of Mass Spectra, Fourth Edition 500
热门求助领域 (近24小时)
化学 材料科学 医学 生物 工程类 有机化学 生物化学 物理 内科学 纳米技术 计算机科学 化学工程 复合材料 遗传学 基因 物理化学 催化作用 冶金 细胞生物学 免疫学
热门帖子
关注 科研通微信公众号,转发送积分 3951021
求助须知:如何正确求助?哪些是违规求助? 3496420
关于积分的说明 11081962
捐赠科研通 3226913
什么是DOI,文献DOI怎么找? 1784010
邀请新用户注册赠送积分活动 868130
科研通“疑难数据库(出版商)”最低求助积分说明 801003