Efficient service reconfiguration with partial virtual network function migration

计算机科学 控制重构 功能(生物学) 服务(商务) 分布式计算 虚拟网络 网络功能虚拟化 计算机网络 嵌入式系统 操作系统 云计算 经济 进化生物学 经济 生物
作者
Dongquan Liu,Zhengyan Zhou,Dong Zhang,Kaiwei Guo,Yanni Wu,Chunming Wu
出处
期刊:Computer Networks [Elsevier]
卷期号:241: 110205-110205 被引量:3
标识
DOI:10.1016/j.comnet.2024.110205
摘要

Network Function Virtualization (NFV) decouples network functions from dedicated hardware devices into Virtual Network Functions (VNFs). These VNFs are chained in order as a Service Function Chain (SFC) to provision flexible and efficient services. When service requests dynamically increase, the intensive workloads often lead to node overloads and further impact the Quality of Service (QoS). Existing works address this problem by migrating VNFs from overload nodes to other low-load nodes, known as VNF migration. However, when a VNF is shared by multiple SFCs, migrating the VNF will change the mapping relationships between these SFCs and the physical network (nodes and links). That may make some SFCs traverse more links and increase their propagation latency. That violates the demand of users for low-latency services. In this paper, to minimize the impact of VNF migration on SFC latency, we propose partial VNF migration. It migrates only partial VNFs within these SFCs to minimize the overall SFC latency while reducing migration costs. As such, we leverage partial VNF migration for efficient latency minimization with the formulation of an integer linear programming (ILP) model. Given the NP-hard nature of the problem, we propose a dynamic latency-aware partial VNF migration algorithm to reduce node overloads and minimize SFC latency. Evaluation indicates that the proposed approach has 12.7%–21.8% lower average SFC latency and 12.5%–48.5% less migration cost than state-of-the-art VNF migration algorithms. And it demonstrates about 90% shorter execution time with similar minimization performance, compared to other SFC reconfiguration algorithms.
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
大幅提高文件上传限制,最高150M (2024-4-1)

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
沐眿完成签到 ,获得积分10
1秒前
enchanted发布了新的文献求助10
1秒前
Up发布了新的文献求助10
3秒前
科研通AI2S应助sunishope采纳,获得10
4秒前
4秒前
嵐嵐完成签到,获得积分10
4秒前
4秒前
4秒前
6秒前
ggyyf完成签到,获得积分10
7秒前
搜集达人应助wx采纳,获得10
8秒前
8秒前
Meizoso发布了新的文献求助20
8秒前
9秒前
冰魄之弓发布了新的文献求助10
9秒前
SciGPT应助jiamso采纳,获得10
10秒前
无花果应助科研通管家采纳,获得10
10秒前
我是老大应助科研通管家采纳,获得10
10秒前
个性归尘应助科研通管家采纳,获得20
10秒前
ferrycake应助科研通管家采纳,获得20
10秒前
Lucas应助科研通管家采纳,获得10
10秒前
险胜应助科研通管家采纳,获得30
11秒前
11秒前
充电宝应助科研通管家采纳,获得10
11秒前
李健应助科研通管家采纳,获得10
11秒前
科研通AI2S应助科研通管家采纳,获得10
11秒前
英姑应助科研通管家采纳,获得10
11秒前
良辰应助科研通管家采纳,获得10
11秒前
脑洞疼应助科研通管家采纳,获得10
11秒前
yiluxiangbei发布了新的文献求助10
11秒前
orixero应助科研通管家采纳,获得10
11秒前
桐桐应助科研通管家采纳,获得10
11秒前
12秒前
12秒前
12秒前
12秒前
ggyyf发布了新的文献求助10
13秒前
好运藏在善良里应助ATLI采纳,获得10
17秒前
17秒前
大个应助卢伟采纳,获得10
18秒前
高分求助中
Licensing Deals in Pharmaceuticals 2019-2024 3000
Cognitive Paradigms in Knowledge Organisation 2000
Effect of reactor temperature on FCC yield 2000
Introduction to Spectroscopic Ellipsometry of Thin Film Materials Instrumentation, Data Analysis, and Applications 1800
Natural History of Mantodea 螳螂的自然史 1000
A Photographic Guide to Mantis of China 常见螳螂野外识别手册 800
How Maoism Was Made: Reconstructing China, 1949-1965 800
热门求助领域 (近24小时)
化学 医学 生物 材料科学 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 基因 遗传学 催化作用 物理化学 免疫学 量子力学 细胞生物学
热门帖子
关注 科研通微信公众号,转发送积分 3313969
求助须知:如何正确求助?哪些是违规求助? 2946329
关于积分的说明 8529696
捐赠科研通 2621983
什么是DOI,文献DOI怎么找? 1434250
科研通“疑难数据库(出版商)”最低求助积分说明 665190
邀请新用户注册赠送积分活动 650774