计算机科学
云计算
虚拟网络
在线算法
近似算法
服务器
分布式计算
延迟(音频)
竞争分析
GSM演进的增强数据速率
虚拟机
虚拟化
软件部署
数学优化
算法
计算机网络
数学
人工智能
操作系统
上下界
数学分析
电信
作者
Yingling Mao,Xiaojun Shang,Yu Liu,Yuanyuan Yang
标识
DOI:10.1109/tc.2023.3347671
摘要
Network Function Virtualization (NFV) is becoming one of the most popular paradigms for providing cost-efficient, flexible, and easily-managed network services by migrating network functions from dedicated hardware to commercial general-purpose servers. Despite the benefits of NFV, it remains a challenge to deploy Service Function Chains (SFCs), placing virtual network functions (VNFs) and routing the corresponding flow between VNFs, in the edge-cloud continuum with the objective of jointly optimizing resource and latency. In this paper, we formulate the SFC Deployment Problem (SFCD). To address this NP-hard problem, we first introduce a constant approximation algorithm for a simplified SFCD limited at the edge, followed by a promotional algorithm for SFCD in the edge-cloud continuum, which also maintains a provable constant approximation ratio. Furthermore, we provide an online algorithm for deploying sequentially-arriving SFCs in the edge-cloud continuum and prove the online algorithm achieves a constant competitive ratio. Extensive simulations demonstrate that on average, the total costs of our offline and online algorithms are around 1.79 and 1.80 times the optimal results, respectively, and significantly smaller than the theoretical bounds. In addition, our proposed algorithms consistently outperform the popular benchmarks, showing the superiority of our algorithms.
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