학술논문

Holu: Power-Aware and Delay-Constrained VNF Placement and Chaining
Document Type
Periodical
Source
IEEE Transactions on Network and Service Management IEEE Trans. Netw. Serv. Manage. Network and Service Management, IEEE Transactions on. 18(2):1524-1539 Jun, 2021
Subject
Communication, Networking and Broadcast Technologies
Computing and Processing
Routing
Power demand
Delays
Servers
Optimization
Approximation algorithms
Service function chaining
Power optimization
power efficiency
energy efficiency
VNF placement
service function chaining
Language
ISSN
1932-4537
2373-7379
Abstract
Service function chains (SFCs) are an ordered set of virtual network functions (VNFs) which can realize a specific network service. Enabled by virtualization technologies, these VNFs are hosted on physical machines (PMs), and interconnected by network switches. In today networks, these resources are usually under-utilized and/or over-provisioned, resulting in power-inefficient deployments. To improve power-efficiency, SFCs should be deployed utilizing the minimum number of PMs and network equipment, which are not concomitant. Considering the existing PM and switch power consumption models and their resource constraints, we formulate the power-aware and delay-constrained joint VNF placement and routing (PD-VPR) problem as an Integer Linear Program (ILP). Due to the NP-completeness of the problem, we propose Holu , a fast heuristic framework that efficiently solves the PD-VPR problem in an online manner. Specifically, Holu decomposes the PD-VPR into two sub-problems and solve them sequentially: i) a VNF placement problem that consists of mapping the VNFs to PMs using a centrality-based ranking method, and ii) a routing problem that efficiently splits the delay budget between consecutive VNFs of the SFC, and finds a Delay-Constrained Least-Cost (DCLC) shortest-path through the selected PMs (hosting VNFs) using the Lagrange Relaxation based Aggregated Cost (LARAC) algorithm. Our simulation results indicate that Holu outperforms the state-of-the-art algorithms in terms of total power consumption and acceptance rate by 24.7% and 31%, respectively.