Holu: Power-Aware and Delay-Constrained VNF Placement and Chaining
| Autor: | Amaury Van Bemten, Carmen Mas-Machuca, Amir Varasteh, Basavaraj Madiwalar, Wolfgang Kellerer |
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| Rok vydání: | 2020 |
| Předmět: |
business.product_category
Linear programming Computer Networks and Communications Computer science Heuristic (computer science) Distributed computing Approximation algorithm 020206 networking & telecommunications 02 engineering and technology Networking hardware ddc Network service 0202 electrical engineering electronic engineering information engineering Network switch Electrical and Electronic Engineering Routing (electronic design automation) business Virtual network |
| Popis: | 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. |
| Databáze: | OpenAIRE |
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