Dynamic, Latency-Optimal vNF Placement at the Network Edge

Cziva, R., Anagnostopoulos, C. and Pezaros, D. P. (2018) Dynamic, Latency-Optimal vNF Placement at the Network Edge. In: IEEE Conference on Computer Communications (INFOCOM 2018), Honolulu, HI, USA, 15-19 Apr 2018, pp. 693-701. ISBN 9781538641286 (doi: 10.1109/INFOCOM.2018.8486021)

153654.pdf - Accepted Version



Future networks are expected to support low-latency, context-aware and user-specific services in a highly flexible and efficient manner. One approach to support emerging use cases such as, e.g., virtual reality and in-network image processing is to introduce virtualized network functions (vNF)s at the edge of the network, placed in close proximity to the end users to reduce end-to-end latency, time-to-response, and unnecessary utilisation in the core network. While placement of vNFs has been studied before, it has so far mostly focused on reducing the utilisation of server resources (i.e., minimising the number of servers required in the network to run a specific set of vNFs), and not taking network conditions into consideration such as, e.g., end-to-end latency, the constantly changing network dynamics, or user mobility patterns. In this paper, we formulate the Edge vNF placement problem to allocate vNFs to a distributed edge infrastructure, minimising end-to-end latency from all users to their associated vNFs. We present a way to dynamically re-schedule the optimal placement of vNFs based on temporal network-wide latency fluctuations using optimal stopping theory. We then evaluate our dynamic scheduler over a simulated nation-wide backbone network using real-world ISP latency characteristics. We show that our proposed dynamic placement scheduler minimises vNF migrations compared to other schedulers (e.g., periodic and always-on scheduling of a new placement), and offers Quality of Service guarantees by not exceeding a maximum number of latency violations that can be tolerated by certain applications.

Item Type:Conference Proceedings
Glasgow Author(s) Enlighten ID:Anagnostopoulos, Dr Christos and Pezaros, Professor Dimitrios and Cziva, Mr Richard
Authors: Cziva, R., Anagnostopoulos, C., and Pezaros, D. P.
College/School:College of Science and Engineering > School of Computing Science
Copyright Holders:Copyright © 2018 IEEE
Publisher Policy:Reproduced in accordance with the copyright policy of the publisher
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