Paper Info
Title
Towards Optimal Hybrid Service Function Chain Embedding in Multi-Access Edge Computing
Abstract
The emerging multiaccess edge computing (MEC) architecture brings the needed computing resource to the network edge. Many 5G and Internet of Things (IoT) applications are latency sensitive and computation intensive in MEC systems. To flexibly provide and manage the network service requests in MEC systems, network function virtualization (NFV) can be employed to create a chain of service functions (SFs), namely, SF chain (SFC). Through SFC, the customer forwards user data to the edge server/cloud, and the edge server/cloud may return the processed results/models to the customer. When the forward and backward traffic is carrying different content, different SFs may be required for the forward and backward traffic, which requires a hybrid SFC (h-SFC). In this article, we study how to minimize the latency cost when embedding an h-SFC in MEC systems. We define a new problem called minimum latency hybrid SFC embedding (ML-HSFCE) and propose an algorithm, namely, optimal hybrid SFC embedding (Opt-HSFCE) to optimally embed a given h-SFC in MEC systems. Our extensive simulations and analysis show that the proposed Opt-HSFCE needs much less runtime compared with the brutal force algorithm and significantly outperforms the schemes that are directly extended from the existing techniques.
Year
DOI
Venue
2020
10.1109/JIOT.2019.2957961
IEEE Internet of Things Journal
Keywords
DocType
Volume
Substrates,Internet of Things,Cloud computing,Bandwidth,Servers,Machine learning,Edge computing
Journal
7
Issue
ISSN
Citations 
7
2327-4662
3
PageRank 
References 
Authors
0.38
0
4
Name
Order
Citations
PageRank
Danyang Zheng1123.91
Chengzong Peng2184.01
Xueting Liao371.12
Xiaojun Cao453074.55