Loughborough University
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Position-aware packet loss optimization on service function chain placement

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posted on 2023-02-23, 14:28 authored by Wenjie Liang, Chengxiang Li, Lin Cui, Fung Po TsoFung Po Tso

The advent of Network Function Virtualization (NFV) and Service Function Chains (SFCs) unleashes the power of dynamic creation of network services using Virtual Network Functions (VNFs). This is of great interest to network operators since poor service quality and resource wastage can potentially hurt their revenue in the long term. However, the study shows with a set of test-bed experiments that packet loss at certain positions (i.e., different VNFs) in an SFC can cause various degrees of resource wastage and performance degradation because of repeated upstream processing and transmission of retransmitted packets.

To overcome this challenge, this study focuses on resource scheduling and deployment of SFCs while considering packet loss positions. This study developed a novel SFC packet dropping cost model and formulated an SFC scheduling problem that aims to minimize overall packet dropping cost as a Mixed-Integer Linear Programming (MILP) and proved that it is NP-hard. In this study, Palosis proposed as an efficient scheme in exploiting the functional characteristics of VNFs and their positions in SFCs for scheduling resources and deployment to optimize packet dropping cost. Extensive experiment results show that Palos can achieve up to 42.73% improvement on packet dropping cost and up to 33.03% reduction on average SFC latency when compared with two other state-of-the-art schemes.


National Natural Science Foundation of China (NSFC) No. 62172189 and 61772235

Natural Science Foundation of Guangdong Province No. 2020A1515010771

Science and Technology Program of Guangzhou No. 202002030372

SYNC: Synergistic Network Policy Management for Cloud Data Centres

Engineering and Physical Sciences Research Council

Find out more...

FRuIT: The Federated RaspberryPi Micro-Infrastructure Testbed

Engineering and Physical Sciences Research Council

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Innovate UK grant 106199–47198



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  • Computer Science

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Digital Communications and Networks




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© Chongqing University of Posts and Telecommunications

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Dr Posco Tso. Deposit date: 23 February 2023