A Lightweight SFC Embedding Framework in SDN/NFV-Enabled Wireless Network Based on Reinforcement Learning

Chen, Jia; Cheng, Xin; Chen, Jing; Zhang, Hongke

doi:10.1109/jsyst.2021.3111972

Cited by 10 publications

(2 citation statements)

References 37 publications

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“…In Reference 38, authors propose a lightweight SFC embedding framework for wireless networks. Authors used Q‐learning to create an algorithm to minimize the end‐to‐end delay and the SFC acceptance ratio.…”

Section: Related Workmentioning

confidence: 99%

“…This is the closest of the works presented in this article, but significant differences can be noted. First, our focus is on SFC availability, while the work presented in Reference 38 addressed the wired and wireless delay. With regard to the implementation, we use the service resource of Kubernetes to forward the data between the VNFs, avoiding using a secondary tool for the data plane, while Reference 38 uses the ONOS.…”

Section: Related Workmentioning

confidence: 99%

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SPIDER: An availability‐aware framework for the service function chain placement in distributed scenarios

et al. 2022

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The network function virtualization (NFV) paradigm replaces hardware-dependent network functions by virtual network functions (VNFs) that can be deployed in commodity hardware, including legacy servers. Consequently, the use of NFV is expected to reduce operating and capital expenses, as well as improve service deployment operation and management flexibility.For many use cases, the VNFs must be visited and invoked following a specific order of execution in order to compose a complete network service, named service function chain (SFC). Nonetheless, despite the benefits from NFV and SFC virtualization technologies, their introduction must not harm network performance and service availability. On the one hand, redundancy is seen by network service planners as a mechanism well established to combat availability issues. At same time, there is a goal to optimize resource utilization in order to reduce operational expenditure. In this article, we share our experience in the design use of a framework, named SPIDER, focused on SFC placement that considers the network infrastructure condition and the required SFC availability to define the placement strategy. The SPIDER monitors the status of infrastructure nodes and links and defines which servers the VNFs should be placed on and the number of redundant replicas needed. We present a proof-of-concept of SPIDER using Kubernetes to launch the VNFs as containers. We also use Kubernetes to forward the traffic between the VNFs, composing the service chain. We perform experiments to evaluate the runtime of SPIDER and the SFC delay under different network conditions.

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Section: Related Workmentioning

confidence: 99%

Section: Related Workmentioning

confidence: 99%