ParaGraph: Subgraph-Level Network Function Composition With Delay Balanced Parallelism

Shen, Dian; Liu, Haoyang; Wang, Rui; Dong, Fang; Li, Fucun

doi:10.1109/access.2020.3035229

Cited by 2 publications

(2 citation statements)

References 33 publications

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“…To reduce SFs' processing delay, the authors in [13] proposed the technique of network function parallelism (NFP), which enables simultaneously executing multiple parallelable SFs. Based on that, works in [39]- [46] investigated how to apply NFP while considering dependencies among the required SFs. Here, dependencies represent executing orders of the required SFs.…”

Section: Related Workmentioning

confidence: 99%

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Towards Optimal Parallelism-Aware Service Chaining and Embedding

Zheng

Shen

Cao

et al. 2022

IEEE Trans. Netw. Serv. Manage.

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Emerging 5G technologies can significantly reduce end-to-end service latency for applications requiring strict quality of service (QoS). With network function virtualization (NFV), to complete a client's request from those applications, the client's data can sequentially go through multiple service functions (SFs) for processing/analysis but introduce additional processing delay. To reduce the processing delay from the serially-running SFs, network function parallelism (NFP) that allows multiple SFs to run in parallel is introduced. In this work, we study how to apply NFP into the SF chaining and embedding process such that the latency, including processing and propagation delays, can be jointly minimized. We introduce a novel augmented graph to address the parallel relationship constraint among the required SFs. Considering parallel relationship constraints, we propose a novel problem called parallelism-aware service function chaining and embedding (PSFCE). For this problem, we propose a near-optimal maximum parallel block gain (MPBG) first optimization algorithm when computing resources at each physical node are enough to host the required SFs. When computing resources are limited, we propose a logarithm-approximate algorithm, called parallelism-aware SFs deployment (PSFD), to jointly optimize processing and propagation delays. We conduct extensive simulations on multiple network scenarios to evaluate the performances of our schemes. Accordingly, we find that (i) MPBG is near-optimal, (ii) the optimization of end-to-end service latency largely depends on the processing delay in small networks and is impacted more by the propagation delay in large networks, and (iii) PSFD outperforms the schemes directly extended from existing works regarding end-to-end latency.

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Section: Related Workmentioning

confidence: 99%

“…That is, if SF1 is parallelizable with SF2 and SF3, then SF2 can co-execute with SF3 as well. In [46], the authors proposed a scheme, called delay-balanced parallelism, to balance the overhead and the processing delay of running the required SFs. However, the above works hardly take the parallel relationship constraints into account.…”

Section: Related Workmentioning

confidence: 99%

Towards Optimal Parallelism-Aware Service Chaining and Embedding

Zheng

Shen

Cao

et al. 2022

IEEE Trans. Netw. Serv. Manage.

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show abstract

Towards Optimal Parallelism-Aware Service Chaining and Embedding

Zheng¹,

Shen²,

Cao³

et al. 2021

Preprint

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<div>Emerging 5G technologies can significantly reduce end-to-end service latency for applications requiring strict quality of service (QoS). With network function virtualization (NFV), to complete a client’s request from those applications, the client’s data can sequentially go through multiple service functions (SFs) for processing/analysis but introduce additional processing delay. To reduce the processing delay from the serially-running SFs, network function parallelism (NFP) that allows multiple SFs to run in parallel is introduced. In this work, we study how to apply NFP into the SF chaining and embedding process such that the latency, including processing and propagation delays, can be jointly minimized. We introduce a novel augmented graph to address the parallel relationship constraint among the required SFs. Considering parallel relationship constraints, we propose a novel problem called parallelism-aware service function chaining and embedding (PSFCE). For this problem, we propose a near-optimal maximum parallel block gain (MPBG) first optimization algorithm when computing resources at each physical node are enough to host the required SFs. When computing resources are limited, we propose a logarithm-approximate algorithm, called parallelism-aware SFs deployment (PSFD), to jointly optimize processing and propagation delays. We conduct extensive simulations on multiple network scenarios to evaluate the performances of our schemes. Accordingly, we find that (i) MPBG is near-optimal, (ii) the optimization of end-to-end service latency largely depends on the processing delay in small networks and is impacted more by the propagation delay in large networks, and (iii) PSFD outperforms the schemes directly extended from existing works regarding end-to-end latency.</div>

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ParaGraph: Subgraph-Level Network Function Composition With Delay Balanced Parallelism

Cited by 2 publications

References 33 publications

Towards Optimal Parallelism-Aware Service Chaining and Embedding

Towards Optimal Parallelism-Aware Service Chaining and Embedding

Towards Optimal Parallelism-Aware Service Chaining and Embedding

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