Evidence map›Paper›PMID 40218756›Full record

ArticleSensors (Basel, Switzerland)2025

Dynamic RSVP in Modern Networks for Advanced Resource Control with P4 Data Plane.

Pin-An Pan, Wen-Long Chin, Yen-Chun Huang, Yu-Xiang Huang, Cheng-Hsien Yu

Abstract read
In one paragraph

Article in Sensors (Basel, Switzerland), 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors.

Pin-An PanVLSI Signal Processing Laboratory, Department of Engineering Science, National Cheng Kung University, Tainan 701, Taiwan.
Wen-Long ChinVLSI Signal Processing Laboratory, Department of Engineering Science, National Cheng Kung University, Tainan 701, Taiwan.ORCID 0000-0002-5914-6253
Yen-Chun HuangVLSI Signal Processing Laboratory, Department of Engineering Science, National Cheng Kung University, Tainan 701, Taiwan.
Yu-Xiang HuangVLSI Signal Processing Laboratory, Department of Engineering Science, National Cheng Kung University, Tainan 701, Taiwan.
Cheng-Hsien YuVLSI Signal Processing Laboratory, Department of Engineering Science, National Cheng Kung University, Tainan 701, Taiwan.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

This study focuses on leveraging the emerging Software-Defined Networking (SDN) technology, P4, to design a data plane for the Resource Reservation Protocol (RSVP) that can be applied in various scenarios, including both wired and wireless networks. This research explores the signaling mechanisms of the RSVP protocol, consolidates the data plane processing requirements, and ensures compliance with RSVP session Quality of Service (QoS) demands. Additionally, this study introduces the architecture, syntax, and external functionalities of the P4 language, which are utilized to develop the data plane required for RSVP-based resource reservation. Various parameters are pre-configured to enable the control plane to efficiently integrate RSVP reservation information into the data plane. Furthermore, Mininet is employed to create a virtual network topology, along with the BMv2 software switch, to evaluate whether the proposed system can fulfill RSVP's end-to-end QoS guarantees. Different traffic transmission scenarios are examined to validate the system's capability in accurately managing bandwidth allocation, latency, priority configuration, and packet counting for end-to-end QoS services.

Indexed as

BMv2 software switchmininetP4 languageQuality of Service (QoS)resource reservation protocol (RSVP)software-defined networking (SDN)wireless networks

Identifiers

PMID40218756
PMCPMC11991447

What OpenQuestion holds

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Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.