Evidence map›Paper›PMID 37468481›Full record

ArticleScientific reports2023

Evolvable design of network-oriented services based on a core/periphery structure.

Shiori Takagi, Shin'ichi Arakawa, Masayuki Murata

Abstract read
In one paragraph

Article in Scientific reports, 2023. 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

3 authors.

Shiori TakagiGraduate School of Information Science and Technology, Osaka University, 1-5 Yamadaoka, Suita, Osaka, Japan. s-takagi@ist.osaka-u.ac.jp.
Shin'ichi ArakawaGraduate School of Information Science and Technology, Osaka University, 1-5 Yamadaoka, Suita, Osaka, Japan.
Masayuki MurataGraduate School of Information Science and Technology, Osaka University, 1-5 Yamadaoka, Suita, Osaka, Japan.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

In recent years, many new network-oriented services have emerged, and such services will need to be virtualized in the multi-access edge computing environment, which is currently being standardized along with fifth-generation network technology. The environment surrounding the service functions network changes over time, such as breaking changes of APIs, and these changes impact the services. The service design should be adaptable to user requirements and environmental changes for accommodating a large number of services at low cost. In addition, it is required not only to assume environmental changes when initially designing the service functions network, but also to enable the network to continue to change its structure to adapt to new environmental changes in the future. In this paper, we propose a method to evolve the entire network of service functions based on a core/periphery structure. The advantage of the core/periphery structure is that it helps reduce the costs for maintaining or changing services by dividing the service functions into core and periphery functions. We propose a method to evolve a service functions network based on this core/periphery structure. Our method evolves the structure of the service functions network at low cost by keeping the core and peripheral functions at the appropriate scale. In addition, our proposed method accommodates almost 100% of randomly generated service chains, and holds their length to less than twice the minimum chain length. Our simulation results reveal that the structure of the service functions networks can continue to evolve at a low cost and maintain a high service accommodation ratio.

Identifiers

PMID37468481
PMCPMC10356835

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Registered trials

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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.