Evidence map›Paper›PMID 39650459›Full record

ArticlePeerJ. Computer science2024

Optimizing 5G network performance with dynamic resource allocation, robust encryption and Quality of Service (QoS) enhancement.

Abdullah M Alashjaee, Sumit Kushwaha, Hayam Alamro, Asma Abbas Hassan, Fuhid Alanazi, Abdullah Mohamed

Abstract read
In one paragraph

Article in PeerJ. Computer science, 2024. 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

6 authors.

Abdullah M Alashjaee *Department of Computer Sciences, Faculty of Computing and Information Technology, Northern Border University, Rafha, Saudi Arabia.ORCID 0000-0002-8682-6609
Sumit Kushwaha *Department of Computer Applications, University Institute of Computing, Chandigarh University, Mohali, Punjab, India.ORCID 0000-0002-3830-1736
Hayam AlamroDepartment of Information Systems, College of Computer and Information Sciences, Princess Nourah bint Abdulrahman University, Riyad, Saudi Arabia.
Asma Abbas HassanDepartment of Computer Science, Community College-Girls Section, King Khalid University, Aseer, Saudi Arabia.
Fuhid AlanaziDepartment of Information Systems, Faculty of Computer and Information Systems, Islamic University of Madinah, Medina, Saudi Arabia.
Abdullah MohamedResearch Centre, Future University in Egypt, New Cairo, Egypt.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The International Telecommunication Union (ITU) predicts a substantial and swift increase in global mobile data traffic. The predictions suggest that this growth will vary from 390 EB (exabytes) to 5,016 EB (exabytes) from 2024 to 2030, accordingly. This work presents a new maximum capacity model (MCM) to improve the dynamic resource allocation, robust encryption, and Quality of Service (QoS) in 5G networks which helps to meet the growing need for high-bandwidth applications such as Voice over Internet Protocol (VoIP) and video streaming. Our proposed MCM model enhances data transmission by employing dynamic resource allocation, prioritised traffic management, and robust end-to-end encryption techniques, thereby guaranteeing efficient and safe data delivery. The encryption procedure is applied to the header cypher, while the output parameters of the payload are altered. This indicates that only the sender and recipient will possess exclusive knowledge of the final outcome. In result, the comparative analyses clearly show that the MCM model outperforms over conventional models in terms of QoS packet planner, QoS packet scheduler, standard packet selection, traffic management, maximum data rate, and bandwidth utilisation.

Indexed as

Digital lifeMCMOptimizationQoSVoIP

Identifiers

PMID39650459
PMCPMC11622846

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

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.