DiffTREAT: Differentiated Traffic Scheduling Based on RNN in Data Centers

Wei, Ziqi; Li, Qing; Zhu, Keke; Zhou, Jianer; Zou, Longhao; Jiang, Yong; Xiao, Xi

doi:10.1109/tcc.2022.3206593

Cited by 6 publications

(3 citation statements)

References 37 publications

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“…The issue of path diversity was also address with the enhanced multipath version of the proposed PDQ scheduling approach. The result of the work showed a tremendous improvement on the existing work such as [Dukkipati and McKeown 2006] and [Wei et al 2022] in terms of resilient to packet loss and preservation of performance gains. However, the at some point the latency for scheduling for short flows are too longer than desired thus enabling the interference of the small flows on the long flows to occur.…”

Section: Predictive Flow Schedulingmentioning

confidence: 91%

Untitled

2023

INDJCSE

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The problem of network flow interference within a data centre network has been addressed by several scholars in the literature with a number of solutions provided. However, many of such solutions does not take into cognisance the relative cost effect of the proposals on the service providers and end-users. The solutions are either on the benefit of the service providers at the expense of the end-users and vice versa. We proposed a Multi-Criteria Optimization Crosspoint Queue which was able to address the traffic flow interference that results into both network instability and unbalanced provider-user relationship. The experimental results showed that the proposed approach is able to maintain a stable specified QoS metric as a single-parameter amidst several QoS and likewise balanced the cost effects on either side of the stakeholders. The solution is relevant to the network organization in prioritizing network quality to adapt to changing business requirements and market demands.

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Section: Predictive Flow Schedulingmentioning

confidence: 91%

Untitled

2023

INDJCSE

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“…Wei et al [16] used Deep Learning (DL) techniques to categorize traffic types and predict traffic size finely. Compared with traditional methods, the algorithm has significant advantages in traffic scheduling, can better adapt to the dynamically changing network environment, and improves the network performance and resource utilization of data centers.…”

Section: Q Du Et Almentioning

confidence: 99%

Review of Load Balancing Mechanisms in SDN-Based Data Centers

Du,

Cui,

Tang

et al. 2024

JCC

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With the continuous expansion of the data center network scale, changing network requirements, and increasing pressure on network bandwidth, the traditional network architecture can no longer meet people's needs. The development of software defined networks has brought new opportunities and challenges to future networks. The data and control separation characteristics of SDN improve the performance of the entire network. Researchers have integrated SDN architecture into data centers to improve network resource utilization and performance. This paper first introduces the basic concepts of SDN and data center networks. Then it discusses SDN-based load balancing mechanisms for data centers from different perspectives. Finally, it summarizes and looks forward to the study on SDN-based load balancing mechanisms and its development trend.

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“…A similar research written by Utami (2020) entitled 'Obstacles and the Role of Parents in Online Learning During the Covid-19 Pandemic' stated that many obstacles faced by parents in online learning included (1) internet signal, which is sometimes difficult, (2) expensive quota, (3) unable to accompany their children fully, (4) parents do not understand the material, so they cannot teach their children optimally, (4) there is no cell phone, so you need to ask a friend directly. From several previous studies, the Covid-19 pandemic has considerably impacted the teaching and learning process involving students, parents, and teachers, as muchneeded cooperation between parents and teachers (Wei et al, 2022). Further research is needed in the management of this online learning.…”

Section: Barriers To Online Learningmentioning

confidence: 99%

Evaluating Learning Management Through Online Mode During the Covid-19 Pandemic

Ariana,

Natalisa,

Maryanti

2023

JHETP

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This research aims to describe the obstacles in the online mode learning process in public junior high schools in Palembang. It uses a qualitative descriptive research method, which is a method that describes the object of research at present based on facts that appear as they should. The data collection technique used was in-depth interviews, observation, and documentation. Respondents came from teachers as educators, students as students, and parents of students as companions in the implementation of learning carried out by teachers and students. The study results show that the obstacles to online learning in the junior high school in Palembang city are the infrastructure facilities provided by the school. The knowledge of the technology skills used by teachers for online learning could be better. The technological facilities owned by students and the assistance provided by parents of students to accompany their children in implementing online learning at public junior high schools in Palembang could be better.

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DiffTREAT: Differentiated Traffic Scheduling Based on RNN in Data Centers

Cited by 6 publications

References 37 publications

Untitled

Untitled

Review of Load Balancing Mechanisms in SDN-Based Data Centers

Evaluating Learning Management Through Online Mode During the Covid-19 Pandemic

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