A deep reinforcement learning approach to the optimization of data center task scheduling
H Che, Z Bai, R Zuo, H Li - Complexity, 2020 - Wiley Online Library
With more businesses are running online, the scale of data centers is increasing
dramatically. The task‐scheduling operation with traditional heuristic algorithms is facing the …
dramatically. The task‐scheduling operation with traditional heuristic algorithms is facing the …
An improved bound for minimizing the total weighted completion time of coflows in datacenters
In data-parallel computing frameworks, intermediate parallel data is often produced at
various stages which needs to be transferred among servers in the datacenter network (eg …
various stages which needs to be transferred among servers in the datacenter network (eg …
Scheduling coflows of multi-stage jobs to minimize the total weighted job completion time
Datacenter networks are critical to Cloud computing. The coflow abstraction is a major leap
forward of application-aware network scheduling. In the context of multistage jobs, there are …
forward of application-aware network scheduling. In the context of multistage jobs, there are …
A survey of big data machine learning applications optimization in cloud data centers and networks
SH Mohamed, TEH El-Gorashi… - arXiv preprint arXiv …, 2019 - arxiv.org
This survey article reviews the challenges associated with deploying and optimizing big data
applications and machine learning algorithms in cloud data centers and networks. The …
applications and machine learning algorithms in cloud data centers and networks. The …
Efficient file dissemination in data center networks with priority-based adaptive multicast
In today's data center networks (DCN), cloud applications commonly disseminate files from a
single source to a group of receivers for service deployment, data replication, software …
single source to a group of receivers for service deployment, data replication, software …
Efficient scheduling of weighted coflows in data centers
Traditional network resource management mechanisms are mainly flow or packet based.
Recently, coflow has been proposed as a new abstraction to capture the communication …
Recently, coflow has been proposed as a new abstraction to capture the communication …
MOSC: A method to assign the outsourcing of service function chain across multiple clouds
Abstract As Network Function Virtualization (NFV) becomes reality and cloud computing
offers a scalable pay-as-you-go charging model, more network operators would like to …
offers a scalable pay-as-you-go charging model, more network operators would like to …
Near optimal coflow scheduling in networks
The coflow scheduling problem has emerged as a popular abstraction in the last few years
to study data communication problems within a data center [6]. In this basic framework, each …
to study data communication problems within a data center [6]. In this basic framework, each …
A survey of coflow scheduling schemes for data center networks
Cluster computing applications, such as MapReduce and Spark, have been widely
deployed in data centers to support commercial applications and scientific research. These …
deployed in data centers to support commercial applications and scientific research. These …