The serverless computing survey: A technical primer for design architecture

Z Li, L Guo, J Cheng, Q Chen, BS He… - ACM Computing Surveys …, 2022 - dl.acm.org
The development of cloud infrastructures inspires the emergence of cloud-native computing.
As the most promising architecture for deploying microservices, serverless computing has …

A WOA-based optimization approach for task scheduling in cloud computing systems

X Chen, L Cheng, C Liu, Q Liu, J Liu, Y Mao… - IEEE Systems …, 2020 - ieeexplore.ieee.org
Task scheduling in cloud computing can directly affect the resource usage and operational
cost of a system. To improve the efficiency of task executions in a cloud, various …

Cloud-native computing: A survey from the perspective of services

S Deng, H Zhao, B Huang, C Zhang… - Proceedings of the …, 2024 - ieeexplore.ieee.org
The development of cloud computing delivery models inspires the emergence of cloud-
native computing. Cloud-native computing, as the most influential development principle for …

Cost-aware job scheduling for cloud instances using deep reinforcement learning

F Cheng, Y Huang, B Tanpure, P Sawalani, L Cheng… - Cluster …, 2022 - Springer
As the services provided by cloud vendors are providing better performance, achieving auto-
scaling, load-balancing, and optimized performance along with low infrastructure …

Deep adversarial imitation reinforcement learning for QoS-aware cloud job scheduling

Y Huang, L Cheng, L Xue, C Liu, Y Li, J Li… - IEEE Systems …, 2021 - ieeexplore.ieee.org
Although cloud computing is one of the promising technologies for online business services,
how to schedule real-time cloud jobs with high quality of service (QoS) is still challenging …

Bibliometric analysis of artificial intelligence in textiles

H Halepoto, T Gong, S Noor, H Memon - Materials, 2022 - mdpi.com
Generally, comprehensive documents are needed to provide the research community with
relevant details of any research direction. This study conducted the first descriptive …

Cost-aware real-time job scheduling for hybrid cloud using deep reinforcement learning

L Cheng, A Kalapgar, A Jain, Y Wang, Y Qin… - Neural Computing and …, 2022 - Springer
Hybrid cloud computing enables enterprises to get the best of both private and public cloud
models. One of its primary benefits is to reduce operational costs, and the prerequisite is that …

Elastic resource management for deep learning applications in a container cluster

Y Mao, V Sharma, W Zheng, L Cheng… - IEEE Transactions on …, 2022 - ieeexplore.ieee.org
The increasing demand for learning from massive datasets is restructuring our economy.
Effective learning, however, involves nontrivial computing resources. Most businesses utilize …

Progress-based container scheduling for short-lived applications in a kubernetes cluster

Y Fu, S Zhang, J Terrero, Y Mao, G Liu… - … Conference on Big …, 2019 - ieeexplore.ieee.org
In the past decade, we have envisioned enormous growth in the data generated by different
sources, ranging from weather sensors and customer purchasing records to Internet of …

An improved Wolf pack algorithm for optimization problems: Design and evaluation

X Chen, F Cheng, C Liu, L Cheng, Y Mao - Plos one, 2021 - journals.plos.org
Wolf Pack Algorithm (WPA) is a swarm intelligence algorithm that simulates the food
searching process of wolves. It is widely used in various engineering optimization problems …