Task scheduling in cloud computing based on meta-heuristics: review, taxonomy, open challenges, and future trends
Cloud computing is a recently looming-evoked paradigm, the aim of which is to provide on-
demand, pay-as-you-go, internet-based access to shared computing resources (hardware …
demand, pay-as-you-go, internet-based access to shared computing resources (hardware …
Future data center energy-conservation and emission-reduction technologies in the context of smart and low-carbon city construction
The energy consumption of data centers accounts for approximately 1% of that of the world,
the average power usage effectiveness is in the range of 1.4–1.6, and the associated carbon …
the average power usage effectiveness is in the range of 1.4–1.6, and the associated carbon …
A scheduling scheme in the cloud computing environment using deep Q-learning
Task scheduling, which plays a vital role in cloud computing, is a critical factor that
determines the performance of cloud computing. From the booming economy of information …
determines the performance of cloud computing. From the booming economy of information …
Machine and deep learning for resource allocation in multi-access edge computing: A survey
With the rapid development of Internet-of-Things (IoT) devices and mobile communication
technologies, Multi-access Edge Computing (MEC) has emerged as a promising paradigm …
technologies, Multi-access Edge Computing (MEC) has emerged as a promising paradigm …
A survey on algorithms for intelligent computing and smart city applications
With the rapid development of human society, the urbanization of the world's population is
also progressing rapidly. Urbanization has brought many challenges and problems to the …
also progressing rapidly. Urbanization has brought many challenges and problems to the …
Task scheduling, resource provisioning, and load balancing on scientific workflows using parallel SARSA reinforcement learning agents and genetic algorithm
Cloud computing is one of the most popular distributed environments, in which, multiple
powerful and heterogeneous resources are used by different user applications. Task …
powerful and heterogeneous resources are used by different user applications. Task …
Adaptive computation offloading and resource allocation strategy in a mobile edge computing environment
With the popularity of smart mobile equipment, the amount of data requested by users is
growing rapidly. The traditional centralized processing method represented by the cloud …
growing rapidly. The traditional centralized processing method represented by the cloud …
DRLBTSA: Deep reinforcement learning based task-scheduling algorithm in cloud computing
Task scheduling in cloud paradigm brought attention of all researchers as it is a challenging
issue due to uncertainty, heterogeneity, and dynamic nature as they are varied in size …
issue due to uncertainty, heterogeneity, and dynamic nature as they are varied in size …
Bi-objective scheduling algorithm for scientific workflows on cloud computing platform with makespan and monetary cost minimization approach
M Hosseini Shirvani, R Noorian Talouki - Complex & Intelligent Systems, 2022 - Springer
Scheduling of scientific workflows on hybrid cloud architecture, which contains private and
public clouds, is a challenging task because schedulers should be aware of task inter …
public clouds, is a challenging task because schedulers should be aware of task inter …
A deep reinforcement learning based hybrid algorithm for efficient resource scheduling in edge computing environment
F Xue, Q Hai, T Dong, Z Cui, Y Gong - Information Sciences, 2022 - Elsevier
Edge computing can greatly decrease the delay between users and cloud servers, which
can significantly improve system service performance. However, it remains challenging for …
can significantly improve system service performance. However, it remains challenging for …