Emerging opportunities and challenges for the future of reservoir computing

M Yan, C Huang, P Bienstman, P Tino, W Lin… - Nature …, 2024 - nature.com
Reservoir computing originates in the early 2000s, the core idea being to utilize dynamical
systems as reservoirs (nonlinear generalizations of standard bases) to adaptively learn …

Modeling the Green Cloud Continuum: integrating energy considerations into Cloud–Edge models

YS Patel, P Townend, A Singh, PO Östberg - Cluster Computing, 2024 - Springer
The energy consumption of Cloud–Edge systems is becoming a critical concern
economically, environmentally, and societally; some studies suggest data centers and …

MAG-D: A multivariate attention network based approach for cloud workload forecasting

YS Patel, J Bedi - Future Generation Computer Systems, 2023 - Elsevier
The Coronavirus pandemic and the work-from-home have drastically changed the working
style and forced us to rapidly shift towards cloud-based platforms & services for seamless …

Multivariate workload and resource prediction in cloud computing using CNN and GRU by attention mechanism

J Dogani, F Khunjush, MR Mahmoudi… - The Journal of …, 2023 - Springer
The resources required to service cloud computing applications are dynamic and fluctuate
over time in response to variations in the volume of incoming requests. Proactive …

Multi-task learning for electricity price forecasting and resource management in cloud based industrial IoT systems

AA Almazroi, N Ayub - IEEE Access, 2023 - ieeexplore.ieee.org
Cloud computing has gained immense popularity in the logistics industry. This innovative
technology optimizes computing operations by eliminating the requirement for physical …

Multivariate time series ensemble model for load prediction on hosts using anomaly detection techniques

S Bawa, PS Rana, RK Tekchandani - Cluster Computing, 2024 - Springer
Host load prediction is essential in computing to improve resource utilization and for
achieving service level agreements. However, due to variations in load and the inefficiency …

A succinct state-of-the-art survey on green cloud computing: Challenges, strategies, and future directions

D Biswas, S Jahan, S Saha, M Samsuddoha - … Computing: Informatics and …, 2024 - Elsevier
Cloud computing is a method of providing various computing services, including software,
hardware, databases, data storage, and infrastructure, to the public through the Internet. The …

Ensemble cnn attention-based bilstm deep learning architecture for multivariate cloud workload prediction

A Kaim, S Singh, YS Patel - … of the 24th International Conference on …, 2023 - dl.acm.org
Cloud computing has drastically changed the nature of computing in recent years. However,
despite its countless benefits, it also suffers from some major challenges including …

A common feature-driven prediction model for multivariate time series data

X Yu, H Wang, J Wang, X Wang - Information Sciences, 2024 - Elsevier
Multivariate time series data contain a variety of common features that are difficult to extract,
among which the sudden irregular fluctuation trend, the trend feature of large fluctuation …

A feature extraction and time war** based neural expansion architecture for cloud resource usage forecasting

G Singh, P Sengupta, A Mehta, J Bedi - Cluster Computing, 2024 - Springer
Accurate resource utilization estimation is crucial for efficient resource allocation, capacity
planning, and cost optimization in cloud systems. In the past, several artificial intelligence …