Enhancing the efficiency and the reliability of the data center are the technical challenges for
maintaining the quality of services for the end-users in the data center operation. The energy …

Multivariate time series prediction (MTSP) stands as a significant and challenging frontier in
the data science domain, garnering considerable interest among researchers. Extreme …

The high computational capability provided by a data center makes it possible to solve
complex manufacturing issues and carry out large-scale collaborative cloud manufacturing …

Estimating interest rates is a typical multivariate prediction problem that has garnered
considerable attention in the finance industry. However, the rising complexity of the …

With the increasing popularity of mobile edge computing (MEC) for processing intensive and
delay sensitive IoT applications, the problem of high energy consumption of MEC has …

This article is a graphical, analytical survey of the literature, over the period 2010–2020, on
the measurement of power consumption and relevant power models of virtual entities as …

Cloud and edge computing are gradually used to achieve complex energy operation control
and massive information processing in conventional power grid. Meanwhile, with the …

Current cloud computing frameworks host millions of physical servers that utilize cloud
computing resources in the form of different virtual machines. Cloud Data Center (CDC) …

Sustainable energy management is an inexpensive approach for improved energy use.
However, the research used does not focus on cutting-edge technology possibilities in an …

To address challenges encountered in traditional Elman neural networks (ENNs), such as
low convergence accuracy, difficulties in hyperparameter selection, and issues with gradient …