Deep neural networks (DNNs) are currently being deployed as machine learning technology
in a wide range of important real-world applications. DNNs consist of a huge number of …

Virtual machine (VM) integration methods have effectively proven an optimized load
balancing in cloud data centers. The main challenge with VM integration methods is the …

Cloud computing has emerged as a cornerstone for modern industries, offering scalable and
flexible resources to meet growing computational demands. However, managing fluctuating …

DNA profiling involves the analysis of sequences of an individual or mixed DNA profiles to
identify the persons that these profiles belong to. A critically important application of DNA …

Recently, the combination of convolutional neural network (CNN) and long short-term
memory (LSTM) exhibits better performance than single network architecture. Most of these …

Given the rise in demand for cloud computing in the modern era, the effectiveness of
resource utilization is eminent to decrease energy footprint and achieve economic services …

Predicting future resource demand in Cloud Computing is essential for optimizing the trade-
off between serving customers' requests efficiently and minimizing the provisioning cost …

Several emerging non-volatile (NV) memory technologies are rising as interesting
alternatives to build the Last-Level Cache (LLC). Their advantages, compared to SRAM …

Exponential growth in the use of cloud computing services makes it difficult to forecast loads
of virtual machines (VMs). Accurate virtual machine (VM) workload forecasting is the most …

Deep Neural Networks (DNNs) are currently used in a wide range of critical real-world
applications as machine learning technology. Due to the high number of parameters that …