Machine Learning (ML) has gained prominence across various fields, including data management. Rule-based components are substituted by ML-driven counterparts that extract rules from experience. The prevalence of statistical methods is waning as ...

Cybersecurity events severely impact many individuals, infras-tructures, businesses, and institutions. Machine learning has been playing a key role in many aspects of our daily life and in particular as a cyber defense mechanism. However, the nature of ...

As the automation of microservice and cloud computing operations grows, models become crucial for enabling resilient and efficient adaptive architectures and implementations.

Heating, Ventilation, and Air Conditioning (HVAC) systems play a significant role in global energy consumption, and their effective maintenance is vital for reducing operational costs. The integra-tion of Cyber-Physical Systems, including Internet of ...

Resource-oriented service computing has emerged as one of the major paradigms for building large scale distributed systems. These systems can grow very complex and require access to diverse re-sources. In order to shorten the development time of such ...

The ever-increasing complexity of applications and networks man-agement demands alternative solutions for identifying of suitable deployment configurations in line with established Service Level Agreements. Some existing approaches utilize methods such ...

Multi-cloud computing is a vitally important topic from both busi-ness and technical perspectives since it guarantees resiliency, avail-ability, and security. Due to the vast number of configurations among cloud providers, it is quite challenging to ...

Advances and synergies between AI and Cloud computing are driv-ing increased levels of automation and autonomy in the strenuous operation of modern and complex IT systems and environments (IT-Sys|Envs). This notion, often termed as AIOps, is transforming ...

Today’s Internet of Things (IoT) environments are heterogeneous as they are typically comprised of devices equipped with various CPU architectures and software platforms. Therefore, in defending IoT environments against security threats, the capability ...

We introduce the Topology-Aware Multi-GPU Scheduler (TAMG), a novel approach to assigning multiple GPUs in a GPU cluster to deep learning jobs in a job queue. TAMG uses an existing method for job selection, while incorporating the cluster topology into ...

It is well known that optimistically initializing a Q-table in table-based Reinforcement Learning can be a useful technique in reward-sparse environments. In this paper, we propose an approach to ini-tialize a Deep Q-network optimistically. The ...

Data migration refers to the transfer of data from one location to another, for instance, from a local database to a cloud server or from one cloud to another. To minimize business disruption during this process, it is essential to ensure that data ...

In this work, we try to address the two challenging problems in machine learning (ML) which are: (a) the need for large amounts of labeled images for training supervised classifiers and (b) the supervised classification for time series data. We formulate ...

An increasing number of studies use gender information to un-derstand phenomena such as gender bias, inequity in access and participation, or the impact of the Covid pandemic response. Un-fortunately, most datasets do not include self-reported gender in-...

Computer-aided processes can be used to improve the quality of requirements in software projects. These processes, in principle, can be divided into two stages: requirement quality evaluation, essentially a classification task, and requirement correction ...

The presence of control-flow divergence in loops can either hin-der or impede auto-vectorization as a compiler transformation to exploit parallelism enabled by Single-Instruction Multiple-Data (SIMD) instructions. A solution is to linearize control flow ...

Microservice applications are increasingly embracing cloud platforms to run their services. These applications can often be impacted by anomalies. Detecting anomalies at runtime is vital to ensure that cloud-native applications meet specified ...

This paper explores the use of text data augmentation techniques to enhance conflict and duplicate detection in software engineer-ing tasks through sentence pair classification. T he s tudy adapts generic augmentation techniques such as shuffling, back ...

In the realm of Software Engineering (SE), automation has become a tangible reality. Artificial Intelligence (AI) has suc-cessfully addressed challenges in project management, mod-eling, testing, and development. Among the latest innova-tions is ChatGPT, ...

The Web of Things (WoT) combined with agent-based computing, has emerged as a powerful computing paradigm where addressable resources are considered as service components which can offer highly granular functionality. In this paper, we present a ...