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The increasing demands for computing performance have been a reality regardless of the requirements for smaller and more energy efficient devices. Throughout the years, the strategy adopted by industry was to increase the robustness of a…
Cloud computing revolutionized the information technology (IT) industry by offering dynamic and infinite scaling, on-demand resources and utility-oriented usage. However, recent changes in user traffic and requirements have exposed the…
Correctly applying distributed systems concepts is important for software that seeks to be scalable, reliable and fast. For this reason, Distributed Systems is a course included in many Computer Science programs. To both describe current…
Large Language Models (LLMs) are used for many different software engineering tasks. In software architecture, they have been applied to tasks such as classification of design decisions, detection of design patterns, and generation of…
Edge computing has become a promising computing paradigm for building IoT (Internet of Things) applications, particularly for applications with specific constraints such as latency or privacy requirements. Due to resource constraints at the…
This paper presents a general xml-based distributed software architecture in the aim of accessing and sharing resources in an opened client/server environment. The paper is organized as follows : First, we introduce the idea of a "General…
Grids aim at exploiting synergies that result from cooperation of autonomous distributed entities. The synergies that result from grid cooperation include the sharing, exchange, selection, and aggregation of geographically distributed…
Computational Grids are emerging as new infrastructure for Internet-based parallel and distributed computing. They enable the sharing, exchange, discovery, and aggregation of resources distributed across multiple administrative domains,…
Distributing development tasks in the context of global software development bears both many risks and many opportunities. Nowadays, distributed development is often driven by only a few factors or even just a single factor such as…
In this tutorial paper, we will firstly review some basic simulation concepts and then introduce the parallel and distributed simulation techniques in view of some new challenges of today and tomorrow. More in particular, in the last years…
With the widespread availability of high-speed networks, it becomes feasible to outsource computing to remote providers and to federate resources from many locations. Such observations motivated the development, from the mid-1990s onwards,…
This paper explores the architecture of Software as a Service (SaaS) platforms, emphasizing scalability and maintainability. SaaS, a flexible software distribution model suitable for individuals and organizations, has become prevalent with…
Large-scale distributed computing infrastructures such as the Worldwide LHC Computing Grid (WLCG) require comprehensive simulation tools for evaluating performance, testing new algorithms, and optimizing resource allocation strategies.…
"Grid" computing has emerged as an important new field, distinguished from conventional distributed computing by its focus on large-scale resource sharing, innovative applications, and, in some cases, high-performance orientation. In this…
High-quality designs of distributed systems and services are essential for our digital economy and society. Threatening to slow down the stream of working designs, we identify the mounting pressure of scale and complexity of…
Business success of companies heavily depends on the availability and performance of their client applications. Due to modern development paradigms such as DevOps and microservice architectural styles, applications are decoupled into…
Significant efforts has been made to expand the use of Large Language Models (LLMs) beyond basic language tasks. While the generalizability and versatility of LLMs have enabled widespread adoption, evolving demands in application…
Deep Learning (DL) models have achieved superior performance in many application domains, including vision, language, medical, commercial ads, entertainment, etc. With the fast development, both DL applications and the underlying serving…
Language models (LMs) are machine learning models designed to predict linguistic patterns by estimating the probability of word sequences based on large-scale datasets, such as text. LMs have a wide range of applications in natural language…
The rise of the Internet of Things and edge computing has shifted computing resources closer to end-users, benefiting numerous delay-sensitive, computation-intensive applications. To speed up computation, distributed computing is a…