Related papers: Self-adaptive, Requirements-driven Autoscaling of …
Edge computing allows for the decentralization of computing resources. This decentralization is achieved through implementing microservice architectures, which require low latencies to meet stringent service level agreements (SLA) such as…
Microservices have become popular in the past few years, attracting the interest of both academia and industry. Despite of its benefits, this new architectural style still poses important challenges, such as resilience, performance and…
Microservices Architecture (MSA) style is a promising design approach to develop software applications consisting of multiple small and independently deployable services. Over the past few years, researchers and practitioners have proposed…
In pervasive dynamic environments, vehicles connect to other objects to send operational data and receive updates so that vehicular applications can provide services to users on demand. Automotive systems should be self-adaptive, thereby…
In cloud-native systems, Kubernetes clusters with interdependent services often face challenges to their operational resilience due to poor workload management issues such as resource blocking, bottlenecks, or continuous pod crashes. These…
In this work, we introduce a Self-Aware Polymorphic Architecture (SAPA) design approach to support emerging context-aware applications and mitigate the programming challenges caused by the ever-increasing complexity and heterogeneity of…
Multi-agent reinforcement learning (MARL) often relies on \emph{parameter sharing (PS)} to scale efficiently. However, purely shared policies can stifle each agent's unique specialization, reducing overall performance in heterogeneous…
In the context of the BI-REX (Big Data Innovation and Research Excellence) competence center SEAWALL (SEAmless loW lAtency cLoud pLatforms) project (scientific coordinator Prof. Maurizio Gabbrielli) we develop a novel approach for run-time…
Microservice Architecture (MSA) denotes an emerging architectural style for distributed and service-based systems whereby each microservice is highly cohesive and implements a single business capability. A microservice system consists of…
This paper proposes a reinforcement learning-based method for microservice resource scheduling and optimization, aiming to address issues such as uneven resource allocation, high latency, and insufficient throughput in traditional…
Microservice Architecture (MSA) is a service-based architectural style with a strong emphasis on high cohesion and loose coupling. It is commonly regarded as a descendant of Service-oriented Architecture (SOA) and thus might draw on…
Achieving resource efficiency while preserving end-user experience is non-trivial for cloud application operators. As cloud applications progressively adopt microservices, resource managers are faced with two distinct levels of system…
Microservices are highly modular and scalable Service Oriented Architectures. They underpin automated deployment practices like Continuous Deployment and Autoscaling. In this paper, we formalize these practices and show that automated…
The growth of compute-intensive AI tasks highlights the need to mitigate the processing costs and improve performance and energy efficiency. This necessitates the integration of intelligent agents as architectural adaptation supervisors…
Optimizing microservice placement to enhance the reliability of services is crucial for improving the service level of microservice architecture-based mobile networks and Internet of Things (IoT) networks. Despite extensive research on…
Microservices have become the dominant architectural paradigm for building scalable and modular cloud-native systems. However, achieving effective auto-scaling in such systems remains a non-trivial challenge, as it depends not only on…
Machine learning is now a central part of how modern systems are built and used, powering everything from personalized recommendations to large-scale business analytics. As its role grows, organizations are facing new challenges in…
The microservice architectural style has many advantages such as scalability, reusability, and easy maintainability. Microservices have therefore become a popular architectural choice when developing new applications. Reaping these benefits…
As data volumes expand rapidly, distributed machine learning has become essential for addressing the growing computational demands of modern AI systems. However, training models in distributed environments is challenging with participants…
Kubernetes provides native autoscaling mechanisms, including the Horizontal Pod Autoscaler, Vertical Pod Autoscaler, and node-level autoscalers, to enable elastic resource management for cloud-native applications. However, production…