Related papers: Adaptable TeaStore: A Choreographic Approach
In service-oriented architecture, services coordinate in one of two ways: directly, using point-to-point communication, or indirectly, through an intermediary called the orchestrator. Orchestrators tend to be more popular because their…
Adaptive learning aims to stimulate and meet the needs of individual learners, which requires sophisticated system-level coordination of diverse tasks, including modeling learning resources, estimating student states, and making…
The shift from monolithic applications to composition of distributed software initiated in the early twentieth, is based on the vision of software-as-service. This vision, found in many technologies such as RESTful APIs, advocates globally…
Adaptive user interfaces adapt their contents, presentation, or behavior mostly in a sudden, fluctuating, and abrupt way, which may cause negative effects on the end users, such as cognitive disruption. Instead, adaptivity should be…
We introduce an adaptive scheduling for adaptive sampling as a novel way of machine learning in the construction of part-of-speech taggers. The goal is to speed up the training on large data sets, without significant loss of performance…
Common deployment models for Edge Computing are based on (composable) microservices that are offloaded to cloudlets. Runtime adaptations-in response to varying load, QoS fulfillment, mobility, etc.-are typically based on coarse-grained and…
Microservices is an architectural style inspired by service-oriented computing that has recently started gaining popularity. Jolie is a programming language based on the microservices paradigm: the main building block of Jolie systems are…
IBM Research Castor, a cloud-native system for managing and deploying large numbers of AI time-series models in IoT applications, is described. Modelling code templates, in Python and R, following a typical machine-learning workflow are…
The increasing complexity of IoT applications and the continuous growth in data generated by connected devices have led to significant challenges in managing resources and meeting performance requirements in computing continuum…
Collective adaptive systems are new emerging computational systems consisting of a large number of interacting components and featuring complex behaviour. These systems are usually distributed, heterogeneous, decentralised and…
Adaptive Computing is an application-agnostic outer loop framework to strategically deploy simulations and experiments to guide decision making for scale-up analysis. Resources are allocated over successive batches, which makes the…
The paper presents a data-driven model of self-adaptivity for multiparty sessions. System choreography is prescribed by a global type. Participants are incarnated by processes associated with monitors, which control their behaviour. Each…
Choreographic Programming is a development methodology for concurrent software that guarantees correctness by construction. The key to this paradigm is to disallow mismatched I/O operations in programs, called choreographies, and then…
While cloud environments and auto-scaling solutions have been widely applied to traditional monolithic applications, they face significant limitations when it comes to microservices-based architectures. Microservices introduce additional…
Modern cloud-native systems increasingly rely on multi-cluster deployments to support scalability, resilience, and geographic distribution. However, existing resource management approaches remain largely reactive and cluster-centric,…
Microservices architectures allow for short deployment cycles and immediate effects but offer no safety mechanisms when service contracts need to be changed. Maintaining the soundness of microservice architectures is an error-prone task…
We believe that to fully support adaptive distributed applications, middleware must itself be adaptable, adaptive and policy-free. In this paper we present a new language-independent adaptable and adaptive policy framework suitable for…
Agentic AI systems - systems that can pursue goals through multi-step planning and tool-mediated action with limited direct supervision - are moving from experimental prototypes to enterprise deployments. This transition introduces tensions…
In the field of ubiquitous computing, a class of applications called context-aware services attracted great interest especially since the emergence of wireless technologies and mobile devices. Context-aware application can dynamically…
We propose Sliceable Monolith, a new methodology for developing microservice architectures and perform their integration testing by leveraging most of the simplicity of a monolith: a single codebase and a local execution environment that…