相关论文: The Microservice Dependency Matrix
Consider learning a policy purely on the basis of demonstrated behavior -- that is, with no access to reinforcement signals, no knowledge of transition dynamics, and no further interaction with the environment. This *strictly batch…
The increasing complexity of modern software systems necessitates robust autonomic self-management capabilities. While Large Language Models (LLMs) demonstrate potential in this domain, they often face challenges in adapting their general…
Using continuous development, deployment, and monitoring (CDDM) to understand and improve applications in a customer's context is widely used for non-safety applications such as smartphone apps or web applications to enable rapid and…
Open-source software (OSS) dependencies introduce systemic risks that are difficult to manage at scale. Existing Software Composition Analysis (SCA) and reachability tools generate severe alert fatigue by treating risk as an intrinsic…
Dependency analysis is a technique to identify and determine data dependencies between service protocols. Protocols evolving concurrently in the service composition need to impose an order in their execution if there exist data…
As microservice-based systems scale across the cloud-edge continuum, traditional centralized scheduling mechanisms increasingly struggle with latency, coordination overhead, and fault tolerance. This paper presents a new architectural…
Cloud computing is a technological advancement in the arena of computing and has taken the utility vision of computing a step further by providing computing resources such as network, storage, compute capacity and servers, as a service via…
Modern cloud architectures demand self-adaptive capabilities to manage dynamic operational conditions. Yet, existing solutions often impose centralized control models ill-suited to microservices decentralized nature. This paper presents…
In practical applications of machine learning, it is necessary to look beyond standard metrics such as test accuracy in order to validate various qualitative properties of a model. Partial dependence plots (PDP), including instance-specific…
In this paper, we propose a novel approach that aims to offer an alternative to the prevalent paradigm to dynamic slicing construction. Dynamic slicing requires dynamic data and control dependencies that arise in an execution. During a…
We propose a novel centralized and decoupled algorithm, DDM, for solving multi-robot path planning problems in grid graphs, targeting on-demand and automated warehouse-like settings. Two settings are studied: a traditional one whose…
The continuously increasing renewable energy sources (RES) and demand response (DR) are becoming important sources of system flexibility. As a consequence, decision-dependent uncertainties (DDUs), interchangeably referred to as endogenous…
In many sequential tasks, a model needs to remember relevant events from the distant past to make correct predictions. Unfortunately, a straightforward application of gradient based training requires intermediate computations to be stored…
The distribution of data changes over time; models operating in dynamic environments need retraining. But knowing when to retrain, without access to labels, is an open challenge since some, but not all shifts degrade model performance. This…
Emergency response management (ERM) is a challenge faced by communities across the globe. First responders must respond to various incidents, such as fires, traffic accidents, and medical emergencies. They must respond quickly to incidents…
In many modern applications, data are received as infinite, rapid, unpredictable and time- variant data elements that are known as data streams. Systems which are able to process data streams with such properties are called Data Stream…
The advent of modern, high-speed electron detectors has made the collection of multidimensional hyperspectral transmission electron microscopy datasets, such as 4D-STEM, a routine. However, many microscopists find such experiments daunting…
Edge computing is the practice of placing computing resources at the edges of the Internet in close proximity to devices and information sources. This, much like a cache on a CPU, increases bandwidth and reduces latency for applications but…
Autonomous driving systems require real-time environmental perception to ensure user safety and experience. Streaming perception is a task of reporting the current state of the world, which is used to evaluate the delay and accuracy of…
In this article, we survey the main models, techniques, concepts, and results centered on the design and performance evaluation of engineered systems that rely on a utilization-dependent component (UDC) whose operation may depend on its…