相关论文: Sage: Leveraging ML to Diagnose Unpredictable Perf…

Sleep is vital for health, yet access to data alone does not guarantee improvement. While wearables and health apps enable tracking, users face a "Data-Action Gap," struggling to interpret metrics and translate them into action. Current…

Root cause analysis (RCA) is essential for diagnosing failures within complex software systems to ensure system reliability. The highly distributed and interdependent nature of modern cloud-based systems often complicates RCA efforts,…

Context: Microservices running and being powered by Edge Computing have been gaining much attention in the industry and academia. Since 2014, when Martin Fowler popularized the Microservice term, many studies have been published relating…

Novel applications such as the Metaverse have highlighted the potential of beyond 5G networks, which necessitate ultra-low latency communications and massive broadband connections. Moreover, the burgeoning demand for such services with…

As Clouds are complex, large-scale, and heterogeneous distributed systems, management of their resources is a challenging task. They need automated and integrated intelligent strategies for provisioning of resources to offer services that…

Many applications are implemented as multi-tier software systems, and are executed on distributed infrastructures, like cloud infrastructures, to benefit from the cost reduction that derives from dynamically allocating resources on-demand.…

[Context] Coupling is a widely discussed metric by software engineers while developing complex software systems, often referred to as a crucial factor and symptom of a poor or good design. Nevertheless, measuring the logical coupling among…

Large Language Models (LLMs), as the foundational architecture for next-generation interactive AI applications, not only power intelligent dialogue systems but also drive the evolution of embodied intelligence on edge devices, including…

The scalability and flexibility of microservice architecture have led to major changes in cloud-native application architectures. However, the complexity of managing thousands of small services written in different languages and handling…

This article presents the design of an open-API-based explainable AI (XAI) service to provide feature contribution explanations for cloud AI services. Cloud AI services are widely used to develop domain-specific applications with precise…

Effective mental health counseling is a complex, theory-driven process requiring the simultaneous integration of psychological frameworks, real-time distress signals, and strategic intervention planning. This level of clinical reasoning is…

This paper presents a novel application of explainable AI (XAI) for root-causing performance degradation in machine learning models that learn continuously from user engagement data. In such systems a single feature corruption can cause…

The IT industry needs systems management models that leverage available application information to detect quality of service, scalability and health of service. Ideally this technique would be common for varying application types with…

Microservices fuel cloud-native systems with small service sets developed and deployed independently. The independent nature of this modular architecture also leads to challenges and gaps. The intended system design might deviate far from…

To assist IT service developers and operators in managing their increasingly complex service landscapes, there is a growing effort to leverage artificial intelligence in operations. To speed up troubleshooting, log anomaly detection has…

Microsoft's internal big data analytics platform is comprised of hundreds of thousands of machines, serving over half a million jobs daily, from thousands of users. The majority of these jobs are recurring and are crucial for the company's…

High-Performance Computing (HPC) centers and cloud providers support an increasingly diverse set of applications on heterogenous hardware. As Artificial Intelligence (AI) and Machine Learning (ML) workloads have become an increasingly…

Phasor Measurement Units (PMUs) generate high-frequency, time-synchronized data essential for real-time power grid monitoring, yet the growing scale of PMU deployments creates significant challenges in latency, scalability, and reliability.…

Channel estimation in mmWave and THz-range wireless communications (producing Gb/Tb-range of data) is critical to configuring system parameters related to transmission signal quality, and yet it remains a daunting challenge both in software…

Much like on-premises systems, the natural choice for running database analytics workloads in the cloud is to provision a cluster of nodes to run a database instance. However, analytics workloads are often bursty or low volume, leaving…