collaborators

8 papers

cs.DC2026

User-Assisted Collaborative Distributed Inference for Efficient QoS-Aware Autoscaling

Alfreds Lapkovskis, Ali Beikmohammadi, Sindri Magnússon +1

Growing demand for artificial intelligence (AI) inference services requires scalable infrastructure, yet centralized serving costs rise with demand. We propose a collaborative dist…

cs.DC2026

A Taxonomy of Performance Metrics for the Distributed Computing Continuum

Praveen Kumar Donta, Boris Sedlak, Alfreds Lapkovskis +6

Performance evaluation is essential for understanding, comparing, and improving computing systems, including Distributed Computing Continuum Systems (DCCS). In recent years, comput…

eess.SY2026

Active Inference for Adaptive Traffic Signal Control in Noisy Nonstationary IoT Environments

Dénes Toth, George Ambroladze, Edwin Sundberg +2

Urban traffic signal control at IoT-instrumented intersections must remain effective under sensor occlusion, weather attenuation, and nonstationary demand. Conventional controllers…

cs.DC2026

An Uncertainty-Aware Resilience Micro-Agent for Causal Observability in the Computing Continuum

Suvi De Silva, Alfreds Lapkovskis, Alaa Saleh +2

Grey failures in the computing continuum produce ambiguous overlapping symptoms that existing approaches fail to diagnose reliably, either due to a lack of causal awareness or acti…

cs.DC2026

Adaptive AI Task Partitioning and Safe Offloading in Heterogeneous Edge-Cloud Continuum

Akuen Akoi Deng, Eimantas Butkus, Alfreds Lapkovskis +1

In recent years, the use of artificial intelligence on resource-constrained IoT devices has grown significantly. However, existing approaches to AI task partitioning and offloading…

cs.DC2026

NeSy-Edge: Neuro-Symbolic Trustworthy Self-Healing in the Computing Continuum

Peihan Ye, Alfreds Lapkovskis, Alaa Saleh +2

The computational demands of modern AI services are increasingly shifting execution beyond centralized clouds toward a computing continuum spanning edge and end devices. However, t…