From the 1 of 27 linked papers with an AI index.
2 citations · 7 across the 18 of their papers we have counts for
17 papers · 1 filter
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…
A Taxonomy of Performance Metrics for the Distributed Computing Continuum
Praveen Kumar Donta, Boris Sedlak, Alfreds Lapkovskis +6
The paper proposes a structured taxonomy of performance metrics for distributed computing continuum systems, categorizing metrics across computing, network, and application levels…
Resilient by Design -- Active Inference for Distributed Continuum Intelligence
Praveen Kumar Donta, Alfreds Lapkovskis, Enzo Mingozzi +1
Failures are the norm in highly complex and heterogeneous devices spanning the distributed computing continuum (DCC), from resource-constrained IoT and edge nodes to high-performan…
Predictive RTO for CoAP using Lightweight Support Vector Regression in Internet of Things
Tobias Hansson, Praveen Kumar Donta
Internet of Things (IoT) networks require lightweight application layer messaging, and CoAP is an option because it supports REST-style interactions over UDP on constrained devices…
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…
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…