97 citations · 203 across the 35 of their papers we have counts for
20 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
Performance evaluation is essential for understanding, comparing, and improving computing systems, including Distributed Computing Continuum Systems (DCCS). In recent years, comput…
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…
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…
LLM-assisted Agentic Edge Intelligence Framework
Chinmaya Kumar Dehury, Siddharth Singh Kushwaha, Qiyang Zhang +2
Edge intelligence delivers low-latency inference, yet most edge analytics remain hard-coded and must be redeployed as conditions change. When data patterns shift or new questions a…
Service Orchestration in the Computing Continuum: Structural Challenges and Vision
Boris Sedlak, Víctor Casamayor Pujol, Ildefons Magrans de Abril +3
The Computing Continuum (CC) integrates different layers of processing infrastructure, from Edge to Cloud, to optimize service quality through ubiquitous and reliable computation.…
Synergizing Monetization, Orchestration, and Semantics in Computing Continuum
Chinmaya Kumar Dehury, Lauri Lovén, Praveen Kumar Donta +2
Industry demands are growing for hyper-distributed applications that span from the cloud to the edge in domains such as smart manufacturing, transportation, and agriculture. Yet to…
A Conflict-Aware Resource Management Framework for the Computing Continuum
Vlad Popescu-Vifor, Ilir Murturi, Praveen Kumar Donta +1
The increasing device heterogeneity and decentralization requirements in the computing continuum (i.e., spanning edge, fog, and cloud) introduce new challenges in resource orchestr…
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…
Performance Measurements in the AI-Centric Computing Continuum Systems
Praveen Kumar Donta, Qiyang Zhang, Schahram Dustdar
Over the Eight decades, computing paradigms have shifted from large, centralized systems to compact, distributed architectures, leading to the rise of the Distributed Computing Con…
Graph-based Gossiping for Communication Efficiency in Decentralized Federated Learning
Huong Nguyen, Hong-Tri Nguyen, Praveen Kumar Donta +2
Federated learning has emerged as a privacy-preserving technique for collaborative model training across heterogeneously distributed silos. Yet, its reliance on a single central se…
Dynamic and Distributed Routing in IoT Networks based on Multi-Objective Q-Learning
Shubham Vaishnav, Praveen Kumar Donta, Sindri Magnússon
IoT networks often face conflicting routing goals such as maximizing packet delivery, minimizing delay, and conserving limited battery energy. These priorities can also change dyna…
Optimizing Multi-DNN Inference on Mobile Devices through Heterogeneous Processor Co-Execution
Yunquan Gao, Zhiguo Zhang, Praveen Kumar Donta +4
Deep Neural Networks (DNNs) are increasingly deployed across diverse industries, driving demand for mobile device support. However, existing mobile inference frameworks often rely…
Benchmarking Dynamic SLO Compliance in Distributed Computing Continuum Systems
Alfreds Lapkovskis, Boris Sedlak, Sindri Magnússon +2
Ensuring Service Level Objectives (SLOs) in large-scale architectures, such as Distributed Computing Continuum Systems (DCCS), is challenging due to their heterogeneous nature and…
Follow-Me AI: Energy-Efficient User Interaction with Smart Environments
Alaa Saleh, Praveen Kumar Donta, Roberto Morabito +2
This article introduces Follow-Me AI, a concept designed to enhance user interactions with smart environments, optimize energy use, and provide better control over data captured by…
Equilibrium in the Computing Continuum through Active Inference
Boris Sedlak, Victor Casamayor Pujol, Praveen Kumar Donta +1
Computing Continuum (CC) systems are challenged to ensure the intricate requirements of each computational tier. Given the system's scale, the Service Level Objectives (SLOs) which…
Designing Reconfigurable Intelligent Systems with Markov Blankets
Boris Sedlak, Victor Casamayor Pujol, Praveen Kumar Donta +1
Compute Continuum (CC) systems comprise a vast number of devices distributed over computational tiers. Evaluating business requirements, i.e., Service Level Objectives (SLOs), requ…
Collaborative Inference in DNN-based Satellite Systems with Dynamic Task Streams
Jinglong Guan, Qiyang Zhang, Ilir Murturi +3
As a driving force in the advancement of intelligent in-orbit applications, DNN models have been gradually integrated into satellites, producing daily latency-constraint and comput…