From the 1 of 14 linked papers with an AI index.
14 papers
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…
Clustered Edge Intelligence: Beyond Just Convergence of Edge Computing and AI
Chinmaya Kumar Dehury, Boris Sedlak, Alaa Saleh +4
We are moving from an information age to the age of intelligence. A decade, or possibly less than that, data will not be the gold anymore rather the derived intelligence out of the…
Fair Comparison of Scheduling Algorithms on Heterogeneous Edge Clusters: A Continuous Adaptive Benchmark
Zihang Wang, Boris Sedlak, Juan Luis Herrera +1
Modern Artificial Intelligence (AI) workloads deployed across the heterogeneous tiers of an edge--cloud continuum must satisfy multi-dimensional Service Level Objectives (SLOs) ove…
Active Inference-Based Adaptive Routing for Heterogeneous Edge AI Services
Zihang Wang, Boris Sedlak, Schahram Dustdar
Edge computing enables AI inference closer to data sources, reducing latency and bandwidth costs. However, orchestrating AI services across the cloud-edge continuum remains challen…
Pricing-Driven Resource Allocation in the Computing Continuum
Alejandro GarcÃa-Fernández, Boris Sedlak, José Antonio Parejo +3
Deploying applications across the computing continuum requires selecting infrastructure nodes from geographically distributed and heterogeneous environments while satisfying constr…
Multi-Dimensional Autoscaling of Stream Processing Services on Edge Devices
Boris Sedlak, Philipp Raith, Andrea Morichetta +2
Edge devices have limited resources, which inevitably leads to situations where stream processing services cannot satisfy their needs. While existing autoscaling mechanisms focus e…