• Computer Science > Distributed, Parallel, and Cluster Computing [Submitted on 20 Feb 2026] Title:A reliability- and latency-driven task allocation framework for workflow applications in the edge-hub-cloud continuum View PDF HTML (experimental)Abstract:A growing number of critical workflow applications leverage a streamlined edge-hub-cloud architecture, which diverges from the conventional edge computing paradigm. • An edge device, in collaboration with a hub device and a cloud server, often suffices for their reliable and efficient execution. • However, task allocation in this streamlined architecture is challenging due to device limitations and diverse operating conditions. • Given the inherent criticality of such workflow applications, where reliability and latency are vital yet conflicting objectives, an exact task allocation approach is typically required to ensure optimal solutions. • As no existing method holistically addresses these issues, we propose an exact multi-objective task allocation framework to jointly optimize the overall reliability and latency of a workflow application in the specific edge-hub-cloud architecture. • We present a comprehensive binary integer linear programming formulation that considers the relative importance of each objective.
Article Summaries:
- A new study proposes an exact multi‑objective task‑allocation framework for workflow applications that run on a streamlined edge‑hub‑cloud architecture. The authors formulate the problem as a binary integer linear program that jointly optimises reliability and latency, incorporating time‑redundancy techniques and constraints often omitted in prior work. Evaluation on a real‑world workflow and a suite of synthetic workloads shows the method improves reliability by an average of 84 % and reduces latency by 50 % compared with baseline strategies. Execution times range from 0.03 to 50.94 seconds, indicating the approach scales well across diverse workflow sizes and criticalities.
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