Combining Declarative and Linear Programming for Application Management in the Cloud-Edge Continuum
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arXiv
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| Main Authors: | , , , |
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| Format: | Preprint |
| Published: |
2025
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| _version_ | 1866918249341386752 |
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| author | Massa, Jacopo Forti, Stefano Dazzi, Patrizio Brogi, Antonio |
| author_facet | Massa, Jacopo Forti, Stefano Dazzi, Patrizio Brogi, Antonio |
| contents | This work investigates the data-aware multi-service application placement problem in Cloud-Edge settings. We previously introduced EdgeWise, a hybrid approach that combines declarative programming with Mixed-Integer Linear Programming (MILP) to determine optimal placements that minimise operational costs and unnecessary data transfers. The declarative stage pre-processes infrastructure constraints to improve the efficiency of the MILP solver, achieving optimal placements in terms of operational costs, with significantly reduced execution times. In this extended version, we improve the declarative stage with continuous reasoning, presenting EdgeWiseCR, which enables the system to reuse existing placements and reduce unnecessary recomputation and service migrations. In addition, we conducted an expanded experimental evaluation considering multiple applications, diverse network topologies, and large-scale infrastructures with dynamic failures. The results show that EdgeWiseCR achieves up to 65% faster execution compared to EdgeWise, while preserving placement stability under dynamic conditions. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2504_12032 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Combining Declarative and Linear Programming for Application Management in the Cloud-Edge Continuum Massa, Jacopo Forti, Stefano Dazzi, Patrizio Brogi, Antonio Distributed, Parallel, and Cluster Computing This work investigates the data-aware multi-service application placement problem in Cloud-Edge settings. We previously introduced EdgeWise, a hybrid approach that combines declarative programming with Mixed-Integer Linear Programming (MILP) to determine optimal placements that minimise operational costs and unnecessary data transfers. The declarative stage pre-processes infrastructure constraints to improve the efficiency of the MILP solver, achieving optimal placements in terms of operational costs, with significantly reduced execution times. In this extended version, we improve the declarative stage with continuous reasoning, presenting EdgeWiseCR, which enables the system to reuse existing placements and reduce unnecessary recomputation and service migrations. In addition, we conducted an expanded experimental evaluation considering multiple applications, diverse network topologies, and large-scale infrastructures with dynamic failures. The results show that EdgeWiseCR achieves up to 65% faster execution compared to EdgeWise, while preserving placement stability under dynamic conditions. |
| title | Combining Declarative and Linear Programming for Application Management in the Cloud-Edge Continuum |
| topic | Distributed, Parallel, and Cluster Computing |
| url | https://arxiv.org/abs/2504.12032 |