An Edge-based Architecture for Phasor Measurements in Smart Grids

Galantino, Stefano; Risso, Fulvio; Cazzaniga, Andrea; Garrone, Fabrizio; Terruggia, Roberta; Lazzari, Riccardo

doi:10.23919/aeit56783.2022.9951842

Cited by 2 publications

(2 citation statements)

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“…In a federation, computing resources are shared between clusters, allowing each entity to access additional resources if needed. This resource sharing can be achieved through the multi-cloud functionalities provided by Liqo 9 , which is already being used as an enabling technology in the European project FLUIDOS 10 to create distributed continuum infrastructures. Practical performance metrics.…”

Section: G Real-world Implementation Considerationsmentioning

confidence: 99%

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Scheduling Multi-Component Applications Across Federated Edge Clusters With Phare

Castellano,

Galantino,

Risso

et al. 2024

IEEE Open J. Commun. Soc.

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The shift towards agile microservice architecture has enabled significant benefits for IT companies but has also resulted in increased complexity for Cloud orchestration tools. Traditional tools were designed for centralized data centers and are ineffective for locating microservices in geographically-distributed edge-like infrastructures. This paper presents Phare, a decentralized scheduling algorithm designed to optimize the placement of microservices by satisfying their computing and communication demands while minimizing deployment costs. Phare employs a heuristic-based approach to solve the NP-Hard scheduling problem, prioritizing the microservices with the more stringent requirements and placing them on the most convenient computing facilities, based on the concept of affinity, contributing to the field by providing a more holistic approach to resource scheduling in edge computing. We validate our approach against Firmament, the state-of-the-art workload scheduling algorithm for component-based applications, on simulated edge infrastructures with hundreds of clusters. Phare achieves up to a 10× reduction in terms of deployment costs compared to Firmament while providing a much lower scheduling latency.

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Section: G Real-world Implementation Considerationsmentioning

confidence: 99%

“…With the advent of Edge computing, telecommunication networks, IoT systems, and Smart City/Grid technologies have significantly enhanced their operational efficiency and resilience. These advancements may leverage thousands of distributed computing resources, markedly improving the Quality of Experience (QoE) and system robustness [9].…”

Section: Introductionmentioning

confidence: 99%