The wide availability of heterogeneous resources at the Edgeof the network is gaining a central role in defining and developing newcomputing paradigms for both the infrastructures and the applications.However, it becomes challenging to optimize the system's behaviour, dueto the Edge's highly distributed and dynamic nature. Recent solutionspropose new decentralized, self-adaptive approaches to face the needs ofthis scenario. One of the most challenging aspect is related to the opti-mization of the system's energy consumption. In this paper, we proposea fully decentralized solution that limits the energy consumed by thesystem, without failing to match the users expectations, defined as theservices' Quality of Experience (QoE.). Specifically, we propose a schemewhere the autonomous coordination of entities at Edge is able to reducethe energy consumption by reducing the number of instances of the ap-plications executed in system. This result is achieve without violatingthe services' QoE, expressed in terms of latency. Experimental evalua-tions through simulation conducted with PureEdgeSim demonstrate theeffectiveness of the approach

Self- organizing energy-minimization placement of QoE-constrained services at the edge

Mordacchini M;Ferrucci L;Carlini E;Kavalionak H;Coppola M;Dazzi P
2021

Abstract

The wide availability of heterogeneous resources at the Edgeof the network is gaining a central role in defining and developing newcomputing paradigms for both the infrastructures and the applications.However, it becomes challenging to optimize the system's behaviour, dueto the Edge's highly distributed and dynamic nature. Recent solutionspropose new decentralized, self-adaptive approaches to face the needs ofthis scenario. One of the most challenging aspect is related to the opti-mization of the system's energy consumption. In this paper, we proposea fully decentralized solution that limits the energy consumed by thesystem, without failing to match the users expectations, defined as theservices' Quality of Experience (QoE.). Specifically, we propose a schemewhere the autonomous coordination of entities at Edge is able to reducethe energy consumption by reducing the number of instances of the ap-plications executed in system. This result is achieve without violatingthe services' QoE, expressed in terms of latency. Experimental evalua-tions through simulation conducted with PureEdgeSim demonstrate theeffectiveness of the approach
2021
Istituto di informatica e telematica - IIT
Istituto di Scienza e Tecnologie dell'Informazione "Alessandro Faedo" - ISTI
Inglese
Konstantinos Tserpes, Jörn Altmann, José Ángel Bañares, Orna Agmon Ben-Yehuda, Karim Djemame, Vlado Stankovski, Bruno Tuffin
Economics of Grids, Clouds, Systems, and Services
GECON 2021: 18th International Conference on Economics of Grids, Clouds, Systems and Services
133
142
9
9783030929152
https://link.springer.com/chapter/10.1007/978-3-030-92916-9_11
Sì, ma tipo non specificato
21-23/09/2021
Virtual Event, Rome
Edge computing
Self-organizing
6
partially_open
Mordacchini, M; Ferrucci, L; Carlini, E; Kavalionak, H; Coppola, M; Dazzi, P
273
info:eu-repo/semantics/conferenceObject
04 Contributo in convegno::04.01 Contributo in Atti di convegno
   Adaptive edge/cloud compute and network continuum over a heterogeneous sparse edge infrastructure to support nextgen applications
   ACCORDION
   H2020
   871793
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Descrizione: Self- organizing energy-minimization placement of QoE-constrained services at the edge
Tipologia: Versione Editoriale (PDF)
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/20.500.14243/400210
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