2021
Conference article  Open Access

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

Mordacchini M., Ferrucci L., Carlini E., Kavalionak H., Coppola M., Dazzi P.

Edge computing  Self-organizing 

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

Source: GECON 2021: 18th International Conference on Economics of Grids, Clouds, Systems and Services, pp. 133–142, Virtual Event, Rome, 21-23/09/2021


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BibTeX entry
@inproceedings{oai:it.cnr:prodotti:458188,
	title = {Self- organizing energy-minimization placement of QoE-constrained services at the edge},
	author = {Mordacchini M. and Ferrucci L. and Carlini E. and Kavalionak H. and Coppola M. and Dazzi P.},
	doi = {10.1007/978-3-030-92916-9_11},
	booktitle = {GECON 2021: 18th International Conference on Economics of Grids, Clouds, Systems and Services, pp. 133–142, Virtual Event, Rome, 21-23/09/2021},
	year = {2021}
}

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Adaptive edge/cloud compute and network continuum over a heterogeneous sparse edge infrastructure to support nextgen applications


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