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Bio-inspired negotiation approach for smart-grid colocation datacenter operation.
Iturriaga, Santiago; Muraña, Jonathan; Nesmachnow, Sergio.
Afiliação
  • Iturriaga S; Department of Computer Science, Universidad de la República, Julio Herrera y Reissig 565, Montevideo, Uruguay.
  • Muraña J; Department of Computer Science, Universidad de la República, Julio Herrera y Reissig 565, Montevideo, Uruguay.
  • Nesmachnow S; Department of Computer Science, Universidad de la República, Julio Herrera y Reissig 565, Montevideo, Uruguay.
Math Biosci Eng ; 19(3): 2403-2423, 2022 01 05.
Article em En | MEDLINE | ID: mdl-35240790
Demand response programs allow consumers to participate in the operation of a smart electric grid by reducing or shifting their energy consumption, helping to match energy consumption with power supply. This article presents a bio-inspired approach for addressing the problem of colocation datacenters participating in demand response programs in a smart grid. The proposed approach allows the datacenter to negotiate with its tenants by offering monetary rewards in order to meet a demand response event on short notice. The objective of the underlying optimization problem is twofold. The goal of the datacenter is to minimize its offered rewards while the goal of the tenants is to maximize their profit. A two-level hierarchy is proposed for modeling the problem. The upper-level hierarchy models the datacenter planning problem, and the lower-level hierarchy models the task scheduling problem of the tenants. To address these problems, two bio-inspired algorithms are designed and compared for the datacenter planning problem, and an efficient greedy scheduling heuristic is proposed for task scheduling problem of the tenants. Results show the proposed approach reports average improvements between 72.9% and 82.2% when compared to the business as usual approach.
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Sistemas Computacionais / Negociação Idioma: En Revista: Math Biosci Eng Ano de publicação: 2022 Tipo de documento: Article País de afiliação: Uruguai País de publicação: Estados Unidos

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Sistemas Computacionais / Negociação Idioma: En Revista: Math Biosci Eng Ano de publicação: 2022 Tipo de documento: Article País de afiliação: Uruguai País de publicação: Estados Unidos