| Texto completo | |
| Autor(es): |
Xavier, Tiago C. S.
[1]
;
Santos, Igor L.
[2]
;
Delicato, Flavia C.
[3]
;
Pires, Paulo F.
[3]
;
Alves, Marcelo P.
[4]
;
Calmon, Tiago S.
[5]
;
Oliveira, Ana C.
[5]
;
Amorim, Claudio L.
[1]
Número total de Autores: 8
|
| Afiliação do(s) autor(es): | [1] Univ Fed Rio de Janeiro, PESC, BR-21941594 Rio De Janeiro, RJ - Brazil
[2] Ctr Fed Educ Tecnol Celso Suckow Fonseca CEFET RJ, BR-20271110 Rio De Janeiro, RJ - Brazil
[3] Univ Fed Fluminense, IC, BR-24210346 Niteroi, RJ - Brazil
[4] Univ Fed Rio de Janeiro, PPGI, BR-20001970 Rio De Janeiro, RJ - Brazil
[5] EMC Brazil, Rio De Janeiro - Brazil
Número total de Afiliações: 5
|
| Tipo de documento: | Artigo Científico |
| Fonte: | JOURNAL OF NETWORK AND COMPUTER APPLICATIONS; v. 159, JUN 1 2020. |
| Citações Web of Science: | 0 |
| Resumo | |
The conceptual approach known as Fog/Edge Computing has recently emerged, aiming to move part of the computing and storage resources from the cloud to the edge of the network. The combination of IoT devices, edge nodes, and the Cloud gives rise to a three-tier Cloud of Things (CoT) architecture. In the complex and dynamic CoT ecosystems, a key issue is how to efficiently and effectively allocate resources to meet the demands of applications. Similar to traditional clouds, the goal of resource allocation in the CoT is to maximize the number of applications served by the infrastructure while ensuring a target operational cost. We propose a resource allocation algorithm for CoT systems that (i) supports heterogeneity of devices and applications, (ii) leverages the distributed nature of edge nodes to promote collaboration during the allocation process and (iii) provides an efficient usage of the system resources while meeting latency requirements and considering different priorities of IoT applications. Our algorithm follows a heuristic-based approach inspired on an economic model for solving the resource allocation problem in CoT. A set of simulations were performed, with promising results, showing that our collaborative resource allocation algorithm is more scalable, reduces the response time for applications and the energy consumption of end devices, in comparison to a two-tier, Cloud-based approach. Moreover, the network traffic between edge nodes, and between the Edge and Cloud tiers, is considerably smaller when using our collaborative solution, in comparison to other evaluated approaches. (AU) | |
| Processo FAPESP: | 15/24144-7 - Tecnologias e soluções para habilitar o paradigma de nuvens de coisas |
| Beneficiário: | José Neuman de Souza |
| Modalidade de apoio: | Auxílio à Pesquisa - Temático |