| Full text | |
| Author(s): |
Pereira, Rickson S.
[1]
;
Lieira, Douglas D.
[1]
;
da Silva, Marco A. C.
[2]
;
Pimenta, Adinovam H. M.
[3]
;
da Costa, Joahannes B. D.
[4]
;
Rosario, Denis
[5]
;
Villas, Leandro
[4]
;
Meneguette, I, Rodolfo
Total Authors: 8
|
| Affiliation: | [1] Sao Paulo State Univ, Comp Syst Dept, UNESP, Campus Sao Jose Rio Preto, BR-15054000 Sao Paulo - Brazil
[2] I, Univ Sao Paulo, Inst Math & Comp Sci, BR-13566590 Sao Paulo - Brazil
[3] Fed Univ Sao Carlos UFSCAR, Comp Sci Dept, BR-13565905 Sao Carlos - Brazil
[4] Univ Estadual Campinas, Inst Comp, UNICAMP, BR-13083852 Campinas - Brazil
[5] Fed Univ Para UFPA, Comp Sci Fac, BR-66075110 Belem, Para - Brazil
Total Affiliations: 5
|
| Document type: | Journal article |
| Source: | SENSORS; v. 20, n. 19 OCT 2020. |
| Web of Science Citations: | 1 |
| Abstract | |
Technological advancement is currently focused on the miniaturization of devices, and integrated circuits allow us to observe the increase in the number of Internet of Things (IoT) devices. Most IoT services and devices require an Internet connection, which needs to provide the minimum processing, storage and networking requirements to best serve a requested service. One of the main goals of 5G networks is to comply with the user's various Quality of Service (QoS) requirements in different application scenarios. Fifth-generation networks use Network Function Virtualization (NFV) and Mobile Edge Computing (MEC) concepts to achieve these QoS requirements. However, the computational resource allocation mechanisms required by the services are considered very complex. Thus, in this paper, we propose an allocation and management resources mechanism for 5G networks that uses MEC and simple mathematical methods to reduce the model complexity. The mechanism decides to allocate the resource in MEC to meet the requirements requested by the user. The simulation results show that the proposed mechanism provides a larger amount of services, leading to a reduction in the service lock number and as a reduction in the blocking ratio of services due to the accuracy of the approach and its load balancing in the process of resource allocation. (AU) | |
| FAPESP's process: | 13/07375-0 - CeMEAI - Center for Mathematical Sciences Applied to Industry |
| Grantee: | Francisco Louzada Neto |
| Support Opportunities: | Research Grants - Research, Innovation and Dissemination Centers - RIDC |
| FAPESP's process: | 18/16703-4 - Vehicular cloud computing for information management in intelligent transportation systems |
| Grantee: | Joahannes Bruno Dias da Costa |
| Support Opportunities: | Scholarships in Brazil - Doctorate |
| FAPESP's process: | 20/07162-0 - Services for an intelligent transport system |
| Grantee: | Rodolfo Ipolito Meneguette |
| Support Opportunities: | Regular Research Grants |