Inicio  /  Future Internet  /  Vol: 14 Par: 12 (2022)  /  Artículo
ARTÍCULO
TITULO

Integrated SDN-NFV 5G Network Performance and Management-Complexity Evaluation

Nico Surantha and Noffal A. Putra    

Resumen

Digitalization is one of the factors that affects the acceleration of the application of telecommunications technologies such as 5G. The 5G technology that has been developed today does not yet meet different performance and manageability standards, particularly for data center networks as a supportive technology. Software-defined networking (SDN) and network function virtualization (NFV) are two complementary technologies that are currently used by almost all data centers in the telecommunications industry to rectify performance and manageability issues. In this study, we deliver an integrated SDN-NFV architecture to simplify network management activities in telecommunication companies. To improve network performance at the computing level, we performed a modification of a networking system at the computing level, underlying NFV devices by replacing the default virtual switch with a data plane development kit (DPDK) and single root I/O virtualization (SR-IOV). This study evaluated the proposed architecture design in terms of network performance and manageability. Based on 30 days of observation in prime time, the proposed solution increased throughput up to 200 Mbps for the server leaf and 1.6 Gbps for the border leaf compared to the legacy architecture. Meanwhile, the latency decreased to 12 ms for the server leaf and 17 ms for the border leaf. For manageability, we tested three different scenarios and achieved savings of 13 min for Scenario 1, 22 min for Scenario 2 and 9 min for Scenario 3.

 Artículos similares

       
 
Binita Kusum Dhamala, Babu R. Dawadi, Pietro Manzoni and Baikuntha Kumar Acharya    
Graph representation is recognized as an efficient method for modeling networks, precisely illustrating intricate, dynamic interactions within various entities of networks by representing entities as nodes and their relationships as edges. Leveraging the... ver más
Revista: Future Internet

 
Mustafa Erkan Turan and Tulin Cetin    
Sewer systems are a component of city infrastructure that requires large investment in construction and operation. Metaheuristic optimization methods have been used to solve sewer optimization problems. The aim of this study is to investigate the effects... ver más
Revista: Water

 
Jiahui Zhao, Zhibin Li, Pan Liu, Mingye Zhang     Pág. 115 - 142
Demand prediction plays a critical role in traffic research. The key challenge of traffic demand prediction lies in modeling the complex spatial dependencies and temporal dynamics. However, there is no mature and widely accepted concept to support the so... ver más

 
Benjamin Burrichter, Juliana Koltermann da Silva, Andre Niemann and Markus Quirmbach    
This study employs a temporal fusion transformer (TFT) for predicting overflow from sewer manholes during heavy rainfall events. The TFT utilised is capable of forecasting overflow hydrographs at the manhole level and was tested on a sewer network with 9... ver más
Revista: Hydrology

 
Yong Liu, Xiaohui Yan, Wenying Du, Tianqi Zhang, Xiaopeng Bai and Ruichuan Nan    
The current work proposes a novel super-resolution convolutional transposed network (SRCTN) deep learning architecture for downscaling daily climatic variables. The algorithm was established based on a super-resolution convolutional neural network with t... ver más
Revista: Water