@article{journals/annalsoftelecom/NogueiraPorvir25,

title = {PORVIR-5G: Programmability, ORchestration, and VIRtualization of next-generation networks},

author = {Jose Marcos Silva Nogueira and Paulo Henrique Lopes Rettore and Clayson Sandro Francisco Sousa Celes and Fernando Garcia Diniz Campos Ferreira and Daniel Fernandes Macedo and Juliano Araujo Wickboldt and Vinícius Fernandes Soares Mota and Magnos Martinello and Rodolfo Silva Villaça and Cristiano Bonato Both and Christian Rodolfo Esteve Rothenberg},

url = {https://link.springer.com/article/10.1007/s12243-025-01136-7},

doi = {10.1007/s12243-025-01136-7},

issn = {1958-9395},

year  = {2025},

date = {2025-12-18},

urldate = {2025-12-18},

journal = {Annals of Telecommunications},

abstract = {This paper describes the goals, current state, and future directions of the PORVIR-5G project, which aims to develop and demonstrate a programmable fronthaul and backhaul integrating wireless with optical-packet networks and cloud computing solutions. The project exploits virtual network splits that optimize resource allocation across the wireless, optical, packet, and compute/storage domains. The key enablers for PORVIR-5G are (i) packet slicing, wireless, and optical resources, controlled by (ii) deep programmability interfaces, where devices are configured by network functions to provide the required performance for future applications on the Internet. This programmability allows for a more refined (iii) end-to-end and multilayer orchestration, considering the users’ quality of experience (QoE) for each type of application over the network. This paper also validates and demonstrates the proposed programmability and virtualization capabilities of the PORVIR-5G through demonstrations, thereby enabling the key performance demands of 5G networks.},

note = {In press},

keywords = {5G, Network Orchestration, Network Virtualization & Slicing, Softwarized & Programmable Networks},

pubstate = {published},

tppubtype = {article}

}

@article{journal/access/MartinsSFI223,

title = {Enhancing Network Slicing Architectures With Machine Learning, Security, Sustainability and Experimental Networks Integration},

author = {Joberto Sérgio Barbosa Martins and Tereza Cristina Melo Brito Carvalho and Rodrigo Moreira and Cristiano Bonato Both and Adnei Donatti and João H. Corrêa and José Augusto Suruagy Monteiro and Sand Luz Corrêa and Antônio Jorge Gomes Abelém and Moisés Renato Nunes Ribeiro and José Marcos Silva Nogueira and Luiz Claudio Schara Magalhães and Juliano Araujo Wickboldt and Tiago Coelho Ferreto and Ricardo Mello and Rafael Pasquini and Marcos Schwarz and Leobino Nascimento Sampaio and Daniel Fernandes Macedo and José Ferreira Rezende and Kleber Vieira Cardoso and Flávio Oliveira Silva},

doi = {10.1109/ACCESS.2023.3292788},

year  = {2023},

date = {2023-07-05},

journal = {IEEE Access},

volume = {11},

pages = {69144-69163},

abstract = {Network Slicing (NS) is an essential technique extensively used in 5G networks computing strategies, mobile edge computing, mobile cloud computing, and verticals like the Internet of Vehicles and industrial IoT, among others. NS is foreseen as one of the leading enablers for 6G futuristic and highly demanding applications since it allows the optimization and customization of scarce and disputed resources among dynamic, demanding clients with highly distinct application requirements. Various standardization organizations, like 3GPP’s proposal for new generation networks and state-of-the-art 5G/6G research projects, are proposing new NS architectures. However, new NS architectures have to deal with an extensive range of requirements that inherently result in having NS architecture proposals typically fulfilling the needs of specific sets of domains with commonalities. The Slicing Future Internet Infrastructures (SFI2) architecture proposal explores the gap resulting from the diversity of NS architectures target domains by proposing a new NS reference architecture with a defined focus on integrating experimental networks and enhancing the NS architecture with Machine Learning (ML) native optimizations, energy-efficient slicing, and slicing-tailored security functionalities. The SFI2 architectural main contribution includes the utilization of the slice-as-a-service paradigm for end-to-end orchestration of resources across multi-domains and multi-technology experimental networks. In addition, the SFI2 reference architecture instantiations will enhance the multi-domain and multi-technology integrated experimental network deployment with native ML optimization, energy-efficient aware slicing, and slicing-tailored security functionalities for the practical domain.},

keywords = {Experimental Approach, Machine Learning, Network Orchestration, Network Security, Network Virtualization & Slicing},

pubstate = {published},

tppubtype = {article}

}

@article{journals/jnsm/Martins5GMS23,

title = {Assisted Monitoring and Security Provisioning for 5G Microservices-Based Network Slices with SWEETEN},

author = {Rafael de Jesus Martins and Juliano Araujo Wickboldt and Lisandro Zambenedetti Granville},

url = {https://link.springer.com/article/10.1007/s10922-023-09728-1},

doi = {10.1007/s10922-023-09728-1},

issn = {1573-7705},

year  = {2023},

date = {2023-02-12},

urldate = {2023-02-12},

journal = {Journal of Network and Systems Management (JNSM)},

volume = {31},

number = {2},

pages = {36},

abstract = {5G networks have imposed a drastic shift in how mobile telecommunications must operate. In order to comply with the new requirements, solutions based on network function virtualization (NFV) and network slicing must be carried out. Regarding NFV in particular, the trend towards pulverizing the monolithic software in a microservices-based one carries network management challenges to operators. The deployment and integration of one or more network management software with the managed services is as important as it is delicate, as stringent requirements of 5G applications must be respected. In this paper, we propose SWEETEN as a solution for automating the deployment and transparently integrating network management solutions from different management disciplines, in this case, monitoring and security. Demonstrating its usability through a intelligent healthcare use case, SWEETEN is shown to transparently provide monitoring and security solutions for a complete network slice, enabling compliance with privacy requirements through minimal low-level interventions from the network slice tenant. The results show how SWEETEN integration of monitoring and security disciplines can assist users in guaranteeing the correct operation of their deployments regardless of the underlying software solutions used.},

keywords = {5G, Cloud Computing, Microservices, Network Orchestration, Network Security, Network Virtualization & Slicing},

pubstate = {published},

tppubtype = {article}

}

@article{journal/cn/Martins20,

title = {Virtual Network Functions Migration Cost: from Identification to Prediction},

author = {Rafael de Jesus Martins and Cristiano Bonato Both and Juliano Araujo Wickboldt and Lisandro Zambenedetti Granville},

url = {http://www.sciencedirect.com/science/article/pii/S138912862031118X},

doi = {10.1016/j.comnet.2020.107429},

issn = {1389-1286},

year  = {2020},

date = {2020-11-09},

urldate = {2020-11-09},

journal = {Elsevier Computer Networks},

volume = {181},

pages = {107429},

abstract = {The advent of the function virtualization concept, especially that of network functions, leads to important benefits for future networks. Although the orchestration of virtualized functions presents gains for network operators and clients alike, the overhead for moving functions has not been thoroughly explored so far, especially considering functions virtualized by using container technologies. In this work, we investigate orchestration costs associated with the migration of containerized virtual functions. To this end, we first perform a systematic literature review on state-of-the-art virtual function migration costs, electing time and data transferred as so. We then use a well-known container platform (LXD) to perform several orchestration experiments in a controlled environment. By analyzing the container migration process in smaller complementary steps, and designing experiments to evaluate them individually, a pattern for migration costs is observed. Linear regression is then used to derive a prediction model for the necessary time and data transferring for performing a container migration. To assess the predictor’s accuracy, we present a cloud computing use case where the predictor is deployed. Results indicate that predictions can be accurate within reasonable range, and therefore orchestration algorithms may be improved by accounting for similar prediction models when determining the migration of one or more virtualized functions.},

keywords = {Container Management & Orchestration, Network Orchestration, Network Virtualization & Slicing},

pubstate = {published},

tppubtype = {article}

}

@article{journal/access/Resende20,

title = {COPA: Experimenter-level Container Orchestration for Networking Testbeds},

author = {Henrique Cesar Carvalho de Resende and Matias Artur Klafke Schimuneck and Cristiano Bonato Both and Juliano Araujo Wickboldt and Johann M. Márquez-Barja},

url = {https://ieeexplore.ieee.org/document/9247110},

doi = {10.1109/ACCESS.2020.3035619},

issn = {2169-3536},

year  = {2020},

date = {2020-11-03},

urldate = {2020-11-03},

journal = {IEEE Access},

volume = {8},

pages = {201781-201798},

abstract = {As Cloud Computing (CC) branched areas such as Multi-access Edge Computing (MEC) and Fog computing are still on growing research interest. The creation of new tools to improve quality and speed the experimentation in such areas is a general interest. In this article, we propose COPA, an experimenter-level container orchestration tool for networking testbeds. This tool provides a friendly interface for the experimenter test container orchestration algorithms which can start, stop, copy, and even migrate a container from one host to another. COPA also includes network/resources monitoring to feed the experimenter’s orchestration algorithm so that it can make decisions based on real-time environment information. Furthermore, the experimenter can automatize the experiment scenario setup and deployment by pre-configuring in COPA. This tool helps the experimenter in testing different scenarios and quickly changing experiment parameters. Considering these features, COPA aims to provide an experimentation architecture to deploy and test container orchestration algorithms. Furthermore, we provide a case study explaining how COPA can be a key tool in the MEC and Network Function Virtualization (NFV) experimentation environments. This tool was already deployed in Federated Union of Telecommunications Research Facilities for an EU-Brazil Open Laboratory (FUTEBOL) testbeds as part of the control framework and was well validated by the project reviewers and partners.},

keywords = {5G, Cloud Computing, Container Management & Orchestration, Fog & Edge Computing, Network Orchestration, Network Virtualization & Slicing},

pubstate = {published},

tppubtype = {article}

}

@article{journals/jsac/DallaCosta20,

title = {Orchestra: A Customizable Split-Aware NFV Orchestrator for Dynamic C-RAN},

author = {Ariel Galante Dalla-Costa and Lucas Bondan and Juliano Araujo Wickboldt and Cristiano Bonato Both and Lisandro Zambenedetti Granville},

url = {https://ieeexplore.ieee.org/document/9060959},

doi = {10.1109/JSAC.2020.2986689},

issn = {0733-8716},

year  = {2020},

date = {2020-04-08},

journal = {IEEE Journal on Selected Areas in Communications},

volume = {38},

number = {6},

pages = {1014--1024},

abstract = {Dynamic Cloud Radio Access Networks (C-RAN) is an emerging wireless architecture that splits radio functions in a hierarchical cloud-based infrastructure. In Dynamic C-RAN, wireless functionalities can be divided into smaller components and distributed along with a hierarchical cloud infrastructure. Network Functions Virtualization (NFV) concepts have been recently investigated to facilitate managementrelated operations of these wireless functionalities. Despite the advances in providing flexible NFV orchestration for Virtualized Network Functions (VNF)s, there is still a lack of solutions aware of VNFs internal composition, a key characteristic of split virtualized radio functions. In this article, we advance NFV orchestration in a Dynamic C-RAN scenario presenting Orchestra, a split-aware NFVO for Dynamic C-RAN with support to customizable orchestration algorithms for different radio function splits. Orchestra is validated through instantiates and migrates VNFCs following the decisions of personalized orchestration algorithms, with a petty impact in the VNFC’s deployment and migration time.},

keywords = {5G, Cloud Computing, Cloud Radio Access Networks (C-RAN), Network Orchestration, Network Virtualization & Slicing, Wireless Networks},

pubstate = {published},

tppubtype = {article}

}