Rodolfo Villaca’s research while affiliated with Instituto Federal de Educação, Ciência e Tecnologia do Espírito Santo (IFES) and other places

A rastreabilidade é uma característica essencial para uma gestão eficaz das cadeias de suprimento, mas sua implementação pode enfrentar alguns desafios como garantia de integridade e acessibilidade dos registros. As blockchains, com sua estrutura descentralizada e imutável, prometem superar esses desafios, reforçando a segurança e a transparência dos dados. Apesar do crescente aumento dos estudos sobre a aplicação de blockchains em cadeias de suprimentos nos últimos anos, ainda há poucos trabalhos que explorem sua adoção no Brasil. Da mesma forma, o desenvolvimento de soluções voltadas para o mercado brasileiro é limitado, com poucos sistemas adaptados às suas necessidades específicas. Tendo isso em vista, o presente trabalho apresenta uma análise da adoção de blockchains no suporte à rastreabilidade em cadeias de suprimentos brasileiras, abordando tanto pesquisas acadêmicas quanto soluções desenvolvidas no país, fazendo, ao mesmo tempo, um paralelo com a adoção dessa tecnologia nas cadeias de suprimento estrangeiras. Com base nesse estudo, foram identificadas as potenciais dificuldades e barreiras à adoção de tecnologias blockchains nas cadeias de suprimento brasileiras.

Network Slicing (NS) has transformed the landscape of resource sharing in networks, offering flexibility to support services and applications with highly variable requirements in areas such as the next-generation 5G/6G mobile networks (NGMN), vehicular networks, industrial Internet of Things (IoT), and verticals. Although significant research and experimentation have driven the development of network slicing, existing architectures often fall short in intrinsic architectural intelligent security capabilities. This paper proposes an architecture-intelligent security mechanism to improve the NS solutions. We idealized a security-native architecture that deploys intelligent microservices as federated agents based on machine learning, providing intra-slice and architectural operation security for the Slicing Future Internet Infrastructures (SFI2) reference architecture. It is noteworthy that federated learning approaches match the highly distributed modern microservice-based architectures, thus providing a unifying and scalable design choice for NS platforms addressing both service and security. Using ML-Agents and Security Agents, our approach identified Distributed Denial-of-Service (DDoS) and intrusion attacks within the slice using generic and non-intrusive telemetry records, achieving an average accuracy of approximately $95.60\%$ in the network slicing architecture and $99.99\%$ for the deployed slice -- intra-slice. This result demonstrates the potential for leveraging architectural operational security and introduces a promising new research direction for network slicing architectures.

Ultra-reliable and low-latency communications are essential for new services and applications in Industry 4.0. URLLC is also required to provide traffic density to meet the throughput demands of its clients across the coverage area via cell densification. However, cell densification implies that handover between serving stations will become more and more frequent. In this paper, we introduce the Make Before Degrade solution for zero mobility interruption with a single radio connection. Mobility management is based on contextual information that allows prudently to shift traffic flows before their propagation paths are compromised. The paper brings a proof-of-principle software-defined WiFi testbed able to meet 3GPP’s traffic density specifications in which contextual information is provided by computer vision. An Industry 4.0 use case based on cloud robotics demonstrates the practical applicability of our proposal.

Real-time monitoring and measurement are the basis for most management operations, such as traffic engineering, quality of service assurance, and anomaly detection. Nevertheless, collecting measurements from all network devices with sampling and polling-based methods is not scalable. To tackle this issue, the P4 Language Consortium proposed the In-band Network Telemetry (INT) framework that provides real-time and fine-grain measurements in the data plane using telemetry packets. However, the task of specifying the route taken by a telemetry probe still relays on the traditional routing protocols, which require state changes in routing tables and fail to achieve the required accuracy, coverage and latency. In this context, this article investigates how to combine INT with a source routing method based on the stateless Multipath Polynomial Key-based Architecture (M-PolKA). We implemented this multipath telemetry solution as MPolKA-INT using the P4 language, and the experimental results showed low overhead in the data and control planes with agile and flexible path (re)configuration, since it does not require state changes in the routing tables of the devices in the network core.

Innovative traffic engineering functions and services require disrupting routing and forwarding mechanisms to be performed with low overhead over complex network topologies. Source routing (SR) is a prominent alternative to table-based routing for providing the needed expressiveness and agility by reducing the number of network states. This work proposes the M-PolKA, a topology-agnostic multipath source routing scheme and orchestration architecture for reliable communications, which explores special properties from the Residue Number System (RNS) polynomial arithmetic. A P4-based proof-of-concept is experimentally demonstrated using emulated and hardware prototypes. Also, use cases for revealing M-PolKA’s functionalities are tested in different scenarios in order to address problems, such as communication reliability improvement, agile path migration and fast failure reaction. Finally, low overhead for extra functionalities is observed when RNS-based SR is compared to traditional routing approaches.