Carlos Miguel Ferreira

Since today's networks use traditional centralized management systems, the management became costly with the growth in the number of network equipments and available services. It became then clear that it was necessary to distribute the central management responsibilities throughout the network equipments.

This article proposes an Autonomic Decision System with Learning capabilities based on Artificial Intelligence concepts, to be used by network equipments in mesh-network environments… Show more

Since today's networks use traditional centralized management systems, the management became costly with the growth in the number of network equipments and available services. It became then clear that it was necessary to distribute the central management responsibilities throughout the network equipments.

This article proposes an Autonomic Decision System with Learning capabilities based on Artificial Intelligence concepts, to be used by network equipments in mesh-network environments without the need of a central knowledge. Considering a specific case of QoS routing, this system is able to establish bandwidth-aware communication paths between pairs of nodes in a distributed approach, without the complete knowledge of the network and the available bandwidth of its links.

To develop this system in a real network an architecture has been specified and built, denote as DistArch. This architecture provides all the functionalities to perform distributed autonomic decisions in large-scale networks.

The results of this approach show that, by cooperating with neighbour network agents, even without a full knowledge of the network state, it is possible to establish bandwidth-aware communication paths as optimal as the ones obtained with a central decision approach that contains full network information, being able to react to network changes with a fast convergence.

DOI: 10.1016/j.jocs.2017.04.010 Show less

DOI: 10.1007/s10922-016-9398-4

Nowadays, the prevailing use of networks based on traditional centralized management systems reflects on a fast increase of the management costs. The growth in the number of network equipments and services reinforces the need to distribute the management responsibilities throughout the network devices. In this approach, each device executes common network management functionalities, being part of the overall network management platform. In this paper, we… Show more

DOI: 10.1007/s10922-016-9398-4

Nowadays, the prevailing use of networks based on traditional centralized management systems reflects on a fast increase of the management costs. The growth in the number of network equipments and services reinforces the need to distribute the management responsibilities throughout the network devices. In this approach, each device executes common network management functionalities, being part of the overall network management platform. In this paper, we present a Unified Distributed Network Management (UDNM) framework that provides a unified (wired and wireless) management network solution, where further different network services can take part of this infrastructure, e.g., flow monitoring, accurate routing decisions, distributed policies dissemination, etc. This framework is divided in two main components: (A) Situation awareness, which sets up initial information through bootstrapping, discovery, fault-management process and exchange of management information; (B) Autonomic Decision System (ADS) that performs distributed decisions in the network with incomplete information. We deploy the UDNM framework in a testbed which involves two cities (≈250 km between), different standards (IEEE 802.3, IEEE 802.11 and IEEE 802.16e) and network technologies, such as, wired virtual grid, wireless ad-hoc gateways, ad-hoc mobile access devices. The UDNM framework integrates management functionalities into the managed devices, proving to be a lightweight and easy-respond framework. The performance analysis shows that the UDNM framework is feasible to unify devices management functionalities and to take accurate decisions on top of a real network. Show less

Routing protocols for Mesh-Networks have been intensively researched in the past years.
Protocols such as the AODV, OLSR, Robin-Mesh, BATMAN Adv and Netsukuku are examples from the conducted research.
But one common aspect among these mesh routing protocols is the inability to identify and select a specific network path to route packets.

The application of autonomic self-* properties has always been a challenge, mainly because of the existing limitations with the communication… Show more

Routing protocols for Mesh-Networks have been intensively researched in the past years.
Protocols such as the AODV, OLSR, Robin-Mesh, BATMAN Adv and Netsukuku are examples from the conducted research.
But one common aspect among these mesh routing protocols is the inability to identify and select a specific network path to route packets.

The application of autonomic self-* properties has always been a challenge, mainly because of the existing limitations with the communication capabilities.
Being able to select a specific path to route packets in a mesh network is a capability which an autonomic agent can use to ensure communication quality and self-healing.

This paper proposes a computationally distributed technique to uniquely identify specific network paths with global identifiers, generated by using hash functions.
Path identifiers (Path IDs) can be used by the Autonomic Agents (Peers) in a communications network to implement redundancy or traffic engineering, without resorting to centralized management, full network consensus or full topological knowledge replication. Show less

DOI: 10.1109/ISCC.2015.7405562

With the emergence of OpenFlow, the first Software Defined Network (SDN) communication protocol standard, it is important to understand how current centralized network management platforms can be adapted to support this new protocol.
This paper demonstrates how legacy centralized management systems, and their respective network devices, can be upgraded to provide Multi-Protocol Label Switching (MPLS) and Metro Ethernet Forum (MEF) services using the… Show more

DOI: 10.1109/ISCC.2015.7405562

With the emergence of OpenFlow, the first Software Defined Network (SDN) communication protocol standard, it is important to understand how current centralized network management platforms can be adapted to support this new protocol.
This paper demonstrates how legacy centralized management systems, and their respective network devices, can be upgraded to provide Multi-Protocol Label Switching (MPLS) and Metro Ethernet Forum (MEF) services using the OpenFlow protocol. Show less

This paper discusses the benefits of using a hardware coprocessor to improve the determinism and performance of a Real-Time Kernel. The proposed coprocessor was modeled with the VHDL hardware description language and implemented in a FPGA (Field-Programmable Gate Array). It is able to manage (schedule, preempt and dispatch) several tasks, either periodic or aperiodic. The preemption of the task running on the Central Processing Unit (CPU) is performed through an interrupt line that connects the… Show more

This paper discusses the benefits of using a hardware coprocessor to improve the determinism and performance of a Real-Time Kernel. The proposed coprocessor was modeled with the VHDL hardware description language and implemented in a FPGA (Field-Programmable Gate Array). It is able to manage (schedule, preempt and dispatch) several tasks, either periodic or aperiodic. The preemption of the task running on the Central Processing Unit (CPU) is performed through an interrupt line that connects the coprocessor to the CPU. External interrupt sources are connected to the coprocessor to allow a controlled activation and dispatching of the respective service tasks. The validation and benchmarking of the real-time kernel with the co-processing unit, shows a significant increase on the determinism and performance of the system, when compared with the same system but without the help of the coprocessing unit, i.e. running fully in software. Show less