Case-based Reasoning for Configuring Bandwidth Allocation Models - Raciocínio Baseado em Casos para a Configuração de Modelos de Alocação de Banda
Creators: name: de Oliveira, Eliseu Morais
Publisher: name: Zenodo
Year: 2022
Subjects: Case-based Reasoning
Resource Allocation
Bandwidth Allocation Model
Learning
Artificial Intelligence
Machine Learning
Network Management

description: The extensive adoption of computer networks, especially the Internet, using services that require extensive data flows, has generated a growing demand for computational resources, mainly bandwidth. Bandwidth Allocation Models (BAM) have proven to be a viable alternative to network management where the bandwidth resource is shared to meet the high demand for the network. However, managing these networks has become an increasingly complex task, and solutions that allow for nearly autonomous configuration with less intervention of the network manager are highly demanded. The use of Case-Based Reasoning (CBR) techniques for network management has proven satisfactory for decision making and network management. This work presents a proposal for network reconfiguration based on the CBR cycle, intelligence, and cognitive module for MPLS (Multi-Protocol Label Switching) networks. The results show that CBR is a feasible solution for auto-configuration with autonomic characteristics in the MPLS using bandwidth allocation models (BAMs). The proposal improved the general network performance.
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