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The publications and research associated with this repository is currently under review in the Journal of Network and Computer Applications In that research, we present HADES, an NFV solution for energy-efficient placement and resource allocation in heterogeneous infrastructures. HADES is an OSM (Open Source MANO) extension that allows the configuration of virtual network functions and their subsequent resource allocation and deployment at the edge, minimizing energy consumption and ensuring the quality of service. One of the main components of HADES is The effIcient TAsk and REsource Allocator module (iTAREA), responsible for deciding where should be executed each VNF/KNF and the amount of memory, disk, bandwidth, and percentage of CPU that the nodes must allocate to the execution of each of them. This repository contains two benchmark versions of the iTAREA module: A time Benchmark version of the iTAREA module to measure its execution time for different problem sizes (number of tasks and nodes), and randomized applications and infrastructures. An energy Benchmark version of the iTAREA module to measure the reduction in energy consumption obtained for different problem sizes (number of tasks and nodes), and randomized applications and infrastructures. This implementation also contains the logic of other 5 assignment policies to measure their reduction in energy consumption: First-fit, Random-fit, Fastest-fit, Best-fit and kube-scheduler (the Kubernetes’ assignment policy). This work is supported by the European Union's H2020 research and innovation programme under grant agreement DAEMON 101017109 and by the projects co-financed by FEDER funds LEIA UMA18-FEDERJA-15 and IRIS PID2021-122812OB-I00 (MCI/AEI).
IoT, VNF placement, Open Source Mano, Edge Computing, energy efficiency, B5G, Feature Models
IoT, VNF placement, Open Source Mano, Edge Computing, energy efficiency, B5G, Feature Models
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