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Table 15 Summary of ML-based Resource Allocation

From: A comprehensive survey on machine learning for networking: evolution, applications and research opportunities

Ref. ML Technique Network Dataset Features Output Evaluation
       Settings Results
Baldo et al. [35] Supervised: · MLP-NN Wireless networks Simulation data generated using ns-Miracle simulator · Signal to noise ratio · Received frames · Erroneous frames · Idle time · Throughput · Delay · Reliability 2 layers with 6 neurons in the hidden layer Very good accuracy
Bojovic [65] Supervised: · MLP-NN Wireless LAN Synthetic data generated using testbed · Signal to noise ratio · Probability of failure · Business ratio · Average beacon delay · Number of detected stations · Throughput of an access point 2 layers with varying number of nodes in the hidden layer, maximum number of epochs, and learning rate NRMSE = 8%
Adeel et al. [6] RNN with GD, AIWPSO, and DE Cellular network Synthetically generated using a SEAMCAT LTE simulator · Signal to interference noise ratio · Inter-cell-interference · Modulation/coding schemes · Transmit power Throughput 5-8-1a Mean square error · AIWPSO: 8.5 ×10−4· GD: 1.03 ×10−3 · DE: 9.3 ×10−4
Testolin et al. [443] Supervised: · Linear classifier Unsupervised: · RNN Wireless networks 38 video clips taken from CIF · Video frame size · Quality level of each video in terms of the average SSIM index 32 visible units with a varying number of hidden units RMSE < 3%
Mijumbi et al. [312] RL · Q-learning (ε-greedy and softmax) VNs Simulation on ns-3 and real Internet traffic traces States · Percentages of allocated and unused resources in substrate nodes and links Actions · Increase or decrease the percentages of allocated resource 29 states, 9 actions Improved the acceptance ratio
Mijumbi et al. [313] Supervised: · FNN VNF chains VoIP traffic traces · Dependency of resource requirements of each VNFC on its neighbor VNFCs · Historical local VNFC resource utilization · Resource requirements of each VNFC 2 NNs for each VNFC Accuracy  90%
Shi et al. [410] Supervised: · MDP · BN VNF chains Simulation data generated using WorkflowSim · Historical resource usage · Future resource reliability Running time for MDP: O(tv+1), where t and v stand for the number of NFV component tasks and the number of VMs, respectively Better than other greedy methods in terms of cost
  1. aNumber of neurons at the input layer, hidden, and output layers, respectively