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Related Experiment Video

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Automated Deployment of an Internet Protocol Telephony Service on Unmanned Aerial Vehicles Using Network Functions Virtualization
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Intelligent Approach to Network Device Migration Planning towards Software-Defined IPv6 Networks.

Babu R Dawadi1, Danda B Rawat2, Shashidhar R Joshi1

  • 1Department of Electronics and Computer Engineering, Pulchowk Campus, Tribhuvan University, Kathmandu 19758, Nepal.

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|January 11, 2022
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Summary
This summary is machine-generated.

This study introduces an Adaptive Neuro Fuzzy Inference System (ANFIS) to assess network device compatibility for Internet protocol version 6 (IPv6) and software-defined networking (SDN) upgrades. ANFIS accurately identifies devices needing replacement, aiding telecom providers in sustainable network migration.

Keywords:
ANFISIPv6SDNSoDIP6migration planningnetwork device

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Area of Science:

  • Computer Science
  • Network Engineering

Background:

  • Internet and telecom providers face financial challenges migrating from IPv4 to IPv6 and SDN due to backward compatibility issues.
  • Accurate assessment of existing network device upgradeability is crucial for optimizing capital and operational expenditures.

Purpose of the Study:

  • To develop and evaluate an intelligent system for classifying network devices as upgradable or requiring replacement for IPv6 and SDN compatibility.
  • To assist service providers in planning efficient and sustainable network transitions.

Main Methods:

  • Implementation of an Adaptive Neuro Fuzzy Inference System (ANFIS) for device status identification.
  • Establishment of a knowledge base (KB) storing device firmware, SDN/IPv6 support, and end-of-life data.
  • Performance metrics (CPU, throughput, memory) used as input for ANFIS, compared against SVM, fine tree, and linear regression.

Main Results:

  • ANFIS demonstrated superior accuracy and optimality in classifying network device upgradeability compared to SVM, fine tree, and linear regression.
  • The ANFIS approach effectively integrates device performance metrics with KB data for classification.

Conclusions:

  • The ANFIS-based classification system provides an accurate and optimal solution for identifying network devices for migration to SDN-enabled IPv6 networks.
  • This method supports service providers in making informed decisions for smooth and cost-effective network transitions.