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Large Scale Energy Efficient Sensor Network Routing Using a Quantum Processor Unit
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Termite inspired algorithm for traffic engineering in hybrid software defined networks.

R Ananthalakshmi Ammal1, Sajimon Pc1, Vinodchandra Ss2

  • 1Cyber Security Group, Centre for Development of Advanced Computing (CDAC), Thiruvananthapuram, Kerala, India.

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Summary
This summary is machine-generated.

This study introduces a novel Termite-Inspired Optimization algorithm for efficient network traffic management in hybrid Software-Defined Networking (SDN) environments. The algorithm enhances Quality of Service (QoS) and optimizes resource utilization, offering a superior alternative to traditional methods.

Keywords:
Hybrid SDNMulti Commodity Flow (MCF)Software Defined Networking (SDN)Termite-inspiredTraffic Engineering

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Area of Science:

  • Computer Science
  • Network Engineering
  • Artificial Intelligence

Background:

  • Managing real-time network traffic in the era of Internet of Things (IoT) and 5G networks presents significant challenges in Quality of Service (QoS) and resource utilization.
  • Traditional Traffic Engineering (TE) methods, including IP-based and MPLS-based approaches, face limitations in dynamic and hybrid network environments.
  • Software-Defined Networking (SDN) offers promising characteristics for advanced traffic scheduling and management, necessitating exploration of hybrid IP/SDN solutions.

Purpose of the Study:

  • To propose a novel bio-inspired algorithm for dynamic path allocation in hybrid IP/SDN networks.
  • To enhance network link utilization and meet elastic bandwidth demands.
  • To provide a more efficient and less complex traffic engineering solution compared to traditional MPLS TE.

Main Methods:

  • Development of a Termite-Inspired Optimization algorithm implemented within an SDN Controller.
  • Integration of the algorithm into a hybrid IP/SDN setup to manage network traffic.
  • Testing and validation of the algorithm's performance in simulated and physical testbeds.

Main Results:

  • The proposed algorithm effectively supports elastic bandwidth demands, avoids network congestion, and handles traffic priority.
  • Demonstrated graceful failure recovery in the event of link failures.
  • Achieved better network link utilization and performance compared to traditional MPLS TE setups.

Conclusions:

  • The Termite-Inspired Optimization algorithm is a viable and efficient solution for dynamic path allocation in hybrid IP/SDN networks.
  • The algorithm offers improved QoS, resource utilization, and resilience, making it a strong alternative to traditional TE mechanisms.
  • The proposed SDN-based approach can be readily implemented in existing Wide Area Networks (WANs) as a hybrid solution.