Energy efficiency is a key part of networking—it saves on cost and has an environmental impact. Multi-path routing is a well-known technique used for network traffic management to make it more efficient and reliable. Unfortunately, traditional multi-path routing techniques are oblivious to energy and suffer from poor energy utilization. This paper: An approach to efficient smart scheduling for multi-path routing with deep learning. Employing a deep learning algorithm with relevant network parameters allows us to predict the lightest path for processing in/outbound data. Simulation results demonstrate that our solution guarantees higher energy efficiency than conventional algorithms while enjoying better network performance. This solution proposes the formulation of a green and sustainable networking approach. Thus, it can be better adopted as an innovative security mechanism in many practical scenarios.

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Energy Efficient Smart Scheduling for Multi-path Routing Using Deep Learning

  • Amit Garg,
  • J. Logeshwaran,
  • S. Dhanasekaran,
  • Rishi Gupta,
  • Saurabh Singhal

摘要

Energy efficiency is a key part of networking—it saves on cost and has an environmental impact. Multi-path routing is a well-known technique used for network traffic management to make it more efficient and reliable. Unfortunately, traditional multi-path routing techniques are oblivious to energy and suffer from poor energy utilization. This paper: An approach to efficient smart scheduling for multi-path routing with deep learning. Employing a deep learning algorithm with relevant network parameters allows us to predict the lightest path for processing in/outbound data. Simulation results demonstrate that our solution guarantees higher energy efficiency than conventional algorithms while enjoying better network performance. This solution proposes the formulation of a green and sustainable networking approach. Thus, it can be better adopted as an innovative security mechanism in many practical scenarios.