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Large Scale Energy Efficient Sensor Network Routing Using a Quantum Processor Unit
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A fully distributed traffic allocation algorithm for nonconcave utility maximization in connectionless communication

Jingyao Wang1,2, Mahmoud Ashour3, Constantino M Lagoa3

  • 1The Department of Automation, The Xiamen University, China.

Automatica : the Journal of IFAC, the International Federation of Automatic Control
|May 28, 2021
PubMed
Summary
This summary is machine-generated.

Optimizing internet resource allocation for IP video services is challenging due to nonconcave Quality of Experience (QoE) functions. This paper introduces a Fully Distributed Traffic Allocation Algorithm (FDTAA) for efficient, decentralized routing.

Keywords:
Connectionless communication networksFully distributed traffic allocation algorithmNetwork utility maximization problemNonconcave utility functionTraffic engineering

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Area of Science:

  • Computer Science
  • Network Engineering
  • Telecommunications

Background:

  • Internet Protocol (IP) video services are dominant, necessitating efficient resource allocation.
  • User Quality of Experience (QoE) for video services exhibits nonconcave data rate dependency, complicating optimization.
  • Existing methods struggle with decentralized optimization for complex utility functions.

Purpose of the Study:

  • To develop a Fully Distributed Traffic Allocation Algorithm (FDTAA) for optimizing internet resource allocation.
  • To address the challenge of maximizing network utility with nonconcave Quality of Experience functions.
  • To enable efficient packet routing in networks with decentralized control.

Main Methods:

  • Modeled traffic allocation as a network utility maximization problem using a fluid flow model.
  • Designed FDTAA for hop-by-hop forwarding, utilizing local information at each router.
  • Analyzed convergence properties of the algorithm for optimal network utility.

Main Results:

  • FDTAA operates in a fully distributed manner, requiring only local information for routing decisions.
  • The algorithm minimizes computational workload at each router.
  • Demonstrated convergence of network utility values to the optimal value at a rate of (1/K).

Conclusions:

  • FDTAA provides an effective solution for optimizing internet resource allocation in IP networks.
  • The algorithm's distributed nature and efficiency make it suitable for large-scale networks.
  • FDTAA successfully handles nonconcave utility functions, improving Quality of Experience for users.