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Updated: Oct 7, 2025

Large Scale Energy Efficient Sensor Network Routing Using a Quantum Processor Unit

Large Scale Energy Efficient Sensor Network Routing Using a Quantum Processor Unit

Published on: September 8, 2023

Optimal Routing in Stochastic Networks with Reliability Guarantees.

Wanzheng Zheng¹, Pranay Thangeda², Yagiz Savas³

¹Department of Aerospace Engineering, University of Illinois Urbana-Champaign, Urbana, USA.

Proceedings. IEEE Conference on Intelligent Transportation Systems

|January 10, 2022

Summary

This summary is machine-generated.

This study introduces a new routing policy for congested roads that minimizes expected travel time while ensuring a target on-time arrival probability. This approach addresses limitations of traditional methods, especially with high travel time variance.

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Area of Science:

Operations Research
Transportation Science
Computer Science

Background:

Optimal routing in congested networks with stochastic travel times is complex.
Minimizing only expected travel time is insufficient when travel time variance is high.

Purpose of the Study:

To develop a routing policy minimizing expected travel time under a strict on-time arrival probability constraint.
To address the practical need for reliable travel times in urban navigation.

Main Methods:

Modeling stochastic travel times as discrete random variables.
Formulating the routing problem as a Markov decision process.
Solving the problem as a linear program.

Main Results:

The proposed method generates routing policies that balance expected travel time with arrival time reliability.
A case study in Manhattan, New York, demonstrated the approach's efficacy using real-world data.

Conclusions:

The developed Markov decision process and linear programming framework effectively solves the constrained optimal routing problem.
This approach offers a more robust solution for navigation in stochastic urban environments.