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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

Decentralized routing on spatial networks with stochastic edge weights.

Till Hoffmann¹, Renaud Lambiotte, Mason A Porter

¹Astrophysics Group, Imperial College London, London, United Kingdom.

Physical Review. E, Statistical, Nonlinear, and Soft Matter Physics

|September 17, 2013

Summary

This study introduces a decentralized routing algorithm for spatial networks with unpredictable travel times. It guides travelers without needing complete network information, improving navigation in complex environments.

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Area of Science:

Computer Science
Network Science
Algorithm Design

Background:

Traditional shortest path algorithms assume deterministic edge weights and global network knowledge.
Real-world networks often feature stochastic (random) edge weights and limited information availability.
Decentralized approaches are needed for routing in dynamic and partially observable networks.

Purpose of the Study:

To develop and evaluate a decentralized algorithm for finding short paths in spatial networks with stochastic edge weights.
To enable en route guidance without requiring global knowledge of the entire network.
To introduce a criterion for discriminating between arrival probability distributions for effective routing.

Main Methods:

Developed a decentralized routing algorithm utilizing an estimation function based on cumulative arrival probability distributions.
The estimation function quantifies node proximity to facilitate routing decisions.
Tested the algorithm and a novel discrimination criterion on both synthetic and real-world network data.

Main Results:

The decentralized algorithm successfully provides en route guidance in networks with stochastic edge weights.
The algorithm operates effectively without relying on global network knowledge.
The developed criterion allows for effective discrimination among different arrival probability distributions.

Conclusions:

Decentralized routing algorithms can effectively manage spatial networks with stochastic edge weights.
The proposed estimation function enables proximity-based routing, overcoming the need for global network information.
This approach offers a viable solution for navigation in complex, dynamic environments.