Jie Chen, a researcher at Imperial College London, has developed a hybrid quantum algorithm to improve large scale network routing. The algorithm, which focuses on wireless sensor networks, aims to increase transmission speed and reduce energy consumption. Chen’s design clusters sensor nodes into small-scale networks, each with a maximum of six nodes, and selects a routing path with minimal energy consumption for each source node. The algorithm can be applied to networks of unmanned drones or vehicles, helping to optimise power supply and break down large computational problems into smaller, manageable ones.
Hybrid Quantum Algorithm for Large-Scale Network Routing
Jie Chen, a researcher from the Department of Electrical and Electronic Engineering at Imperial College London, has been studying the use of a hybrid quantum algorithm for large scale network routing. The research focuses on wireless sensor networks, aiming to increase transmission speed while reducing energy consumption.
Quantum Processor in Sensor Network Design
Chen’s previous research demonstrated the benefits of using a quantum processor in small-scale sensor networks to ensure a given transmission rate with minimal energy consumption. The current work presents a design for large-scale sensor networks that use a quantum processor unit. The design clusters large numbers of sensor nodes into multiple small-scale networks, each with a maximum of six nodes. For each small-scale network, a routing path with minimal energy consumption is selected for each source node. The design has shown to outperform the Advanced Leach algorithm in terms of network lifetime.
Quantum Processor-Based Algorithm
The algorithm developed by Chen takes advantage of the current state of quantum processor units based on quantum annealing techniques. The algorithm is a combination of distributed computing on a macro scale and centralized computing on a micro scale. The process involves segmenting the topology using conventional clustering techniques in sensor networks and replacing classical solvers with a quantum processor unit in each cluster. The optimal routing for each cluster is then computed centrally. The algorithm guarantees a more extensive search for a more refined routing scheme per round, aiming to minimize overall energy consumption.
Application of the Algorithm
The algorithm can be applied to networks of unmanned drones or vehicles. When groups of these machines embark on a new journey, it is crucial to ensure they have enough resources, including power, human capital, and backup facilities, to complete the task successfully. The algorithm can help optimize power supply in the face of rapidly changing network dynamics. The algorithm can also be used to break down large computational problems into smaller ones, tackling each one individually and then integrating the sub-solutions to form an overall approach that takes advantage of quantum speedup.
Problem Formulation
The problem formulation involves a given number of sensor source nodes scattered around a monitor device. Half of the sensor nodes have an initial energy of 0.5 joule, while the other half have an initial energy of 1 joule. The transmission packet size is 4000 bits. The goal is to maximize the network’s lifetime in terms of the number of transmission rounds.
Hybrid Algorithm Procedure
The hybrid algorithm procedure involves preparing the network topology, selecting the cluster heads, and forming the cluster. The problem is then submitted to the Quantum Processing Unit (QPU). The steps are repeated until the overall energy in the network has been drained.
Experiment Configurations
Chen’s experiments were mostly submitted to a local Cplex solver due to limited access to the Dwave machine. Previous research has shown that for a six-sized network, Cplex runs much slower than Dwave Advanced System with equal solution quality.
On the Effectiveness of Utilizing A Hybrid Quantum Algorithm on Large Scale Network Routing is an article authored by Jie Chen, published on January 24, 2024. The research focuses on the application of a hybrid quantum algorithm in large scale network routing. The detailed findings and methodologies can be accessed via the DOI link: https://doi.org/10.21203/rs.3.rs-3890502/v1.
Source: Jie Chen