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Research Data: Quantum-Aided Multi-Objective Routing Optimization Using Back-Tracing-Aided Dynamic Programming

Research Data: Quantum-Aided Multi-Objective Routing Optimization Using Back-Tracing-Aided Dynamic Programming
Research Data: Quantum-Aided Multi-Objective Routing Optimization Using Back-Tracing-Aided Dynamic Programming
Datasets for plotting the performance figures of the paper:Alanis, D, Botsinis, P, Babar, Z, Nguyen, HV, Chandra, D, Ng, S & Hanzo, L (2018), 'Quantum-aided multi-objective routing optimization using back-tracing-aided dynamic programming' IEEE Transactions on Vehicular Technology. DOI: 10.1109/TVT.2018.2822626.Results may reproduced using GLE graphics.Abstract: Pareto optimality is capable of striking the optimal trade-off amongst the diverse conflicting QoS requirements of routing in wireless multihop networks. However, this comes at the cost of increased complexity owing to searching through the extended multi-objective search-space. We will demonstrate that the powerful quantum-assisted dynamic programming optimization framework is capable of circumventing this problem. In this context, the so-called Evolutionary Quantum Pareto Optimization~(EQPO) algorithm has been proposed, which is capable of identifying most of the optimal routes at a near-polynomial complexity versus the number of nodes. As a benefit, we improve both the the EQPO algorithm by introducing a back-tracing process. We also demonstrate that the improved algorithm, namely the Back-Tracing-Aided EQPO~(BTA-EQPO) algorithm, imposes a negligible complexity overhead, while substantially improving our performance metrics, namely the relative frequency of finding all Pareto-optimal solutions and the probability that the Pareto-optimal solutions are indeed part of the optimal Pareto front.
University of Southampton
Alanis, Dimitrios
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Botsinis, Panagiotis
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Babar, Zunaira
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Nguyen, Hung Viet
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Chandra, Daryus
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Ng, Soon
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Hanzo, Lajos
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Alanis, Dimitrios
8ae8ead6-3974-4886-8e17-1b4bff1d94e0
Botsinis, Panagiotis
d7927fb0-95ca-4969-9f8c-1c0455524a1f
Babar, Zunaira
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Nguyen, Hung Viet
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Chandra, Daryus
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Ng, Soon
e19a63b0-0f12-4591-ab5f-554820d5f78c
Hanzo, Lajos
66e7266f-3066-4fc0-8391-e000acce71a1

Alanis, Dimitrios, Botsinis, Panagiotis, Babar, Zunaira, Nguyen, Hung Viet, Chandra, Daryus, Ng, Soon and Hanzo, Lajos (2018) Research Data: Quantum-Aided Multi-Objective Routing Optimization Using Back-Tracing-Aided Dynamic Programming. University of Southampton doi:10.5258/SOTON/D0479 [Dataset]

Record type: Dataset

Abstract

Datasets for plotting the performance figures of the paper:Alanis, D, Botsinis, P, Babar, Z, Nguyen, HV, Chandra, D, Ng, S & Hanzo, L (2018), 'Quantum-aided multi-objective routing optimization using back-tracing-aided dynamic programming' IEEE Transactions on Vehicular Technology. DOI: 10.1109/TVT.2018.2822626.Results may reproduced using GLE graphics.Abstract: Pareto optimality is capable of striking the optimal trade-off amongst the diverse conflicting QoS requirements of routing in wireless multihop networks. However, this comes at the cost of increased complexity owing to searching through the extended multi-objective search-space. We will demonstrate that the powerful quantum-assisted dynamic programming optimization framework is capable of circumventing this problem. In this context, the so-called Evolutionary Quantum Pareto Optimization~(EQPO) algorithm has been proposed, which is capable of identifying most of the optimal routes at a near-polynomial complexity versus the number of nodes. As a benefit, we improve both the the EQPO algorithm by introducing a back-tracing process. We also demonstrate that the improved algorithm, namely the Back-Tracing-Aided EQPO~(BTA-EQPO) algorithm, imposes a negligible complexity overhead, while substantially improving our performance metrics, namely the relative frequency of finding all Pareto-optimal solutions and the probability that the Pareto-optimal solutions are indeed part of the optimal Pareto front.

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More information

Published date: 2018
Organisations: Electronics & Computer Science, Southampton Wireless Group

Identifiers

Local EPrints ID: 419191
URI: https://eprints.soton.ac.uk/id/eprint/419191
PURE UUID: 0d120ec2-6ca3-4a90-815c-dd29545fc119
ORCID for Dimitrios Alanis: ORCID iD orcid.org/0000-0002-6654-1702
ORCID for Zunaira Babar: ORCID iD orcid.org/0000-0002-7498-4474
ORCID for Hung Viet Nguyen: ORCID iD orcid.org/0000-0001-6349-1044
ORCID for Daryus Chandra: ORCID iD orcid.org/0000-0003-2406-7229
ORCID for Soon Ng: ORCID iD orcid.org/0000-0002-0930-7194
ORCID for Lajos Hanzo: ORCID iD orcid.org/0000-0002-2636-5214

Catalogue record

Date deposited: 06 Apr 2018 16:31
Last modified: 06 Jun 2018 13:15

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Contributors

Creator: Dimitrios Alanis ORCID iD
Creator: Panagiotis Botsinis
Creator: Zunaira Babar ORCID iD
Creator: Hung Viet Nguyen ORCID iD
Creator: Daryus Chandra ORCID iD
Creator: Soon Ng ORCID iD
Creator: Lajos Hanzo ORCID iD

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