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A quantum-search-aided dynamic programming framework for Pareto optimal routing in wireless multihop networks

A quantum-search-aided dynamic programming framework for Pareto optimal routing in wireless multihop networks
A quantum-search-aided dynamic programming framework for Pareto optimal routing in wireless multihop networks
Wireless Multihop Networks (WMHNs) have to strike a trade-off among diverse and often conflicting Quality-of-Service (QoS) requirements. The resultant solutions may be included by the Pareto Front under the concept of Pareto Optimality. However, the problem of finding all the Pareto-optimal routes in WMHNs is classified as NP-hard, since the number of legitimate routes increases exponentially, as the nodes proliferate. Quantum Computing offers an attractive framework of rendering the Pareto-optimal routing problem tractable. In this context, a pair of quantum-assisted algorithms have been proposed, namely the Non-Dominated Quantum Optimization (NDQO) and the Non-Dominated Quantum Iterative Optimization (NDQIO). However, their complexity is proportional to $\sqrt{N}$, where $N$ corresponds to the total number of legitimate routes, thus still failing to find the solutions in ``polynomial time''. As a remedy, we devise a dynamic programming framework and propose the so-called Evolutionary Quantum Pareto Optimization (EQPO) algorithm. We analytically characterize the complexity imposed by the EQPO algorithm and demonstrate that it succeeds in solving the Pareto-optimal routing problem in polynomial time. Finally, we demonstrate by simulations that the EQPO algorithm achieves a complexity reduction, which is at least an order of magnitude, when compared to its predecessors, albeit at the cost of a modest heuristic accuracy reduction.
0090-6778
1-16
Alanis, Dimitrios
8ae8ead6-3974-4886-8e17-1b4bff1d94e0
Botsinis, Panagiotis
d7927fb0-95ca-4969-9f8c-1c0455524a1f
Babar, Zunaira
23ede793-1796-449d-b5aa-93a297e5677a
Nguyen, Hung Viet
6f5a71ef-ea98-49e0-9be7-7f5bb9880f52
Chandra, Daryus
a2f091a8-9772-4633-8e3b-d3220b10a2ec
Ng, Soon
e19a63b0-0f12-4591-ab5f-554820d5f78c
Hanzo, Lajos
66e7266f-3066-4fc0-8391-e000acce71a1
Alanis, Dimitrios
8ae8ead6-3974-4886-8e17-1b4bff1d94e0
Botsinis, Panagiotis
d7927fb0-95ca-4969-9f8c-1c0455524a1f
Babar, Zunaira
23ede793-1796-449d-b5aa-93a297e5677a
Nguyen, Hung Viet
6f5a71ef-ea98-49e0-9be7-7f5bb9880f52
Chandra, Daryus
a2f091a8-9772-4633-8e3b-d3220b10a2ec
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) A quantum-search-aided dynamic programming framework for Pareto optimal routing in wireless multihop networks. IEEE Transactions on Communications, 1-16. (doi:10.1109/TCOMM.2018.2803068).

Record type: Article

Abstract

Wireless Multihop Networks (WMHNs) have to strike a trade-off among diverse and often conflicting Quality-of-Service (QoS) requirements. The resultant solutions may be included by the Pareto Front under the concept of Pareto Optimality. However, the problem of finding all the Pareto-optimal routes in WMHNs is classified as NP-hard, since the number of legitimate routes increases exponentially, as the nodes proliferate. Quantum Computing offers an attractive framework of rendering the Pareto-optimal routing problem tractable. In this context, a pair of quantum-assisted algorithms have been proposed, namely the Non-Dominated Quantum Optimization (NDQO) and the Non-Dominated Quantum Iterative Optimization (NDQIO). However, their complexity is proportional to $\sqrt{N}$, where $N$ corresponds to the total number of legitimate routes, thus still failing to find the solutions in ``polynomial time''. As a remedy, we devise a dynamic programming framework and propose the so-called Evolutionary Quantum Pareto Optimization (EQPO) algorithm. We analytically characterize the complexity imposed by the EQPO algorithm and demonstrate that it succeeds in solving the Pareto-optimal routing problem in polynomial time. Finally, we demonstrate by simulations that the EQPO algorithm achieves a complexity reduction, which is at least an order of magnitude, when compared to its predecessors, albeit at the cost of a modest heuristic accuracy reduction.

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Submitted date: 2017
e-pub ahead of print date: 6 February 2018
Additional Information: Under Review, submitted to IEEE Transactions on Communications

Identifiers

Local EPrints ID: 416758
URI: https://eprints.soton.ac.uk/id/eprint/416758
ISSN: 0090-6778
PURE UUID: 5701e941-1c85-4b44-8cbc-5edebf0d398c
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: 09 Jan 2018 17:30
Last modified: 29 Jun 2018 04:01

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Contributors

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

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