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Non-dominated quantum iterative routing optimization for wireless multihop networks

Non-dominated quantum iterative routing optimization for wireless multihop networks
Non-dominated quantum iterative routing optimization for wireless multihop networks
Routing in Wireless Multihop Networks (WMHNs) relies on a delicate balance of diverse and often conflicting parameters, when aiming for maximizing the WMHN performance. Classified as a Non-deterministic Polynomial-time hard problem (NP-hard), routing in WMHNs requires sophisticated methods. As a benefit of observing numerous variables in parallel, quantum computing offers a promising range of algorithms for complexity reduction by exploiting the principle of Quantum Parallelism (QP), while achieving the optimum full-search-based performance. In fact, the so-called Non-Dominated Quantum Optimization (NDQO) algorithm has been proposed for addressing the multi-objective routing problem with the goal of achieving a near-optimal performance, while imposing a complexity of the order of $O(N)$ and $O(N\sqrt{N})$ in the best- and worst-case scenarios, respectively. However, as the number of nodes in the WMHN increases, the total number of routes increases exponentially, making its employment infeasible despite the complexity reduction offered. Therefore, we propose a novel optimal quantum-assisted algorithm, namely the Non-Dominated Quantum Iterative Optimization (NDQIO) algorithm, which exploits the synergy between the hardware and the quantum parallelism for the sake of achieving a further complexity reduction, which is on the order of $O(\sqrt{N})$ and $O(N\sqrt{N})$ in the best- and worst-case scenarios, respectively. Additionally, we provide simulation results for demonstrating that our NDQIO algorithm achieves an average complexity reduction of almost an order of magnitude compared to the near-optimal NDQO algorithm, while having the same order of power consumption
1-25
Alanis, Dimitrios
39e04fad-7530-44f2-b7d3-1b20722a0bd2
Botsinis, Panagiotis
d7927fb0-95ca-4969-9f8c-1c0455524a1f
Babar, Zunaira
23ede793-1796-449d-b5aa-93a297e5677a
Ng, Soon
e19a63b0-0f12-4591-ab5f-554820d5f78c
Hanzo, Lajos
66e7266f-3066-4fc0-8391-e000acce71a1
Alanis, Dimitrios
39e04fad-7530-44f2-b7d3-1b20722a0bd2
Botsinis, Panagiotis
d7927fb0-95ca-4969-9f8c-1c0455524a1f
Babar, Zunaira
23ede793-1796-449d-b5aa-93a297e5677a
Ng, Soon
e19a63b0-0f12-4591-ab5f-554820d5f78c
Hanzo, Lajos
66e7266f-3066-4fc0-8391-e000acce71a1

Alanis, Dimitrios, Botsinis, Panagiotis, Babar, Zunaira, Ng, Soon and Hanzo, Lajos (2015) Non-dominated quantum iterative routing optimization for wireless multihop networks. IEEE Access, 3, 1-25. (doi:10.1109/ACCESS.2015.2478793).

Record type: Article

Abstract

Routing in Wireless Multihop Networks (WMHNs) relies on a delicate balance of diverse and often conflicting parameters, when aiming for maximizing the WMHN performance. Classified as a Non-deterministic Polynomial-time hard problem (NP-hard), routing in WMHNs requires sophisticated methods. As a benefit of observing numerous variables in parallel, quantum computing offers a promising range of algorithms for complexity reduction by exploiting the principle of Quantum Parallelism (QP), while achieving the optimum full-search-based performance. In fact, the so-called Non-Dominated Quantum Optimization (NDQO) algorithm has been proposed for addressing the multi-objective routing problem with the goal of achieving a near-optimal performance, while imposing a complexity of the order of $O(N)$ and $O(N\sqrt{N})$ in the best- and worst-case scenarios, respectively. However, as the number of nodes in the WMHN increases, the total number of routes increases exponentially, making its employment infeasible despite the complexity reduction offered. Therefore, we propose a novel optimal quantum-assisted algorithm, namely the Non-Dominated Quantum Iterative Optimization (NDQIO) algorithm, which exploits the synergy between the hardware and the quantum parallelism for the sake of achieving a further complexity reduction, which is on the order of $O(\sqrt{N})$ and $O(N\sqrt{N})$ in the best- and worst-case scenarios, respectively. Additionally, we provide simulation results for demonstrating that our NDQIO algorithm achieves an average complexity reduction of almost an order of magnitude compared to the near-optimal NDQO algorithm, while having the same order of power consumption

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Submitted date: 11 August 2015
Accepted/In Press date: 29 August 2015
e-pub ahead of print date: 15 September 2015
Organisations: Southampton Wireless Group

Identifiers

Local EPrints ID: 381682
URI: https://eprints.soton.ac.uk/id/eprint/381682
PURE UUID: 1ded2558-d411-4728-bb2e-061c7b26fcd9
ORCID for Zunaira Babar: ORCID iD orcid.org/0000-0002-7498-4474
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: 15 Oct 2015 08:40
Last modified: 20 Jul 2019 01:26

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