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Quantum-assisted joint multi-objective routing and load balancing for socially-aware networks

Quantum-assisted joint multi-objective routing and load balancing for socially-aware networks
Quantum-assisted joint multi-objective routing and load balancing for socially-aware networks
The widespread use of mobile networking devices, such as smart phones and tablets, has substantially increased the number of nodes in the operational networks. These devices often suffer from the lack of power and bandwidth. Hence, we have to optimize their message routing for the sake of maximizing their capabilities. However, the optimal routing typically relies on a delicate balance of diverse and often conflicting objectives, such as the route's delay and power consumption. The network design also has to consider the nodes' user-centric social behavior. Hence, the employment of socially aware load balancing becomes imperative for avoiding the potential formation of bottlenecks in the network's packet-flow. In this paper, we propose a novel algorithm, referred to as the multi-objective decomposition quantum optimization (MODQO) algorithm, which exploits the quantum parallelism to its full potential by reducing the database correlations for performing multi-objective routing optimization, while at the same time balancing the teletraffic load among the nodes without imposing a substantial degradation on the network's delay and power consumption. Furthermore, we introduce a novel socially aware load balancing metric, namely, the normalized entropy of the normalized composite betweenness of the associated socially aware network, for striking a better tradeoff between the network's delay and power consumption. We analytically prove that the MODQO algorithm achieves the full-search based accuracy at a significantly reduced complexity, which is several orders of magnitude lower than that of the full search. Finally, we compare the MODQO algorithm to the classic non-dominated sort genetic algorithm II evolutionary algorithm and demonstrate that the MODQO succeeds in halving the network's average delay, while simultaneously reducing the network's average power consumption by 6 dB without increasing the computational complexity.
NSGA-II, DTNs, routing, load balancing, quantum computing, NDQIO, BBHT-QSA, DHA, Grover's QSA
9993 - 10028
Alanis, Dimitrios
8ae8ead6-3974-4886-8e17-1b4bff1d94e0
Hu, Jie
d9a3b90d-803a-4938-8518-87e964cc95db
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
8ae8ead6-3974-4886-8e17-1b4bff1d94e0
Hu, Jie
d9a3b90d-803a-4938-8518-87e964cc95db
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, Hu, Jie, Botsinis, Panagiotis, Babar, Zunaira, Ng, Soon and Hanzo, Lajos (2017) Quantum-assisted joint multi-objective routing and load balancing for socially-aware networks IEEE Access, 4, 9993 - 10028.

Record type: Article

Abstract

The widespread use of mobile networking devices, such as smart phones and tablets, has substantially increased the number of nodes in the operational networks. These devices often suffer from the lack of power and bandwidth. Hence, we have to optimize their message routing for the sake of maximizing their capabilities. However, the optimal routing typically relies on a delicate balance of diverse and often conflicting objectives, such as the route's delay and power consumption. The network design also has to consider the nodes' user-centric social behavior. Hence, the employment of socially aware load balancing becomes imperative for avoiding the potential formation of bottlenecks in the network's packet-flow. In this paper, we propose a novel algorithm, referred to as the multi-objective decomposition quantum optimization (MODQO) algorithm, which exploits the quantum parallelism to its full potential by reducing the database correlations for performing multi-objective routing optimization, while at the same time balancing the teletraffic load among the nodes without imposing a substantial degradation on the network's delay and power consumption. Furthermore, we introduce a novel socially aware load balancing metric, namely, the normalized entropy of the normalized composite betweenness of the associated socially aware network, for striking a better tradeoff between the network's delay and power consumption. We analytically prove that the MODQO algorithm achieves the full-search based accuracy at a significantly reduced complexity, which is several orders of magnitude lower than that of the full search. Finally, we compare the MODQO algorithm to the classic non-dominated sort genetic algorithm II evolutionary algorithm and demonstrate that the MODQO succeeds in halving the network's average delay, while simultaneously reducing the network's average power consumption by 6 dB without increasing the computational complexity.

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More information

Accepted/In Press date: 14 November 2016
e-pub ahead of print date: 16 November 2016
Published date: 27 January 2017
Keywords: NSGA-II, DTNs, routing, load balancing, quantum computing, NDQIO, BBHT-QSA, DHA, Grover's QSA
Organisations: Southampton Wireless Group

Identifiers

Local EPrints ID: 410593
URI: http://eprints.soton.ac.uk/id/eprint/410593
PURE UUID: 08df1ab0-063e-4366-af6e-2d480b0e51c4
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 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 Jun 2017 09:12
Last modified: 04 Oct 2017 05:01

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Contributors

Author: Dimitrios Alanis ORCID iD
Author: Jie Hu
Author: Panagiotis Botsinis
Author: Zunaira Babar ORCID iD
Author: Soon Ng ORCID iD
Author: Lajos Hanzo ORCID iD

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