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User adaptive QoS aware selection method for cooperative heterogeneous wireless systems: a dynamic contextual approach

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User adaptive QoS aware selection method for cooperative heterogeneous wireless systems: a dynamic contextual approach. / Pervaiz, Haris; Ni, Qiang; Zarakovitis, Charilaos C.
In: Future Generation Computer Systems, Vol. 39, 10.2014, p. 75-87.

Research output: Contribution to Journal/MagazineJournal articlepeer-review

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Pervaiz H, Ni Q, Zarakovitis CC. User adaptive QoS aware selection method for cooperative heterogeneous wireless systems: a dynamic contextual approach. Future Generation Computer Systems. 2014 Oct;39:75-87. Epub 2014 Mar 12. doi: 10.1016/j.future.2014.02.012

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Bibtex

@article{5c60fcf224f9454ca022b2bba7d3dd15,
title = "User adaptive QoS aware selection method for cooperative heterogeneous wireless systems: a dynamic contextual approach",
abstract = "This paper proposes an adaptive realistic mechanism for joint network and user selection in cooperative wireless network environments. We present a novel optimization utility to incorporate the quality-of-service (QoS) dynamics of the available networks along with heterogeneous attributes of each user. The joint network and user selection is modelled by an evolutionary game theoretical approach and replicator dynamics is solved to seek an optimal stable solution. Combining both self-control of users{\textquoteright} preferences and self-adjustment of networks{\textquoteright} parameters, our study innovates over related efforts. The simulation results demonstrate that the proposed inverse cumulative ranking scheme significantly improves the overall QoS performance and system benefits as compared to other solutions. Our results also show that by incorporating the proposed Region of Interest (RoI) scheme, the complexity of the evolutionary game with and without network re-configuration can be reduced by 23% and 58 % respectively.",
keywords = "Evolutionary game theory, Iterative method, Analytic Hierarchy Process (AHP), Heterogeneous networks , Cooperative wireless networks , QoS",
author = "Haris Pervaiz and Qiang Ni and Zarakovitis, {Charilaos C.}",
year = "2014",
month = oct,
doi = "10.1016/j.future.2014.02.012",
language = "English",
volume = "39",
pages = "75--87",
journal = "Future Generation Computer Systems",
issn = "0167-739X",
publisher = "Elsevier",

}

RIS

TY - JOUR

T1 - User adaptive QoS aware selection method for cooperative heterogeneous wireless systems

T2 - a dynamic contextual approach

AU - Pervaiz, Haris

AU - Ni, Qiang

AU - Zarakovitis, Charilaos C.

PY - 2014/10

Y1 - 2014/10

N2 - This paper proposes an adaptive realistic mechanism for joint network and user selection in cooperative wireless network environments. We present a novel optimization utility to incorporate the quality-of-service (QoS) dynamics of the available networks along with heterogeneous attributes of each user. The joint network and user selection is modelled by an evolutionary game theoretical approach and replicator dynamics is solved to seek an optimal stable solution. Combining both self-control of users’ preferences and self-adjustment of networks’ parameters, our study innovates over related efforts. The simulation results demonstrate that the proposed inverse cumulative ranking scheme significantly improves the overall QoS performance and system benefits as compared to other solutions. Our results also show that by incorporating the proposed Region of Interest (RoI) scheme, the complexity of the evolutionary game with and without network re-configuration can be reduced by 23% and 58 % respectively.

AB - This paper proposes an adaptive realistic mechanism for joint network and user selection in cooperative wireless network environments. We present a novel optimization utility to incorporate the quality-of-service (QoS) dynamics of the available networks along with heterogeneous attributes of each user. The joint network and user selection is modelled by an evolutionary game theoretical approach and replicator dynamics is solved to seek an optimal stable solution. Combining both self-control of users’ preferences and self-adjustment of networks’ parameters, our study innovates over related efforts. The simulation results demonstrate that the proposed inverse cumulative ranking scheme significantly improves the overall QoS performance and system benefits as compared to other solutions. Our results also show that by incorporating the proposed Region of Interest (RoI) scheme, the complexity of the evolutionary game with and without network re-configuration can be reduced by 23% and 58 % respectively.

KW - Evolutionary game theory

KW - Iterative method

KW - Analytic Hierarchy Process (AHP)

KW - Heterogeneous networks

KW - Cooperative wireless networks

KW - QoS

U2 - 10.1016/j.future.2014.02.012

DO - 10.1016/j.future.2014.02.012

M3 - Journal article

VL - 39

SP - 75

EP - 87

JO - Future Generation Computer Systems

JF - Future Generation Computer Systems

SN - 0167-739X

ER -