Research output: Contribution to Journal/Magazine › Journal article › peer-review
Research output: Contribution to Journal/Magazine › Journal article › peer-review
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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 -