TY - GEN
T1 - Client-based QoS data selection and modeling using generalized extreme value theorem and linear opinion pool
AU - Kamel, Ammar
AU - Al-Fuqaha, Ala
AU - Benhaddou, Driss
PY - 2012
Y1 - 2012
N2 - Assuring Quality-of-Service (QoS) guarantees to mobile clients is still a long-standing problem in today's wireless mobile networks. In this paper, we propose new algorithms that validate the accuracy of service measurements collected from the mobile clients to construct a precise QoS model. The proposed algorithms utilize the Linear Opinion Pool (LOP) approach in conjunction with Generalize Extreme Value theorem (GEV) to converge to a precise QoS model. The main objective of this work is to construct a QoS model that excludes the out-of-profile data that is collected from the Mobile Clients (MCs). Therefore, any MC with unreliable data is considered as un-trusted. The proposed approach is effective in providing service providers with a better assessment tool to evaluate and improve their services. The results show the usefulness of our algorithms and their ability to recognize and exclude the data collected from un-trusted MCs; thus, creating a precise QoS model.
AB - Assuring Quality-of-Service (QoS) guarantees to mobile clients is still a long-standing problem in today's wireless mobile networks. In this paper, we propose new algorithms that validate the accuracy of service measurements collected from the mobile clients to construct a precise QoS model. The proposed algorithms utilize the Linear Opinion Pool (LOP) approach in conjunction with Generalize Extreme Value theorem (GEV) to converge to a precise QoS model. The main objective of this work is to construct a QoS model that excludes the out-of-profile data that is collected from the Mobile Clients (MCs). Therefore, any MC with unreliable data is considered as un-trusted. The proposed approach is effective in providing service providers with a better assessment tool to evaluate and improve their services. The results show the usefulness of our algorithms and their ability to recognize and exclude the data collected from un-trusted MCs; thus, creating a precise QoS model.
KW - Client-Based Quality of Service
KW - Extreme Values
KW - Generalized Extreme Value
KW - Linear Opinion Pool
UR - http://www.scopus.com/inward/record.url?scp=84872001118&partnerID=8YFLogxK
U2 - 10.1109/ICC.2012.6364959
DO - 10.1109/ICC.2012.6364959
M3 - Conference contribution
AN - SCOPUS:84872001118
SN - 9781457720529
T3 - IEEE International Conference on Communications
SP - 7045
EP - 7049
BT - 2012 IEEE International Conference on Communications, ICC 2012
T2 - 2012 IEEE International Conference on Communications, ICC 2012
Y2 - 10 June 2012 through 15 June 2012
ER -