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Game-Theoretic Paradigm for Resource Management in Spectrum Agile Wireless Networks

Fangwen Fu, Ahmad Fattahi, Mihaela Der Schaar
2006 2006 IEEE International Conference on Multimedia and Expo  
We propose a new way of architecting the wireless multimedia communications systems by jointly optimizing the protocol stack at each station and the resource exchanges among stations.  ...  We show through simulations that the proposed game-theoretic resource management outperforms alternative techniques such as air-fair time and equal time resource allocation in terms of the total system  ...  Let i i i i i [PHY MAC APP ] l m n t o t = a be a vector of crosslayer adaptation strategies that can be deployed by WSTA i , where tot PHY MAC APP i i i i = × × denotes the joint set of all possible strategies  ... 
doi:10.1109/icme.2006.262640 dblp:conf/icmcs/FuFS06 fatcat:4qhxsipeznh3vocltzbscat4wq


Rohan Thakkar .
2014 International Journal of Research in Engineering and Technology  
Depending on their applications, the solutions have focused mainly on the following three network layers: Media Access Control layer (MAC), Application layer (APP) and Physical layer (PHY).  ...  For the sake of adaptive QoS, the cross-layer architecture assumes that layer information could be exchanged between application layer and lower layers.  ...  ACKNOWLEDGEMENTS We would like to thank K.J.Somaiya College of Engineering for giving all of us students a great opportunity to work on creating a report and giving a seminar on topics of such great importance  ... 
doi:10.15623/ijret.2014.0307060 fatcat:qwa23quyorfy3pxf6lzjpu6neq

Cross-layer wireless multimedia transmission: challenges, principles, and new paradigms

M. Van Der Schaar, S. Shankar N
2005 IEEE wireless communications  
Q (i.e., find the optimal cross-layer strategy) Figure 4 illustrates the results obtained using the joint PHY-MAC-APP optimization for a video streaming application that can tolerate 1 s delay.  ...  This number further varies depending on the deployed retry limit at the MAC that results in different PLRs.  ... 
doi:10.1109/mwc.2005.1497858 fatcat:xv5ym4ezq5eelkunmv25xhrfxm


Kalyani Kulkarni, Bharat S. Chaudhari
2015 ICTACT Journal on Communication Technology  
The edge PSNR of reconstructed video obtained as 32.6dB resulting to optimum decoding of the video at the receiver. The study also shows upbeat factor can be used to enhanced capacity of the network.  ...  Utility function based on bargaining model is proposed.  ...  These solutions include joint PHY-MAC, APP-PHY, MAC-APP layer optimizations for robust video over wireless transmission.  ... 
doi:10.21917/ijct.2015.0171 fatcat:jbovt4n5svbytismfurhart3jy

Energy Efficient and QoS Aware Framework for Video Transmission over Wireless Sensor Networks

Mohammed Ezz El Dien, Aliaa A. A. Youssif, Atef Zaki Ghalwash
2016 Wireless Sensor Network  
It adapts the application layer parameter of video encoder to current wireless channel state, and drops less important packets in case of network congestion according to packet type.  ...  Simulation results show that the new scheme EQWSN transmits video quality with QoS guarantees in addition to prolonging network lifetime.  ...  It is a position oriented resource allocation scheme across PHY, MAC, APP layers for image transmission over WMSN.  ... 
doi:10.4236/wsn.2016.83003 fatcat:a5k4cf2lw5az3onwqyfmd2nc7a

A New MAC Approach in Wireless Body Sensor Networks for Health Care [chapter]

Begonya Otal, Luis Alonso, Christos Verikoukis
2011 Emerging Communications for Wireless Sensor Networks  
Hence, the right MAC approach is able to handle cross-layer PHY-MAC-APP features.  ...  Its main goal is to optimize MAC layer performance in terms of QoS and energy consumption by applying fuzzy-logic decision techniques into the DQBAN logic system model (see Fig. 5 ).  ...  Wireless sensor networks are deployed in a rapidly increasing number of arenas, with uses ranging from healthcare monitoring to industrial and environmental safety, as well as new ubiquitous computing  ... 
doi:10.5772/10513 fatcat:u6lrhhkgorghxaym3fpltin7ne