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Small-world network concept deals with the addition of a few Long-ranged Links (LLs) to significantly bring down the average path length (APL) of the network. The existing small-world models do not consider the real constraints of wireless networks such as the transmission range of LLs, limited radios per mesh router, and limited bandwidth for wireless links, therefore, we propose C-SWAWN (Constrained...
In this paper, we investigate the machine learning based strategies for dynamic channel selection in Cognitive Access Points (CogAPs) of WLANs. We employ Multi-layer Feedforward Neural Network (MFNN) models that utilize historical traffic information from network environment for learning the influence of spatio-temporal-spectral factors on the network and then predicting future traffic loads on each...
We propose a novel power saving strategy called Sleep during Neighbor-Addressed Frame (SNAF) for improving energy efficiency of IEEE 802.11 based wireless networks. IEEE 802.11 (Wi-Fi) radios that employ SNAF mode can turn OFF their wireless transceivers (i.e., put radios in sleep mode) within specific periods of neighbor-addressed frames while they are being received. The sleep duration of transceivers...
Tactical communication networking faces diverse operational scenarios where network optimization is a very challenging task. Learning from the network environment, in order to optimally adapt the network settings, is an essential requirement for providing efficient communication services in such environments. Cognitive networking deals with the application of cognition to the entire protocol stack...
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