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State-of-the-art methods for traffic signs detection based feature extraction have got a high recall rate, but the detection rates are not ideal for some mistakenly detected. In this work, this paper presents a method of traffic signs detection based on HOG and Boolean Convolutional Neural Networks (HOG-BCNN). A cascade classifier is trained based on HOG to detect the candidate regions of traffic...
Virtual machine (VM) migration is a key technique for network resource optimization in modern data center networks (DCNs). Previous work generally focuses on how to place the VMs efficiently in a static network topology by migrating the VMs with large traffic demands to close servers. When the VM demands change, however, a great cost will be paid on the VM migration. With the advance of software-defined...
Energy consumption of data center has become an important challenge due to high electric cost and carbon dioxide emissions. Previous work has mainly focused on saving energy cost of servers, though the energy consumption of data center networks (DCNs), consisting of networking equipments like switches, also takes a significant part of the overall energy consumption. In this paper, we propose ProCons,...
Imbalanced load distribution among multiple APs (access points) has become a serious problem in enterprise WLANs. Load imbalance causes inefficiency of network usage and unreasonable resource allocation. We find that users tend to come and leave together, which can lead to fluctuation of network load. We propose a novel online AP allocation scheme (ASC) to keep load balanced when users come and leave...
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