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In the proposed scheme a novel, multi-dimensional, unsupervised clustering method is used to properly initialize neural network architectures, focusing on resource allocating networks (RAN); both the hidden and output layer parameters are determined by the output of the clustering process, without the need for any user interference.
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There are two organizations responsible for allocating network resources.
It is considered to be included in 5G standards to alleviate the problem of allocating network resources to the ever increasing number of users and devices.
Despite the common use of PSNR to rate video quality, allocating network resources subject to a long term rate constraint does not reflect the group of pictures structure of the video decoder, and thus may not maximize video quality.
By taking advantage of this model, we design a novel Load-Aware Route Selection algorithm, named LARS, which improves the network capacity by allocating network paths to upstream Internet flows so as to ensure a more balanced utilization of wireless network resources and gateways' Internet connections.
We propose the introduction of auction mechanisms to allocate network services in the short run.
One of the major concerns is how to allocate network resources efficiently to diverse traffic classes with heterogeneous QoS constraints.
The goal of traffic management is to efficiently allocate network resources via adjustment of source transmission rates and routes selection.
A static scheduling method, periodic communication sequence (PCS), is applied to allocate network resource and schedule the access to the network.
Optimization Theory can provide the necessary tools to develop such mechanisms that will allocate network resources optimally and fairly among users.
Hence, efficient scheduling at the medium access control (MAC) protocol level is needed to properly allocate network resources, especially when coping with bursty multimedia users.
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CEO of Professional Science Editing for Scientists @ prosciediting.com