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42results about How to "Optimize network resources" patented technology

Methods And Systems For Providing Quality Of Service In Packet-Based Core Transport Networks

Methods and systems for providing necessary and sufficient quality-of-service (QoS), in a packet-based core transport network that utilizes dynamic setting of bandwidth management pipes or thresholds to obviate link congestion are disclosed. Congestion avoidance is a necessary and sufficient requirement in order to guarantee Quality of Service (QoS) in packet-based core networks.
A typical network is composed of a plurality of backbone links connecting edge nodes where backhaul links are aggregated. The backhaul links connect the backbone links to the remote sites serving the subscribers. In order to enforce bandwidth management policies, Access Controllers, which perform traffic shaping, are situated on each remote site.
In the event of a violation of certain link threshold settings, dynamic adjustment of the bandwidth management policies on affected Access Controllers is enforced. Various algorithms in determining the correlation between the link nearing congestion and the source or destination of traffic streams are also discussed. This invention implements a feedback control loop wherein probes at various points in the network checks for congestion states to guide bandwidth management threshold decisions in order to maintain the condition of non-congestion throughout the network. Capacity planning and congestion avoidance mechanisms work hand-in-hand to fulfill Service Level Agreements (SLA).
Owner:LATITUDE BROADBAND

Resource management method suitable for multilayer satellite system

The invention relates to a resource management method suitable for a multilayer satellite system. The resource management method adopts the following design principle that high altitude satellites are used as reserved resources and are specially used for distributing resources for users with high priorities and high QOS (Quality of Service) requirements and distributing the resources for the user as required in a real-time manner; and meanwhile, low earth orbit satellites are combined and are used as ground network supplements, the characteristics of high-speed motion and the like of the low earth orbit satellites are considered and a method for dynamically distributing the resources for users with low priorities by using efficiency, cost and user publicity as evaluation indexes is designed. According to the design, the characteristics of the high altitude satellites and the low earth orbit satellites are combined; the priorities of the users are considered; the resources are distributed for the users with high priorities as required; a multi-target evaluation function is designed for the users with low priorities; and the multi-target evaluation function is nondimensionalized, so that in the resource management process, the evaluation indexes of other targets are not ignored due to an excessive function value of a certain index, and thus, a multi-target optimization method which has the advantages of short time delay, high bandwidth utilization rate and balanced resource distribution is integrally implemented.
Owner:NANJING UNIV OF POSTS & TELECOMM

Disease and pest identification system and method based on machine vision and convolutional neural network

The invention relates to a pest identification system and a method based on machine vision and a convolutional neural network, and belongs to the technical field of artificial intelligence. The systemmainly comprises an image acquisition module, a model training module, a model test module, a visual identification module, an information classification detection module and a training updating module. The method mainly comprises an image acquisition step, a model training step, a model test step, a visual identification step, an information classification detection step and a training updatingstep. According to the disease and pest identification system and the method based on machine vision and the convolutional neural network, a large amount of image data can be obtained at fixed pointsand fixed time; visual identification and convolutional neural network model testing are placed at an acquisition front end, invalid image bandwidth occupation is reduced, network resources are optimized, identification efficiency is improved, a feedback and updating mechanism enables the model to be continuously optimized in a gradient mode, a front end model is synchronized in real time, and disease and pest identification accuracy is effectively improved.
Owner:陈峰
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