103 results about "Time-varying network" patented technology

The invention generally relates to the field of markup languages used to describe adaptive mobile multimedia applications and/or presentations being inherently dependent on the dynamic mobile environment they are running in, which means that these mobile multimedia applications and/or presentations need to be adapted to the preferences of mobile users, the capabilities of their mobile computing devices, and their current situation. It allows adaptive mobile stream-based multimedia applications with real-time requirements in a typical wireless scenario (e.g. a radio link with a changing transmission quality and hand-over procedures) to adaptively and responsively react to a time-varying network topology and different radio link characteristics. Thereby, the underlying invention especially includes research and development issues in the field of describing adaptation possibilities (1500), adaptation constraints (802) and adaptation events (3802) directed to a personalization and context-aware adaptation of document-based multimedia applications by providing methods for pre-allocating, reserving, monitoring and adapting QoS-related parameters in a dynamic mobile environment using an XML-based multimedia presentation language.

In this connection, a document model (100) consisting of vocabulary, document structure and linking means (1600) between the document model elements is presented which supports the description (700) of adaptive mobile multimedia applications and/or presentations. Besides, a document object model supporting a simplified transaction-oriented access is proposed.

A system and method for using mobile network devices that are periodically connected to a network server are disclosed. The devices exchange data in an ad hoc manner when not connected to the server. In the preferred embodiment, independent mobile wireless network devices are connected to a network server through a client computing device acting as a gateway to the server. The presence of the mobile network device and the client computing device cause both devices to become users. The server pairs both the network device and the client computing device with a unique identity contained on the network device. Paired and independent identities that have presence on the server then interact with each other in such a manner that data on the connected mobile network devices is changed and stored in concordance with this community interaction. Unconnected mobile network devices search for other unconnected mobile network devices within range to form an ad hoc network. This allows the mobile network devices to exchange and store data related to their last community server interaction. This data is context specific in terms of the specific services used by the by the users that had presence on the community server. User interaction directly with mobile network devices can change this information locally even when not connected to a client computer. This information will also be exchanged and affect data stored on mobile devices that are part of an independent ad hoc network according to the context of the previous server data stored on the mobile devices.

Methods and apparatus for optimum file transfers in a time-varying network environment. A method is provided for transmitting content in a data network. The method includes transmitting content at a selected transmission rate, and receiving one or more acknowledgement signals. The method also includes estimating a network delivery rate from the one or more acknowledgment signals, and adjusting the selected transmission rate of the content based on the network delivery rate.

A method and apparatus is disclosed herein for delivering information over time-varying networks. In one embodiment, the method comprises, for each of a plurality of time intervals, determining a virtual network topology for use over each time interval; selecting for the time interval based on the virtual network topology, a fixed network code for use during the time interval; and coding information to be transmitted over the time-varying network topology using the fixed network code with necessary virtual buffering at each node.

Certain aspects of a method and system for dynamically adjusting forward error correction (FEC) rate to adapt for time varying network impairments in video streaming applications over IP networks may be disclosed. At a server side of a client-server communication system, a rate of transmission of forward error correction (FEC) packets to one or more clients may be dynamically adjusted based on receiving at least one upstream FEC packet from a plurality of clients. The rate of transmission of the FEC packets to the plurality of clients may be increased when a rate of occurrence of lost data packets is above a particular threshold value. The upstream FEC packets may comprise an urgent packet requesting transmission of a particular FEC packet in order to recover one or more particular lost data packets.

A system and method for automatically analyzing data streams in a hierarchical and temporal network to identify node positions and the network topology in order to generate a hierarchical model of the temporal or spatial data. The system and method receives data streams, identifies a correlation between the data streams, partitions/clusters the data streams based upon the identified correlation and forms a current level of a hierarchical temporal network by having each cluster of data streams be an input to a hierarchical temporal network node. After training the nodes, each of the nodes creates a new data stream and these data streams are correlated and partitioned/clustered and are input into a node at a next level. The process can repeat until a desired portion of the network topology is determined.

A method and apparatus is disclosed herein for information delivery with network coding over time-varying network topologies. In one embodiment, the method comprises decomposing a sequence of topology graphs that model a time-varying network topology into a plurality of virtual graphs, where each virtual graph of the plurality of virtual graphs corresponds to a distinct traffic class, and the virtual topology graph representing a partial topology of a time-varying network. The method also includes selecting a network code for each virtual graph in the plurality of the virtual graphs to meet requirements of the distinct traffic class corresponding to said each topology graph, where the network code is used to encode packets of the associated traffic class, and processing packets of each traffic class using the network code determined by its corresponding virtual topology and the requirements of said each traffic class, including using a virtual buffer system to implement the network code corresponding to each traffic class over the physical network topology. The method also includes using a scheduler to determine the transmission schedules for each output packet from the virtual buffer system of each traffic class where the scheduling decisions are based, at least in part, on the QoS requirements of each class.

The invention provides a time diffusion route search method of a satellite DTN (Delay/Disrupt-Tolerant Networking) network, wherein the method is used for solving a route selection problem of an intermittent relay satellite network, and is obtained by CGR (Contact Graph Routing) principle improvement. An ERSA algorithm described in the invention calculates all information of a time-varying network, and the paths searched by the ERSA algorithm comprise a directly connected end-to-end path and a path for storage waiting for communication through a discontinuous link, and quantitative analysis is performed on the paths. Two new path measuring standards consider the transmission performance of the link, so as to guarantee the successful delivery rate and the shortest reach time of data. The increment of available paths improves the utilization rate of the algorithm for the system throughput performance. The time diffusion route search method of the satellite DTN network provided by the invention obtains a more efficient routing design and transmission quality by utilizing the overall inspection information of the network and the real-time network condition; therefore, compared with the traditional method, the method has certain advantages both in objective elevation index and subjective visual effect.

The invention discloses an obstacle avoidance method and system of a UAV (unmanned aerial vehicle) formation under time-varying network topology. The method comprises a step of obtaining a current UAV network topology condition according to position information of each UAV at present, a step of obtaining current UAV global formation information by using a distributed transmission mode according to the current UAV network topology condition, a step of carrying out centralized transmission according to regional information obtained by a sensor of a boundary UAV to calculate a global barrier-free area, a step of carrying out optimal calculation to obtain a target formation according to the current UAV global formation information and the barrier-free area, and a step of distributing a UAV to each target point according to the calculated target formation. According to the method and the system, the overall communication overhead and time cost are reduced, at the same time, a topology change caused by a formation change in the formation process is considered, a slice type topological model is established, different topologies are updated according to a current formation state in different time slots, and thus an algorithm is more close to the actual application. The integrity of the formation is ensured.

The invention provides a networking time-delay compensation and control method using the active-disturbance-rejection control technology for a permanent magnet synchronous motor. The method comprises the following steps: 1) building a permanent magnet synchronous motor control system model containing time-varying network-induced delay, and describing a permanent magnet synchronous motor control system as a discrete-time linear time-varying system with one-step input delay, so as to describe an undetermined dynamic part of the system caused by the time-varying delay as the additive noise of the system; 2) designing an expanding state observing device, and estimating the undetermined dynamic part caused by the time-varying delay as part of total disturbance through the expanding state observer; 3) compensating the undetermined dynamic state caused by the time-varying delay in the networking permanent magnet synchronous motor control system, wherein all undetermined dynamic parts caused by the time-varying delay and the internal and external disturbances in the system can be counteracted during compensating. The method shows high capability on inhibiting the nondeterminacy caused by time-varying delay, the internal and external disturbances of the system, and the nondeterminacy of a model.

The utility model relates to a customized bus route optimization method for reliability shortest path, which comprises the following steps of establishing a road network, comprising establishing a spatio-temporal network and a reliability network; determining the passenger relaxation time window; determining the scope of service; calculating whether a passenger can be serviced by the opened vehicle k; finding the shortest path of reliability; opening the customized new bus routes. The invention discloses a custommized bus line optimization method for reliability shortest path, which can efficiently and quickly deliver passengers to a destination under the condition of satisfying passenger travel. Due to the delays caused by traffic congestion during the morning and evening rush hours of customized buses, the invention creatively proposes a method for searching the shortest path of reliability, which avoids the delay caused by driving, improves the stability and reliability of vehicle operation, meets the requirement of high punctuality of customized bus service by commuters during morning and evening rush hours, and finally improves the share rate of customized bus service.

The present invention provides an adaptive FEC (Forward Error Correction) mechanism based on the media content. The mechanism classifies the media content and gives different significances, and the mechanism dynamically regulate the degrees of importance of frames included in the media data and the corresponding encoding schemes according to the current channel state in the condition without performing shunt of the current media data stream and transmits a data packet to a corresponding FEC encoder to perform protection with different degrees and finally encode one source data flow to an FEC code stream. The adaptive FEC mechanism based on the media content reduces the great data bulk caused by the FEC while ensuring the quality of the media content to the utmost extent; the adaptive FEC mechanism based on the media content does not need the shunt of the source data stream to reduce the complexity of the FEC encoding of a sending terminal and improve the efficiency of the FEC encoding; one source data stream only can encode and generate one FEC code stream so as to greatly reduce the increasing of the data bulk caused by the FEC encoding; and the adaptive FEC mechanism based on the media content can dynamically regulate the encoding scheme according to the changing of the current network state so as to has higher adaptability for the time varying network.

The invention provides an urban area tail gas pollution prediction method based on a depth space-time correction model, which comprises the following steps: acquiring multi-source heterogeneous data;a self-encoder feature extraction method realizes feature dimension reduction extraction of the multi-source heterogeneous data by constructing a three-layer self-encoder network structure; tail gas emission correction, substituting dimension reduction characteristic data of each data source extracted in the step 2 into the tail gas emission correction model; Spatio-temporal series data generation; deep spatio-temporal network model pre-training; replacing the corrected model data with the telemetry data of the real monitoring points, and re-training the corrected regional tail gas emission prediction model; the weighted parameters of the model are determined to obtain a depth spatio-temporal network model, and the multi-source heterogeneous data are input to obtain a predicted regional tail gas pollution emission result.

The invention provides a method for predicting the tail gas pollution distribution in a city road network. The method comprises the following steps: acquiring multi-source heterogeneous data; carryingout stack-type self-encode features dimension reduction, and constructing a multi-layer sparse self-encoder network structure to extract the features of the multi-source heterogeneous data; generating sequential data based on spatio-temporal semi-supervised learning; pre-training a deep spatio-temporal network model replacing the corrected model data with the telemetry data of the real monitoringpoints, and re-training the corrected regional tail gas emission prediction model; determining the weighted parameters of the model to obtain a deep spatio-temporal network model, and inputting the multi-source heterogeneous data t to obtain a predicted regional tail gas pollution emission result. The invention is based on a stack-type self-encoder dimension reduction feature extraction method, which can learn essential feature mapping between road network information, meteorological information, traffic flow information, POIs information and regional tail gas emission, and can realize higherprecision regional tail gas prediction on real telemetry data.

The invention relates to a method of a DC motor networked tracking controller. The method comprises the steps of (1) establishing a DC motor discrete system state equation with the consideration of atime-varying network induced delay, describing the DC motor system as a discrete-time norm bounded uncertain system with a one-time input delay, and using an uncertain system method to process an exponential time-varying problem in a motor state equation, (2) establishing a closed-loop system model of a DC motor networked tracking control system containing uncertainties, wherein the closed-loop system is an uncertain augmented closed-loop system with the one-step input delay, and (3) designing the DC motor networked tracking controller including the steps of firstly carrying out H-infinity performance analysis on the closed-loop system to verify stability and then designing the networked tracking controller, wherein the time delay is divided into a mean part and an uncertainty part in modeling, a networked control system is described as a class of discrete-time norm bounded uncertain system, and a networked H-infinity tracking control strategy is used to design a state feedback controller.

The invention discloses a radar moving target multi-frame joint detection method based on a graph space-time network. The method mainly solves the problem that in the prior art, the false alarm rate of moving target detection of a single-channel system is high. According to the scheme, the method comprises the steps of obtaining a sub-aperture distance Doppler spectrum; constructing a sub-residualnetwork and a sub-graph space-time network, and forming a neural network model for moving target detection by using the sub-residual network and the sub-graph space-time network; performing regionaltarget detection by using the sub residual network, outputting a preliminary detection probability graph, and calculating cross entropy loss; performing spatial-temporal feature extraction and fusionby using a sub-graph spatial-temporal network, outputting a final detection probability graph of an intermediate frame moving target, and calculating a mean square error; and taking the sum of the cross entropy loss and the mean square error as a total cost function, training the neural network until the total cost function is converged to obtain a trained neural network, inputting test data intothe trained neural network, judging an output threshold value of the trained neural network, and suppressing a non-maximum value to obtain a moving target detection result of an intermediate frame. According to the invention, the false alarm rate is reduced, and reliable moving target detection can be realized.

The invention belongs to the technical field of complex network analysis, and particularly relates to a method and a device for detecting aging stability communities in a time-varying network. The method provided by the invention comprises the following steps: acquiring the change condition of connection between nodes along with time, and constructing a time-varying network; Using the volatility to quantitatively describe the dynamic change degree of the connection edge in the network; Initializing a community structure, and calculating the dynamic modularity of the time-varying network in combination with the fluctuation rate; And optimizing the dynamic modularity, wherein the community structure corresponding to the maximum value is the time-varying stable community of the time-varying network. According to the invention, the network dynamic change is quantitatively described by using the volatility; the network dynamic change characteristics are combined with a community detection method; The method for identifying the stable community in the time-varying network is provided, the accuracy and reliability of community detection are improved, the method has wide application prospects in different fields of social networks, biological networks, traffic networks and the like, and meanwhile a new visual angle is provided for understanding the functions and the dynamic process ofthe community structure in a complex system in actual life.

The present invention provides an installation method and relative devices of a business packet. The method comprises that: a server, according to a dynamic host configuration protocol (DHCP) request of a node, acquires a media access control (MAC) address of the node and a temporal network Internet protocol (IP) assainged for the node; the server queries the switchboard name and a port number which are corresponding to the MAC address; the server, according to the switchboard name and the port number, acquires a fixed IP address and a gateway which are needed to be assigned to the node; the server, on the basis of the temporal IP address, builds a connection with the node, sets the fixed IP address and the gateway to the node, and installs the business packet on the node.

The invention discloses an incremental steady-state layout method for time-varying network data. The incremental steady-state layout method comprises the following steps: loading network structure data; preprocessing the data; generating an initial static graph by adopting a multi-level method; initializing node positions for newly added nodes; adjusting the length of the edge for the newly-addededge; calculating the level attribute of the node; partitioning the nodes, calculating the repulsive force in the form of pseudo nodes, and simplifying the layout updating process of the force guidingalgorithm. According to the invention, a stable layout method for time-varying network data is designed as a starting point; a force guide graph is used as a basic visual presentation mode; network structure characteristics such as'node level 'are introduced, it is guaranteed that focus of interest of a user does not change suddenly in the large-range change process of the network topology structure, the stability and continuity of the cognitive process of the user are kept, the user is helped to understand the topology structure of a complex network more effectively, and the understanding difficulty of the time-varying network topology structure is reduced.

The invention discloses a time varying network link packet loss probability estimation method based on a Kalman filter. The time varying network link packet loss probability estimation method based on the Kalman filter mainly comprises a training phase and an estimation phase. In the training phase, a source node sends back-to-back detection packets to multiple destination nodes so as to obtain path data, then, prior information of time varying link packet loss probability is estimated according to the path data, and a state transition equation of the Kalman filter is established. In the estimation phase, under the condition that the detection packets do not need to be sent, recursive computation and estimation of the time varying link packet loss probability are completed through a feedback control method according to the state transition equation and the path data obtained from network background flow. Due to the fact that a Kalman filter module is introduced to estimate the link packet loss probability of a time varying network, an obtained link packet loss probability estimated result has a minimum mean square error as well as high estimated accuracy, and the time-variation characteristic of the time varying network link packet loss probability can be reflected in real time.