53 results about "Mobility model" patented technology

A method for enhancing operational efficiency of a remote vehicle using a diagnostic behavior. The method comprises inputting and analyzing data received from a plurality of sensors to determine the existence of deviations from normal operation of the remote vehicle, updating parameters in a reference mobility model based on deviations from normal operation, and revising strategies to achieve an operational goal of the remote vehicle to accommodate deviations from normal operation. An embedded simulation and training system for a remote vehicle. The system comprises a software architecture installed on the operator control unit and including software routines and drivers capable of carrying out mission simulations and training.

A method for determining location history of a mobile device is provided. A plurality of states corresponding to a plurality of reachable road segments associated with a road network is determined based on one or more initial estimated locations of the mobile device. Mobility model defining transition probabilities between the determined plurality of states is generated. Time series network data associated with the mobile device is received from a network data source. The time series network data is associated with a given period of time. The time series network data is processed using the generated mobility model to estimate an actual route most likely travelled by the mobile device during the given time period.

A device includes a processor configured to execute one or more instructions stored in a memory to receive an electrical vehicle (EV) location profile having information regarding movement of an EV between a first and a second charging location of an electrical network. The processor is also configured to apply an EV mobility model to the EV location profile to determine an optimized schedule for the EV to charge or discharge a storage cell of the EV at the first or second charging locations during a scheduling period. The EV mobility model comprises constraints that describe interactions of the EV with the electrical network.

Efficient routing techniques that meet performance objectives associated with an ad-hoc network environment and the like. More specifically, the invention provides a routing methodology proven to provide high (e.g., close-to-optimal) throughput and low delay guarantees. Further, the present invention preferably considers a network with both static and mobile nodes. The mobile nodes preferably follow a particular model of movement, referred to herein as a mobility model.

The invention discloses a quality overhead ratio hop cluster-based service discovery method and a mobility model establishing method. The service discovery method improves a k-hop non-uniform cluster scheme in the conventional CASD scheme and provides a quantitative criteria for the cluster hop, namely the quality overhead ratio. By searching a hop value at the maximum quality overhead ratio and uniformly clustering according to the optimized hop, the load balance and the maximum quality overhead ratio of cluster-head nodes can be realized. In the mobility model establishing method, a random walking model is adopted to establish the mobility model for the network nodes. The quality overhead ratio hop cluster-based service discovery method avoids the probability of idle load or full load operation of the cluster-head nodes, and better realizes the load balance of the cluster-head nodes; and more importantly, the quality overhead ratio hop cluster-based service discovery method can realize the maximum ratio of the service and communication quality to the cluster and communication overhead, namely the maximum quality overhead ratio.

The invention discloses a self-adaptive over-booked LEO satellite system channel distribution method, and belongs to the field of mobile communication. The self-adaptive over-booked LEO satellite system channel distribution method specifically comprises the steps of firstly building a mobile model of an LEO satellite system and setting a condition for a channel distribution strategy; aiming at a beam cell Ci, initially setting the total occupation number of virtual channels S to be equal to zero; then aiming at a call request of a user with high priority, accessing the beam cell Ci and judging whether the call request is a new calling request or a switched call request, and aiming at different requests, performing self-adaptive over-booked channel distribution processing respectively and determining whether to access the new call request or the switched call request; and finally, processing the ended call by the beam cell Ci and transferring a preserved request at any virtual channel to the occupied available channel. The self-adaptive over-booked LEO satellite system channel distribution method has the advantages of obtaining a relatively low new call blocking rate and improving the service quality of the whole system under the condition of ensuring that the switching call drop rate of the user with high priority is close to zero.

The invention belongs to the technical field of mobile communications, and discloses a Markov mobility model suitable for a mobile Ad Hoc network in obstacle environment. The invention is characterized in that the construction process of the mobility model comprises the following steps: giving out the concept of the obstruction property and transparency of the obstacle, and analyzing two situations that the obstacle obstructs the node movement but does not influence communications, and obstructs the node movement and interrupts signal transmission; expressing the node movement condition by using a discrete-time Markov chain, and obtaining node location information by utilizing state identifications; and finally, giving out two state-transition matrix setting methods. Under different state-transition matrixes, the node has different movement characteristics. The invention can simulate the node movement conditions in a true environment, and is suitable for various obstacle environments.The state-transition matrixes are utilized to describe the node movement conditions, and the movement conditions with different characteristics are obtained by adjusting the parameters in the state-transition matrix.

A novel method and apparatus is presented for providing transparent mobility of an entity within a network, by allowing the entity, which has a communication path set up between it and a peer entity, to move from one location to another, without informing the peer entity of this movement, and without having the communication path broken. The invention is applicable to decentralized networks using IP protocols, and is particularly applicable on networks where the mobility mechanism neither introduces latency nor decreases the available bandwidth of the network. In the invention, neither is latency increased nor is bandwidth utilization increased, as is done in other mobility models. Additionally, the invention utilizes standard protocols that are widely available from a plurality of equipment manufacturers on a variety of platforms. Thus, the invention provides a very cost-effective model for network providers that need to support transparent mobility within their networks.

The invention provides a full path typhoon hazard analysis method based on statistical dynamics. A generating model is used to generate annual occurrence times and occurrence positions of typhoon, and a one-dimensional kernel probability density function and a three-dimensional kernel probability density function are used to estimate the annual occurrence times of the typhoon and the probability density of the generating positions of the typhoon on the ocean, and in addition, a Monte Carlo method is used to simulate the annual occurrence times and the occurrence positions of the typhoon. The simulated annual occurrence times and the simulated occurrence positions of the typhoon are substituted into the mobility model of the statistical dynamics to simulate the positions of the typhoon in every six hours after the generating of the typhoon, and at the same time, an intensity model is used to estimate the intensity of the typhoon in every six hours. The generating positions of the typhoons simulated by the generating model of the kernel density probability function are not limited by historical generating positions, and a defect of less typhoon generating point samples caused by an empirical full path model directly using the historical generating positions is overcome.

The invention provides a method and system for establishing a 3-dimension spatio temporally correlated group mobility model of an unmanned aerial vehicle mobile ad hoc network node. The method comprises an initialization step, a selection step, a member node setting step and a logic center node setting step. The method also comprises the step that a member node generates a base speed, direction and pitch angle value through utilization of a Gauss Markov stochastic process; and the member node calculates to obtain the final speed, direction and pitch angle value at the current moment by referring to the speed, direction and pitch angle value of a logic center node at the current moment. The method has the beneficial effects that a time correlation mobility track is established through utilization of the Gauss Markov stochastic process; the node mobility space correlation is established through a method of setting the logic center node; and the mobility state of the unmanned aerial vehicle mobile ad hoc network node is decomposed into three dimensions of the speed, the direction and the pitch angle, thereby establishing the 3-dimension space mobility model and establishing the mobility model applicable to various scenes.

The embodiment of the invention provides a navigation control method and device and mobile equipment. The method includes the steps that actual parameter data of reference system parameters is collected; according to the currently collected actual parameter data and a mobility model, current actual behavior data is obtained, wherein the mobility model is obtained by conducting training according to sample parameter data of the reference system parameters and expected behavior data; by combining the current actual behavior data and the expected behavior data, an action instruction is generated; according to the action instruction, the mobile equipment is controlled to walk. By means of the navigation control method and device and the mobile equipment, the accuracy of route navigation is improved.

A method for operating an integrated circuit tester information processing system includes: measuring current information from test structures for an integrated circuit having a stress liner; forming a transfer curve by simulating based on the current information with a first range of first mobility multipliers; forming an inverse transfer curve by applying an inverse transfer function to the transfer curve; forming a stress curve with second mobility multipliers from the inverse curve; and validating the second mobility multipliers by comparing a measured curve and a simulated curve with the measured curve based on the current information and the simulated curve based on stress curve.

The invention provides a spiral line mobility model construction method based on an SDN, which is used for solving the problems of unsmooth track and inaccurate coverage of an existing model in searchand rescue scenes. According to the scheme, the method comprises the following steps: 1) constructing an application layer including a search and rescue control center and a field command vehicle forcommanding a search and rescue team to enter a disaster area; 2) constructing a control layer to collect emergency events occurring in a scene, calibrating priorities of the emergency events, sortingthe emergency events, and generating a target area search list according to an event sequence; 3) generating unmanned aerial vehicle moving track data according to the region search list provided bythe control layer, and establishing a data layer; 4) enabling the application layer, the control layer and the data layer to jointly form an SDN-based spiral line mobility model, and employing the model to complete the coverage of the disaster area. According to the invention, the smoothness of the flight path is ensured, and the accurate search of the target area is realized; the system can be used for searching and rescuing victims in disaster scenes and providing temporary aerial base stations for the victims.

A computer implemented method of planning a drone flight path to increase safety of dynamic objects the drone is estimated to encounter along the flight path based on a mobility model constructed to predict movement of dynamic objects, comprising receiving sensory data captured over time by one or more sensors monitoring movement of a plurality of dynamic objects in a certain geographical area, analyzing the sensory data to identify one or more mobility patterns of one or more dynamic objects detected in the certain geographical area, updating a mobility model with the mobility pattern(s) and generating a planned flight path based on the mobility model for one or more drones planned to fly in the certain geographical area, the flight path is planned to maintain a predefined safety space between the drone(s) and the dynamic object(s).

The invention provides a system and method for location management in a mobile network through sharing individual mobility model between a mobile station and the mobile network. The mobile station and the mobile network always exchange large amounts of data in order to make location updating management in the conventional way, which in turn results in an increase in the overall network overhead and wastes the network resource. The system and method of the invention makes location management in both the mobile station and the mobile network by sharing the mobility model reflecting the action regulation of the mobile station between the mobile station and the mobile network, such that the network overhead is greatly reduce.

The invention provides a large-scale network accessibility model based on an Internet of Vehicles communication base. Considering the redundant characteristics of an Internet of Vehicles network node,an Internet of Vehicles network topology is given, namely the Internet of Vehicles communication base, and a heuristic algorithm is used to give a construction method of the communication base. Starting from the internal structure attribute and the dynamic characteristic of the communication base, and in combination with a smooth Gaussian-semi-Markov mobility model, the connectivity and stabilityof an Internet of Vehicles large-scale network are proved, and an Internet of Vehicles accessibility theoretical model is given; the theoretical model can accurately evaluate the network connectivityand stability under an Internet of Vehicles high dynamic environment, and provide a theoretical support for a network layer and provide real-time data guarantee for an application layer, so that stable and everlasting transmission of important information, such as traffic accident information and real-time media data and the like, in the Internet of Vehicles high dynamic network environment can be kept, which has important theoretical and practical application values.

Provided is an integrated-system simulation system obtained from a simulation system having a command, control, and communication (C3) system of systems (SoS). The integrated-system simulation system includes an abstracted command and control (C2) model including a traffic model including inter-node traffic information transferred according to time, a mobility model including position information of nodes, and an interface model making the traffic model and the mobility model interoperate, and a communication (C) model configured to be combined with the abstracted C2 model so as to interact with the abstracted C2 model in a full-duplex manner. The abstracted C2 model is generated by acquiring traffic and mobility data between the C2 model and the C model of the SoS simulation system, hypothesizing a form of the abstracted C2 model, and learning the traffic and mobility data acquired from the SoS simulation system and determining variables of the abstracted C2 model form.