50results about How to "Realize resource allocation" patented technology

The invention discloses a distribution method of multi-user parallel transmission resource in wireless heterogeneous network and mainly aims to solving the problem that the existing heterogeneous network source distribution technology cannot distribute the resource to concurrent shunt users; the distribution method comprises the steps that, (1), when a resource allocation cycle is coming, users report the detected channel quality indication information to each wireless access network, and report rate statistical information and resource request to a joint radio resource management module; (2), the wireless access network calculates the amount of the resource in each resource unit capable of being provided to users, and reports the resource amount and the channel quality indication information to the joint radio resource management module; (3), the joint radio resource management module calculates the priority of each user, and then sequentially distribute the resources to the users from high priority to low priority; and (4), the joint radio resource management module sends the resource distribution result to each wireless access network, and then the wireless access networks finish the user resource allocation. The distribution method has the advantages of high network resource use efficiency.

The invention discloses a resource allocation method under H-CRAN based on multi-time scale collaborative optimization. Resource allocation is taken as a two-layer model of large time scale-small timescale, from a large time scale perspective, according to long-term average information of a user moving track and the like, a large time scale resource allocation model based on an expert system is constructed by querying and matching priori knowledge of the expert system; from a small time scale prospective, according to short-term instant information of channel quality and the like, self-learning and self-optimizing characteristics of deep reinforcement learning are utilized to construct a small time scale resource allocation model based on the deep reinforcement learning; from a collaborative optimization prospective, based on a master-slave game view, a collaborative optimization resource allocation model taking the large time scale as the principle factor and the small time scale asthe secondary factor is constructed, and the resource allocation of a heterogeneous cloud wireless access network is achieved.

The invention discloses an edge computing resource allocation method and system for an ultra-dense network, and the method comprises the steps: collecting task requests of all terminal devices and resource states of all edge servers from a global perspective, and carrying out the reasonable allocation of computing resources of all the edge servers through employing an SDN controller as a decisionbody; the system comprises a macro base station, a micro base station and an edge server, and the macro base station is connected with each micro base station through a high-speed optical fiber link,and is in wireless connection with a mobile user. And the macro base station manages the resource condition of the whole network from the overall perspective and collects the information of each mobile user. According to the invention, the effectiveness of edge server computing resources, the resource total quantity of each server and performance difference are fully considered; a bidirectional multi-round auction mechanism is introduced into the multi-server computing resource distribution process in the ultra-dense network, the total income of the servers is maximized on the premise that theuser service quality is guaranteed, and the loads of all the servers are balanced.

The invention relates to an unmanned aerial vehicle resource allocation method based on a quantum bird flock evolution mechanism, belonging to the unmanned aerial vehicle autonomous control field. Themethod of the invention comprises the following steps: establishing a resource allocation model of an unmanned aerial vehicle; determining the types of UAV tasks, and initializing the quantum bird flocks; calculating the fitness according to the fitness function, and determining the global optimal position of the population; The quantum position is updated and measured through the quantum revolving gate and the quantum non-gate. Calculating fitness according to fitness function; Updating the local best position of each quantum bird and the global best position of the whole colony; judging whether the maximum iteration number is reached or not; if the maximum iteration number is reached, the global best position of the group is output and mapped to the task resource matrix. The invention fully takes into account the different resource requirements of the unmanned aerial vehicle (UAV) when executing different tasks, obtains an optimal UAV resource allocation scheme with a lower resourceallocation ratio at a time cost, simultaneously satisfies the performance requirements of the UAV, and obtains a more reasonable UAV resource allocation scheme.

This invention discloses one method to realize load network materials distribution, which comprises the following steps: dividing the LSP area into at least two Quos class and setting business type and each Quos class relation; then CA is as current business flow to send materials requirement to the load control layer; the load layer receives the requirement and determines the type relative class and judges the class relative LSP materials is enough, if yes, then dispatching the current business flow with relative LSP materials and then sends the successful message and starts mapping order; otherwise, sending the failure message to the linkage.

The embodiment of the invention discloses a D2D communication method, user equipment and a base station which are used for realizing resource allocation of D2D distributed networks and efficient utilization of channels. The method of the invention includes the step that the UE acquires a D2D distributed network data transmission request and time frequency-domain resources for channel measurement, and then, measures channels where the time frequency-domain resources are located to determine whether the channels are idle, and establishes D2D connections if the channels are idle. According to the D2D communication method of the invention, a D2D distributed network-based resource allocation process is provided, and D2D distributed network-based resource allocation under a D2D multi-hop data transmission condition can be realized.

The invention discloses a resource distribution method and apparatus. The resource distribution method includes the steps: a base station distributes resources for a physical uplink shared channel PUSCH of user equipment according to a pre-defined resource distribution mode; and the base station sends the resource distribution result to the user equipment through DCI. By means of the technical scheme of the resource distribution method and apparatus, resource distribution of PUSCH can be realized and the problem that the related technology has no distribution methods is solved.

The invention discloses a system for sharing books. The system comprises a book purchasing system for a user, a book printing system, a bookcase, a user mobile phone side and a server. The method comprises the following steps that: a user puts forward a book purchasing request for a platform; while the book is published, or for books which are published but are not sold, a two-dimensional code is printed on a book spine position, wherein the two-dimensional code contains the following information: the own information of a book, book purchasing user information and platform information; and the user puts, borrows and lends books. By use of the method and the system, the problem that books are difficult in sharing is solved, the user purchases books, the ''identity authentication'' of the user is added into a book purchasing link, necessary conditions are provided for the valuable circulation of books in a later stage, the ''property right'' of the book is transferred to the book purchasing user, and the user decides whether the book is "shared" to obtain earnings or not. Therefore, on one hand, platform input is lowered, and on the other hand, the development of "sharing" is accelerated.

The invention discloses an adaptive scheduling method for inverse synthetic aperture radar imaging resources in networking. On the basis of feature recognition on a target by each radar, three-dimensional information fusion is firstly carried out on the target; the time resource demand of the target in each radar is then analyzed; a radar for realizing target imaging is further determined according to constraint conditions for radar selection; and finally, a target imaging target resource scheduling model is established, the radar time resources are allocated reasonably, the resource scheduling for the imaging target is realized, and the working efficiency of the radar is improved.

The invention discloses a two-dimensional resource allocation method for networking radar multi-target ISAR imaging, relates to the technical field of phased array radar inverse synthetic aperture radar imaging, and solves the technical problem of how to reasonably allocate time and aperture resources of a radar system for a multi-target imaging task under a radar networking condition so as to improve the overall performance of the radar system. According to the method, on the basis of target feature cognition, requests for radar resolution are determined, time and aperture resources requiredby target imaging are determined by combining a sparse ISAR imaging technology and a radar equation on the basis; and then resource allocation of the networking radar system is realized through a two-dimensional resource scheduling model for multi-target imaging of the distributed networking radar system, and finally, a multi-radar to multi-target inverse synthetic aperture imaging task is realized through alternate observation and acquisition of target echo signals. According to the method, resource allocation is considered from two perspectives of time and aperture, the resource utilizationrate is improved, and the overall performance of the system is improved.

The invention discloses a two-way auction-based method of mobile group intelligence perception and resource allocation and an incentive mechanism thereof. The method is suitable for use in mobile group intelligence perception. Certain users are limited by perception resources and data collection conditions of equipment which is thereof and cannot provide high-rate high-quality data resources withdiversity, and need the aid of resources of other equipment to participate in scenes of mobile group intelligence perception. Under the scenes, on the one hand, the intelligent equipment can provide the richer resources by the aid of powerful computing capability of a micro cloud, and on the other hand, a data exchange network among the equipment can be established by the aid of other intelligentequipment with good performance status and high credibility. A process thereof involves two-way auction between the intelligent equipment and the micro cloud or between the intelligent equipment, andtherefor, auction theory can be applied to study resource allocation and incentive-mechanism design thereof.

The invention discloses an image processing system with a distributed architecture. The image processing system comprises a core controller and a plurality of embedded GPUs, wherein the core controller comprises an address channel, an image channel and a result channel which are parallel; wherein the address channel is used for receiving configuration parameters sent by remote control equipment; wherein the image channel is used for receiving image data to be processed and decoding the image data, distributing the image data to the corresponding embedded GPUs according to a target equipment mask obtained by decoding, and executing parallel data processing by the plurality of embedded GPUs; the result channel is used for receiving and outputting a processing result of the embedded GPU on the image data; based on the architecture of the FPGA core control panel and the plurality of embedded GPUs, the image processing speed is greatly improved, the structure simplification, high integration and system miniaturization of the system are realized, the use flexibility of the system is enhanced, and the test requirements of a large-size and high-resolution display panel are met.

The invention provides a new boundary calculation method for a visible light communication multiple access channel capacity region, and provides a new inner boundary and a new outer boundary of the multiple access channel capacity region in a visible light communication network under the constraint of a peak value and average optical power. In particular, the proposed inner bound is established byimplementing an input profile for each user using a single user capacity. The proposed external boundaries are derived by determining a single user capacity for each user and relaxing the input constraints to calculate a sum capacity upper limit. Numerical results show that the proposed new boundary is very tight, and is superior to existing boundaries over the wide area of SNR.

The invention discloses an interface management method, device and system. A gateway device receives interface information sent by the interface extension device, an Ethernet interface of the interface extension device is connected with an Ethernet interface of the gateway device, and the interface information comprises an interface type of a first OT interface of the interface extension device. The gateway device creates a first virtual interface according to the interface information, the first virtual interface corresponds to a first OT interface of the interface extension device, and the interface type of the first virtual interface is the same as that of the first OT interface. The gateway device allocates the first virtual interface to a target virtual open system of the gateway device, and therefore an application program in the target virtual open system can access the first OT interface. The gateway device sends an interface allocation completion notification to the interfaceextension device. The gateway device performs resource allocation on the virtual interface, so that resource allocation of the OT interface on the interface extension device is realized, and the application limitation of the interface extension device is reduced.

The invention relates to a cloud room sharing system and a commercial method based on intelligent identity identification, belonging to the field of information technology, including public and private cloud services. The system and method adopt big data processing technology, cloud computing technology, ID card or automatic intelligent unlocking module as the core link, and are based on the development of mobile phone APP, WeChat applet, WeChat public number, PC terminal booking system client, integrated communication technology applied to the operation and management process of hotels or lodging places. The invention has the advantages that the cloud server follows a one-to-many deployment mode, the application development cost of the hotel desktop end is reduced by adopting a hybrid cloud, and the cloud computing technology can realize effective resource allocation, thereby greatly reducing the burden of the hotel server.

The invention discloses a 5G network slice resource allocation method which is simple in implementation process, high in spectrum utilization rate and capable of meeting service requests of different users. The method comprises the following steps: (10) user communication time delay sensitivity acquisition: acquiring the sensitivity of a mobile user to communication time delay in a 5G wireless network slice, and performing data quantization on the sensitivity; (20) user service request distribution: distributing service requests proposed by mobile users to different network slices; (30) base station spectrum resource allocation: allocating the spectrum resources of the base station to different network slices by using a generalized Kailey algorithm and taking minimization of user transmission delay as a target cost function; (40) user spectrum resource allocation: further dividing the base station spectrum resources allocated to different network slices by using a Lyapunov algorithm, so that each mobile user obtains the required spectrum resources; and (50) data transmission: the user completes data transmission according to the obtained spectrum resources.

The embodiment of the invention provides an opportunistic network resource dynamic allocation method based on service priority, which is applied to a current node carrying a service message in an opportunistic network, and the service message comprises a target delay for sending the service message, a message size of the service message and an identifier of a destination node. The method comprisessteps of obtaining the total number of nodes in the opportunity network, the average congestion degree of the social group of the current node, the cache space size of the current node and the initial priority of the service message; calculating the number of copies of the service message based on the target delay, the message size, the total number of the nodes, the average congestion degree ofthe social group, the cache space size of the current node and the initial priority of the service message; and acquiring a plurality of service message copies of the service message, and sending theacquired service message copies to a destination node with the identifier. The method can improve the service quality of the service to which the service message belongs.

The invention provides an information processing method and a system of terminal security. The method comprises the following steps that a mapping relation server synchronizes a secure question statistical table to an information processing server which obtains a first current system time slice amount, the information processing server confirms a first distribution time slice and systematic surplus time slices of each terminal according to the secure question statistical table, the first current system time slice amount and a first strategy, and if the systematic surplus time pieces are larger than preset value, the information processing server takes the systematic surplus time slices as a second current system time slice amount. According to the first strategy, a second distribution time slice of each terminal is recounted, and if now the systematic surplus time pieces are smaller than or equal to the preset value, target distribution time pieces of each terminal are obtained according to the first distribution time slice and the second distribution time slice. According to the target distribution time slices of each terminal, the information processing server deals with security problem of each terminal.