334 results about "Mobile cloud computing" patented technology

The invention discloses a system and method for health management based on the internet of things and cloud computing. The system comprises at least one health detection device, an intelligent mobile platform, a cloud center server, at least one doctor working platform, at least one relation query platform and at least one client side. The client sides comprise the emergency center client side and the insurance client side. The health detection device is connected with the intelligent mobile platform through a communication protocol. The intelligent mobile platform is connected with the cloud center server through a communication network. The relation query platform, the doctor working platform, the emergency center client side and the insurance client side are respectively connected with the cloud center server. According to the system and method for health management based on the internet of things and cloud computing, a user, a relation and a doctor are main participants, services such as health data checking, recording, visual displaying, data analyzing and mining, doctor guiding, customization message pushing, positioning and tumbling detection pre-warning are provided for the user, meanwhile, a health service is provided for infants, and a monitoring service is provided for the endowment insurance and the medical insurance.

Aspects of the present invention include distributing new resources closer to end-users which are making increased demands by spinning-up additional virtualized instances (as part of a cloud provisioning) within servers that are physically near to the network equipment (i.e., web servers, switches, routers, load balancers) that are receiving the requests.

The invention discloses a cloud security access control model. The model is characterized in that: aiming at the multi-tenant architecture characteristic of cloud computing, by combining a role-based access control (RBAC) model, a tenant concept and a cloud service provider concept are introduced to an access control model, and a uniform tenant access control model and a user access control model are formed by defining model elements and formally describing model functions. The cloud security access control model can adapt to the characteristic of multi-tenant of the cloud computing, improves the flexibility of user authority management in a cloud computing environment, can reduce the complexity of authorization management and management overhead, and can effectively ensure the security and integrity of user data in the cloud computing environment.

The invention discloses a hybrid cloud computing system based on a cloud bus and a realization method of the hybrid cloud computing system. The system is based on a local private cloud, one or more public clouds are integrated, the internal constitution of the local private cloud is consistent with that of the public cloud, both the internal constitution of the local private cloud and the internal constitution of the public cloud comprise an infrastructure, a virtualization layer, a cloud platform layer, a cloud bus layer, a cloud application layer, a management center and a storage center, wherein the hardware resources on a bottom layer are grouped into a virtual cluster through the infrastructure and the virtualization layer so as to provide different virtual resources to the superior layer; the cloud platform is used for operating a web application program or a service and utilizing an open interface to carry out the secondary development and application integration; and the cloud bus layer is used for managing and monitoring various services on the cloud platform layer and is a hub for connecting the cloud application layer and the cloud platform layer, and the cloud bus layer is established on the basis of SOA (service oriented architecture) concept and comprises a control bus, a plurality of node buses and an adapter. Due to the adoption of the hybrid cloud computing system, the migration of the existing IT (internet) environment of an enterprise to a cloud computing environment can be accelerated, the investment can be reduced, and the resource can be adequately utilized.

The invention provides a highly-efficient safe outsourcing decryption method based on the attribute encryption in mobile cloud computing environment. The method comprises the following steps: system initialization; a data owner encrypting a file and uploading the file to a cloud service provider; an authorization organization generating secret keys; a third party transforming ciphertexts; and a mobile terminal user decrypting the file. According to the method, targeted for the mobile cloud computing environment, by utilizing a ciphertext policy attribute-based encryption shared data method, according to the requirement of limited operation and storage capacity of a mobile terminal, and under the premise of guaranteeing data security, a portion of complex decryption tasks are outsourced to the third party; and by utilizing outsourcing decryption, secret key decomposition technique and matching algorithm, unnecessary bilinearity pairing operation is reduced, and a reliable method is provided for the mobile terminal to carry out rapid decryption.

The invention discloses a mobility management method and system for mobile edge computing. The method comprises the following steps that a change of an IP address of UE is acquired to obtain a changeof a bearing path, and a position change of the system UE is determined by analyzing a data packet; after target MEC acquires a bearing change of the system UE, the system UE is guaranteed to continuously use services of an MEC application in a process of moving in different MEC regions; the mobile edge computing application is migrated from system source MEC to system target MEC according to a migration decision; after the system migration is completed, the system target MEC carries out routing update and provides a local mobile edge computing service for the system UE; and the system targetMEC provides services for the system UE and sends a notification to the system source MEC simultaneously, and the system source MEC determines whether to be closed or not according to a use conditionof a system application. According to the method, the energy optimization can be effectively realized on the premise of guaranteeing the customer service quality.

The invention relates to a comprehensive service providing system and method based on cloud computing. The system comprises a user interface module, a management module, a functional module and a basic cloud computing platform, wherein the management module is used for calling the functional module according to requesting information sent by the user interface module, conducting unified management on the functional module and the basic cloud computing platform, storing the service record fed back by the functional module and conducting monitoring analysis, the functional module is used for providing the service needed by a user according to corresponding resource support obtained from the basic cloud computing platform through the calling of the management module, and the basic cloud computing platform is used for conducting unified management and deployment on resources of a physical resource pool and a virtual resource pool and providing corresponding resource support according to the calling of the functional module. According to the system and method, the user can obtain technologies such as information safety, big data, intelligence and mobile Internet needed by enterprises and websites online, user-related IT requirements can be met quickly, and a flexible, customized, high-quality and highly-reliable service platform is provided for the user.

The invention provides a base station, a service processing method and a cloud computing system. The base station comprises the steps of building a wireless network bearing channel between the base station and user experience (UE), receiving service requests of the UE through the wireless network bearing channel, analyzing request contents in the service requests of the UE, generating cloud service access requests through the contents needed to be processed by a cloud server terminal according to the request contents, sending the cloud service access requests to the cloud server terminal, and returning corresponding processing results of the cloud server terminal to the UE through the wireless network bearing channel. Therefore, transport layer protocols and access layer protocols of a user device side are ended at the base station, and cross layer optimization is achieved through the base station, the service processing method and the cloud computing system.

The invention discloses a method for scheduling resource based on cloud computing. The method comprises the following steps that: a visualization policy management interface is provided for a user; each policy is partitioned in the visualization policy management interface and is set into the minimum atom policies; the atom policies interacted with the user are provide and operations including modification, addition, delete, combination and priority determination are carried out on the atom policies, and an extensive makeup language (XML) file editor with which the user can edit a user-defined resource allocation policy is provided on the visualization policy management interface; the visualization policy management interface receives the operations of the user to the resource policy and transmits the requests of the user to the resource policy operations to a cloud server; the cloud server receives the requests submitted by the visualization policy management interface and stores the requests into corresponding resource scheduling policy information in a mode that the user is taken as a unit; and the cloud server receives the resource requests of the user and allocates the resource according to the stored corresponding resource policy information of the user. By utilizing the method, a scheduling policy defined by a third party can be supported under a cloud computing environment.

The invention provides an electronic nose air quality monitoring system and method based on cloud computing. The system is provided with an electronic nose cloud terminal, a cloud monitoring center and a mobile phone client. A mode recognition network, a concentration computing network, a pollution source positioning network and an air quality forecasting network are configured on the cloud monitoring center. The electronic nose air quality monitoring system has the advantages that system integrates technologies such as an electronic nose, cloud computing, Internet of Things, clean energy and manual neural network, air quality and position information of each monitoring point are collected in real time and stored, information such as pollution gas category, concentration, pollution source position and air quality forecasting of each monitoring point is obtained after algorithm processing, and results are pushed to the mobile phone client, a large-range and large-scale air quality remote real-time monitoring and forecasting function is achieved, the monitoring results are precise, and the monitoring function is powerful.

The invention provides a heterogeneous storage management architecture system and method oriented to cloud computing. The system comprises a physical storage clustering module, a driving adaption layer module, a data access scheduling module, a uniform storage interface module and a client. According to the system and method, due to the fact that different storing types in the rear end physical storage clustering module are packaged, a uniform interface is provided for the front end. Different drivers provided by different block equipment service manufacturers can be provided with uniform interfaces. The expandability of a cloud service platform can be greatly improved, high cohesion and low coupling of cloud service platform architecture are achieved, flexible expandability is achieved under a cloud computing environment, and construction of private cloud and public cloud of enterprises is achieved.

The present invention provides a method and a system for a cloud computing system to allocate GPU resources to a virtual machine. By applying the method, the virtual machine does not need to be constantly allocated with certain GPU resources; when the virtual machine needs to perform related high-definition video or 3D rendering, the virtual machine can apply to the cloud computing management system for the GPU resources; after the virtual machine uses the GPU resources, the resources are released and return to a GPU resource pool, so that large amounts of the GPU resources are saved; and the cloud computing management system evenly distributes virtual machines in need of the GPU resources to computing nodes with GPU cards according to created GPU usage identifiers of the virtual machines, thereby achieving usage effects of load balance and GPU resource optimization.

The invention relates to a cross-terminal network browser tag page synchronizing method based on cloud computing. The method using a cloud server to synchronize tag pages opened through web browsers on a personal computer and a mobile terminal includes the steps: a user needs to set up a cloud account and log in on the web browsers of the personal computer and the mobile terminal; the opened webpage can be automatically synchronized onto the background cloud server; and whether the user needs to synchronize the tag page on the personal computer to the mobile terminal or not, clicking a synchronizing button, and the tag page can be synchronized among different devices and quite convenient to open.

The invention discloses a large high-definition video monitoring system based on cloud computing, comprising a video acquisition end which consists of a plurality of high-definition cameras, a broadband network, a cloud computing and storage platform which consists of cluster nodes and a monitoring end. Wherein, the video acquisition end acquires video data, the data is transmitted to the cluster nodes of the cloud computing and cloud storage platform via the broadband network after being coded to some extent, the platform decodes, classifies and stores the video data through cloud computing and cloud storage technologies, codes are converted according to the needs of the monitoring end, and images with different definition on different acquisition ends are transmitted to the monitoring end via the broadband network. Consequently, the large-scale high-definition real-time monitoring is realized.

The invention discloses a resource allocation method in a cloud computing system. The method comprises the following steps of: S1, obtaining the computing node parameters of computing nodes in the cloud computing system; S2, obtaining a resource need parameter according to an access request of a user; and S3, selecting the computing nodes, of which the computing node parameters meet the resource need parameter, from the cloud computing system, and allocating the resource of the selected computing nodes to the user for carrying out the access request. With the resource allocation method in the cloud computing system described by the embodiment, the resource can be allocated according to the user request in the cloud computing system, under the condition that virtual servers change frequently in the computing system, a dynamic load balancing strategy can be realized, the efficiency is improved, and the effective allocation of resource is guaranteed.

The invention discloses a multi-inter-domain asymmetric group key agreement protocol method under the mobile cloud computing network environment. The method comprises the following steps: adopting a bilinear mapping technology and a blind secret key technology to realize a short signature mechanism between a domain secret key management center and a domain terminal; using a short signature technology to realize a multi-inter-domain group key agreement authentication mechanism of terminals distributed in different domains, and further realize asymmetric group key agreement of the terminals distributed in multiple domains. The protocol method disclosed by the invention has the anonymity and the authentication, supports dynamic group key updating of nodes, and realizes the security of forward confidentiality and backward confidentiality of the group keys; on the hypothesis of the Diffe-Hellman bilinear computing problem, the security of the protocol is proved; the computing and communication energy consumption of the protocol is low; the method is good in flexibility, security and practicability, and suitable for cross-domain group key agreement of the terminals distributed in the multiple domains under the mobile cloud computing network environment.

The invention discloses a cloud computing system towards multiple tenants. The cloud computing system towards the multiple tenants is characterized by storing tenant data in different modes according to different requirements of the multiple tenants for data isolation; using an independent database to store the tenant data for the tenants who require high isolation, and using a shared database to store the tenant data in shared data architecture mode for common users. The cloud computing system towards the multiple tenants further introduces hierarchical management into a traditional access control model based on roles. Compared with the prior art, the cloud computing system towards the multiple tenants can meet user demands for different quality levels well, improves safety of an SaaS (software as a service) application platform, and improves right control management efficiency.

The invention discloses an Android platform App (Application) risk assessment method based on mobile cloud computing and an Android platform App risk assessment device based on the mobile cloud computing. The method comprises the following steps of: collecting all Apps in an Android market, and obtaining a permission list of each App; uploading data of the obtained permission list to the cloud; performing risk grade judgment according to the App privacy permission in the permission list and the set privacy permission risk mark in accordance with the obtained permission list of each App; and requesting data to the cloud according to the request of a mobile phone client, and sending the corresponding App risk grade judgment result obtained from the cloud and the privacy permission called by the App to a customer. The method and the device have the advantages that the permission characteristics of mass Apps are subjected to similar App population characteristic analysis; the dynamic minimum permission set of a certain population is defined; then, the malicious tendency of Android application software is detected by a similarity calculation method; a feasible and effective App assessment method is provided for a user; and the user privacy leakage risk is effectively reduced.

Disclosed is an electric power system resource integration method based on mobile cloud computing. The electric power system resource integration method includes that an electrical device condition monitoring module, a wireless mobile control cabin control center module, a mobile working module, a special service management module, a dispatching center module, a scientific research module, an experiment module, a scheduled maintenance pre-experiment module, a personal computer module, an electronic book module, a mobile phone internet module, and an enterprise distributed type server module in the whole power grid system are connected into a distributed type cloud internet through a resource pool (fusion cloud server). The method which integrates internal resources of the electric power system based on the mobile cloud computing mode has the advantages of being low in construction cost, and high in resource utilization rate, preventing recycle, being high in popularization, and the like.

The present invention discloses a method and apparatus for mining massive intelligent power consumption data based on cloud computing. The method comprises the following steps of: storing massive power consumption data generated by a peripheral system in a distributed file system; a user actively initiating a service request, and a master node receiving the request and analyzing the service request, selecting slave nodes required to participate in mining and a mining algorithm according to an actual situation, and assigning tasks to the slave nodes after decomposition of dimension; and each slave node according to the assigned task, performing data storage and task execution, using the data mining algorithm selected by master node to perform a power consumption data mining task independently, and interacting with task management. The apparatus comprises a data management module, a task management module, a task execution module, a data storage module, a mining model library module and a data dimension model module. According to the method and apparatus for mining massive intelligent power consumption data based on cloud computing, power consumption information of massive users is efficiently mined, and forecast of power consumption of domestic consumers is achieved, so as to develop an optimal power consumption strategy.

The invention relates to the technical field of cloud computing networks, particularly a network architecture based on cloud computing and a virtual network management method thereof. The network architecture based on cloud computing is implemented by three-layer virtualization: access layer virtualization, core layer virtualization and virtual machine virtual network. Access layer virtualization: virtualizing network resources on the access layer, thereby implementing the functions of bandwidth allocation, IP (Internet Protocol) address allocation, security access control and the like. Core layer virtualization: virtualizing core layer network devices, and directly intercommunicating service nodes and a service node and a storage node. Virtual machine virtual network: implementing a virtual network card and a virtual switching machine in a computation node. The virtual network card implements connection through the virtual switching machine, and is communicated with an external network. The invention solves the problem in managing the cloud computing network resources through three-layer virtualization technology, and improves the network performance; and the invention can be widely used in virtual networks.

The invention provides a video on demand method and a video on demand system based on cloud computing. A terminal sends video requests to a cloud server through a network, the cloud server carries out computing on the video according to the network link connection conditions and the screen resolution of the terminal to obtain a best-effect video suitable for the terminal, and in addition, the best-effect video obtained through the computing is provided for the terminal to be played. According to the technical scheme of the invention, the complicated video data is processed through the cloud computing, requirements of various kinds of terminal screens and complicated network conditions are met, and the applicability is high; the cloud computing is utilized for realizing the fast and efficient processing on complicated and huge data, the processing and the application of the terminal on the video are improved and expanded, and the terminal widening capability is high; and the could computing is utilized for processing complicated video data computing, and the cloud computing application is enhanced.

The invention discloses a resource allocation method of a cloud computing system. The method comprises steps of acquiring physical computing node parameters of physical computing nodes from a computing node list of the cloud computing system; selecting physical computing nodes meeting resource demand parameters in accordance with physical computing node parameters; acquiring virtual computing node parameters of virtual computing nodes of selected physical computing nodes from the computing node list; and selecting virtual computing nodes meeting resource demand parameters in accordance with virtual computing node parameters. By the aid of the resource allocation method of the cloud computing system, the cloud computing data center balancing method is modified, the mutual effect of a physical server and a virtual server are considered completely, different parameters are set respectively, hierarchical integrated computation is conducted and the stability of the cloud computing data center balancing effect is guaranteed.

The invention provides a mobile cloud computing resource optimal allocation method which comprises the following steps of: establishing a transfer implementation method between different service domains of cloud computing as a cloud computing resource allocation model of a mobile cloud computing system; analyzing the system long-term income of a mobile cloud computing service domain while considering the condition of transferring the cloud computing service between different cloud computing service domains by taking a mobile terminal and a mobile cloud computing service domain as a whole so as to obtain the best cloud computing resource allocation scheme between different mobile cloud computing service domains; and finally deciding to receive, transfer or reject a service request of the mobile terminal in the local cloud computing service domain. The method provided by the invention increases the system income of a cloud computing network and the customer satisfaction (or user QoE (quality of experience)) of a mobile cloud computing user on the basis of considering the benefits of the cloud computing service domain as well as the benefits of the mobile cloud computing user.

The invention discloses an autonomous metal development cloud robot system based on cloud computing. The autonomous metal development cloud robot system based on cloud computing comprises an image processing module, a robot autonomous metal development module, a cloud computing module, a mobile robot module, a multi-channel wireless communication module and a smart mobile terminal module, wherein the robot autonomous metal development module is realized in the cloud computing module, and data exchange is conducted between the mobile robot module and the image processing module, the cloud computing module and the smart mobile terminal module through the multi-channel wireless communication module in a wireless communication mode. According to the autonomous metal development cloud robot system based on cloud computing, in the process of realizing autonomous metal development of a robot, it is avoided that the mobile robot completes the intensive computing tasks by carrying a large number of computing resources, all the tasks are completed by the cloud computing module, and the workload for executing the intensive computing tasks of the robot can be effectively lightened; in addition, knowledge stored by the cloud computing modules can be shared by different robots.

The invention relates to the technical field of cloud computing, in particular to a distributed router obtaining method suitable for cloud computing. The method includes the following steps that firstly, three network bridges are established for each computational node; secondly, an isolated virtual network space is established for each network by the corresponding computational nodes, a network interface is added to each network and connected to the internal network bridge, and the dhcp service is started in each virtual network space; thirdly, each computational node establishes a new network space for multiple networks of the same tenant with the communication requirement, each new network space is named as a router network space, a network port is added to each network and connected to the corresponding router network space and serves as a gateway, and the same mac and ip are set for the gateway of the same network; fourthly, when virtual machines are established, arp tables of the router network spaces are correspondingly updated, and the virtual machines are connected to the internal network bridges; fifthly, a flow rule is set between the internal network bridges. According to the method, the problems of virtual machine network single-point faults and large loads are solved and the method can be used for obtaining distributed routers for cloud computing.

The invention discloses a scheduling method for a mobile cloud computing platform. The method comprises the following steps: monitoring resource occupancy of cloud system programs while running a group of cloud systems; if current total resource occupancy is higher than a preset upper threshold, dynamically changing an execution sequence of the group of cloud system programs according to a resource request amount occupied by each of the plurality of cloud system programs, so that execution priorities of the cloud system programs with relatively low resource occupancy are higher than the execution priorities of the cloud system programs with relatively high resource occupancy; executing the cloud system programs with relatively high resource occupancy at idle periods of execution intervals of the plurality of cloud system programs with relatively low resource occupancy; and when the current total resource occupancy is lower than a preset lower threshold, restoring or maintaining an original execution sequence. The invention also discloses a scheduling device for the mobile cloud computing platform. The scheduling device comprises a monitoring module, an execution priority scheduling module, an idle work scheduling module and an execution priority restoring module.