68 results about "Cloud computing resource allocation" patented technology

The invention relates to a cloud computing resource scheduling method based on dynamic reconfiguration virtual resources. The method comprises the steps of: using cloud application load information collected by a cloud application monitor as a basis; making a dynamic decision based on the load capacity of the virtual resources for running cloud application and the current load of the cloud application; and dynamically reconfiguring virtual resources for cloud application based on the decision result. Dynamic adjustment of resources is realized by a method for reconfiguring virtual resources for cloud application, without needing dynamic redistribution of physical resources or stopping executing cloud application. The method can dynamically reconfigure the virtual resources according to the load variation of the cloud application, optimize allocation of the cloud computing resources, realize effective use of the cloud computing resources, and meet the requirements on dynamic scalability of cloud application. In addition, the method can avoid waste of the cloud computing resources, and save the cost for using resources for cloud application users.

A workload associated with a task is assessed with respect to each of a plurality of computing paradigms offered by a cloud computing environment. Adaptive learning is employed by maintaining a table of Q-values corresponding to the computing paradigms and the workload is distributed according to a ratio of Q-values. The Q-values may be adjusted responsive to a performance metric and/or a value, reward, and/or decay function. The workload is then assigned to available computing paradigms to be performed with improved utilization of resources.

The invention relates to the dynamic resource scheduling technique in the cloud computing field, and provides a cloud computing dynamic resource scheduling method based on the feedback and a prediction mechanism. The method aims to overcome the defects of the cloud computing resource distribution and scheduling technique in the prior art, and can achieve balance use of various computer resources in a cloud computing environment, obtain satisfactory load balance under small pay expenses and improve comprehensive efficiency of system scheduling. According to the scheme, various performance indexes of virtual machines are monitored in real time in operation processes of the virtual machines, operation circumstances of all the current virtual machines within a next short period of time are predicted according to the monitored various current performance indexes of the virtual machines and a virtual machine state prediction model based on state feedback when a task request comes, and the most adaptive virtual machine is selected by combining a prediction result and a required task type and the required task is distributed. In addition, the invention further discloses a corresponding cloud computing dynamic resource scheduling system applicable to dynamic resource scheduling.

The invention discloses a method and a system for distributing cloud computing resources, and relates to the field of cloud computing resource scheduling. The method comprises that various performance indexes of the cloud computing resources of a client are monitored; a current health degree value of the cloud computing resources is calculated according to the monitored various performance indexes and a cloud resource health degree model, wherein the current health degree value can reflect the various performance indexes comprehensively; when the current health degree value exceeds a cloud resource performance alarming threshold value, an cloud resource performance alarm is sent so as to prompt the client that cloud computing resource allocation needs to be optimized; and the cloud computing resources needed by the client are distributed according to a pre-set cloud resource optimization allocation strategy. Automatic monitoring is conducted on the cloud computing resources such as performance indexes of a central processing unit (CPU), internal memory, discs, network input or output (I/O). The current health degree of the cloud resources is calculated according to the performance indexes and the health degree model, and intelligent distribution of the cloud resources is achieved by utilizing an automation resource scheduling technology of cloud computing, and therefore optimal performance of the cloud resources is ensured.

The present invention discloses a game based cloud computation resource allocation method and system. According to the method and system, game balance is introduced, so that interests of a user and a resource provider are taken into full consideration, and corresponding incentives are provided for the user and the resource provider, so as to improve the trade satisfaction of the user and the resource provider; a combined bidirectional auction mechanism is applied to a cloud resource allocation process, thereby effectively solving the problem that one party is monopolistic in cloud resource transaction, and meeting diversified cloud computation resource requirements; an allocation solution is optimized in the final allocation process; while interests of both the user and the resource provider are met, the closest offer and charge are sought so as to complete the transaction; multiple transactions are completed, so that auction number of times are greatly reduced, auction time is reduced, the cloud resource utilization ratio is improved to a greatest extent while both the user and the resource provider are satisfied with the cloud resource allocation solution, the cloud resource allocation system achieves resource load balance through resource dispatching management, idle resources are reduced and resource allocation is optimized.

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 relates to a cloud computing resource allocation method supporting sudden emergency. The method comprises the steps that 1, user resource application information including user priority,urgency degree of resource requirements, resource application quantity and configuration is acquired; 2, the user resource allocation priority is calculated; 3, resource information of a physical server is acquired; 4, the resource utilization rate of the physical server is calculated; 5, a multi-objective function with optimal performance matching of a virtual machine, shortest time provided bythe virtual machine and minimum total load change of a platform and a constraint condition are established; 6, a mapping relation of a virtual machine request and the physical server is established; 7, resource allocation is conducted. According to the cloud computing resource allocation method supporting the sudden emergency, the multi-objective function and the constraint condition are established, a multi-objective optimization algorithm is adopted for obtaining a solution set, a solution is selected as a mapping scheme, and optimal arrangement of the virtual machine can be achieved. Meanwhile, the allocation method has the function of supporting the sudden emergency and can preferentially allocate resources for sudden emergency users.

The invention discloses a cloud computing resource allocation method which relates to the technical field of cloud computing and aims to solving the technical problems of improving the cloud resource utilization rate. The method comprises the following steps: using the cloud computing resource which is reserved by a reservation user but un-used as a temporary resource, building a discrete model of a resource rent cost of temporary user in renting temporary resource, calculating the temporary resource rent cost according to the built discrete model, and allocating the temporary resource to the temporary user according to the calculated out temporary resource rent cost; when the reservation user requires to use the reserved resource, and the required reservation is allocated to the temporary user, storing the application of the temporary running on the resource, recovering and associating to the reservation user, waiting for a spare temporary resource, and then allocating the temporary resource to the reservation user which has not yet reached the end of run. With the adoption of the method, the resource use right of the reservation user is ensured, and meanwhile, the cloud computing resource utilization rate is improved.

The invention discloses a microcloud computing resource allocation method based on a pricing mechanism in an edge computing environment. The concept of a central controller is introduced, idle resources of cooperation microcloud are coordinated and utilized, the goal of reducing transmission delay and energy consumption is realized, the relationship between the microcloud and the central controller is modeled as a double-phase Stackelberg game, each cooperation microcloud determines the computing resource quantity required in the deployment phase, and the central controller coordinates the resource sharing between microcloud in the operation phase, so that the resource utilization rate of an edge computing system based on microcloud is increased, and the cost of a network service provideris reduced to the utmost extent when the user service quality is maintained.

The invention discloses a cloud computing resource distributing method based on energy consumption optimization. The cloud computing resource distributing method includes the steps that a cloud computing experiment platform is deployed; cloud computing resource distribution describing and modeling are conducted; different energy consumption optimization factors are selected; simulation platform construction is conducted; a test experiment is conducted on performance; model correction is conducted; a performance simulation experiment is conducted; a performance analysis model and key factors are determined; an energy consumption optimizing model for resource distribution under the cloud computing environment is studied; a heuristic resource distribution algorithm for achieving load balancing and meeting energy consumption minimization is designed; a performance simulating and testing experiment is conducted. According to the cloud computing resource distributing method based on the energy consumption optimization, the practical situation of resources under the cloud computing environment can be accurately and truly reflected, the energy consumption optimizing model is provided, and the limitation that only user task time demands are considered in an existing research method is broken through. In addition, the heuristic resource distribution algorithm achieving resource load balancing and energy consumption optimization is provided, and the limitation that global and local search balancing cannot be ensured in an existing resource distribution algorithm is broken through.

The invention provides a method and a system of user personalized scheduling of cloud calculation resources. The user personalized scheduling method of the cloud calculation resources comprises steps as below: obtaining user characteristic data; obtaining relevant cloud calculation resource regulation scheme according to the user characteristic data; scheduling according to the cloud calculation regulation scheme. The user personalized scheduling system of the cloud calculation resources comprises a user characteristic module, a connection module and a scheduling module, wherein the user characteristic module is used for obtaining user characteristic data, the connection module is used for obtaining the relevant cloud calculation scheduling scheme according to the user characteristic data and the scheduling module is used for scheduling according to the cloud calculation resource scheduling scheme. The method and the system of the user personalized scheduling of the cloud calculation resources are capable of improving distributing efficiency of cloud calculation resources.

The invention provides a method for enhancing fair cloud computing user resource quota allocation. The method includes the steps of firstly, judging an application type, executing the second step if application is first application, and executing the fourth step if the application is a change application, secondly, acquiring the maximum quota of resource quotas corresponding to a user application system, thirdly, allocating the resource quotas for the first time, fourthly, judging the type of the change application, releasing the corresponding resource quotas if the resource quotas are the resource reduction quota, and executing the fifth step if the resource quotas are the resource increase quota, fifthly, calculating a credit factor shown in the specification, sixthly, allocating the resource quotas which are applied for increase if the credit factor is larger than a reference value C<0>, and multiplying the resource quotas which are applied for increase by a coefficient shown in the specification and then allocating the resource quotas to users if the credit factor is smaller than the reference value C<0>, and seventhly, the resource quotas of the users are dynamically adjusted with time T as the period. By means of the method for allocating the cloud computing user resource quotas, resource abuse is avoided, and allocation fairness is enhanced; the demand quantity of cloud computing platform resources can be effectively evaluated in advance, and the requirements of more users are met.

The invention provides a scheduling method of cloud computing resources. The scheduling method of the cloud computing resources includes: using the maximum burst load, average throughput and the maximum response time to rectify database access requests sent out by a virtual machine so as to form an access request queue; when the access request queue is not full, preferentially scheduling the database access request highest in real time performance through concentrated scheduling; when the access request queue is blocked, calculating the quantities of resources needed by the virtual machine to allocate on all nodes, and processing a high loading request through distributed scheduling of all the nodes. The scheduling method of the cloud computing resources improves utilization rate of database access resources according to database access characteristics of the virtual machine, and performs reasonable resource allocation on the access requests.

A method is described for providing cloud computing resources. The cloud computing resources having a plurality of virtual machine hours and/or bandwidth storage to be provided by a user and intended to attend a number of requests from the user, the requests including a plurality of tasks per second, the method portioning the virtual machine hours uniformly divided in units among several periods of time and providing access to the units virtual machine hours in response to said user's requests and dynamically allocating the cloud computing resources provided, by means of a temporal load awareness scheme.

The invention relates to the technical field of cloud computing resource management, in particular to a charging method for use of cloud computing resources. The charging method for use of cloud computing resources includes the following steps that resource use calculation and charging standards are determined; occupancy expenses of charge resources are calculated out according to the charging standards; the resources are resources of a virtual machine. According to the charging method for use of cloud computing resources, different commercial promotion strategies can be flexibly achieved by changing relevant parameters in terms of a charging module of a cloud computing operation system. The charging method for use of cloud computing resources can be applied to expense computing of use of resources of the cloud computing virtual machine.

The invention discloses a method and system for increasing the utilization rate of cloud computing resources. The method includes the step of detecting a cloud computing request massage from a user to obtain the IP address of the user, the step of obtaining log records related to the user from a cloud computing server according to the IP address, the step of analyzing the log records to obtain characteristic parameters of the user and the step of matching resource scheduling strategies associated with the characteristic parameters and allocating the cloud computing resources to the user according to the resource scheduling strategies. According to the technical scheme, allocation efficiency of the cloud computing resources can be improved on the basis of specific circumstances of the cloud computing resources used by the user.

The invention relates to an optimal service allocation algorithm for mobile applications under mobile cloud computing; the optimal service allocation algorithm can simulate the service and a usage mode of a mobile user according to the mobility of the user. Modeling is firstly performed on mobile cloud service, the mobile user and the mobile applications, and is then performed on the service quality of the mobile applications, and the optimal service allocation algorithm based on mobile awareness in a cloud environment is finally provided. In cloud resource allocation, the optimal service allocation algorithm improves Qos level, reduces delay and power, also has better robustness for error/uncertainty when being used for predicting location-time workflow of the mobile user, and is better in expansibility.

The invention discloses a cloud computing resource allocation method based on a fair and credible two-way auction mechanism. Each provider provides unit prices and the number of various virtual resources capable of being provided by each provider and the available duration of the virtual resources, for an auction arbitration institution in a sealing mode; each user reports the required number and use duration for the virtual resources and an assessment value of the user for a virtual machine to which the user applies, to the auction arbitration institution in the sealing mode; and the auction arbitration institution calculates priorities according to the resource information reported by the providers and the resource requirements reported by the users, sorts the providers and the users according to the priorities in a descending mode, thereby obtaining a provider queue and a user queue, and reads each user from the user queue, in sequence, to match the providers, wherein factors of two aspects of resources and total prices are taken into consideration when matching is carried out, and resource allocation is finished. Through adoption of the method, a fair and efficient auction mechanism can be provided for a cloud resource provider and a user.

The invention discloses a dynamic resource allocation method based on a cloud computing platform, and relates to the technical field of cloud computing resource allocation. The method comprises the following steps: step 1, creating a plurality of virtual servers on the cloud computing platform; step 2, matching the virtual servers according to a user request list, and allocating resources in a resource pool to users according to a matching result; step 3, dynamically allocating the resources in the resource pool according to temporary requirements of the users, wherein the temporary requirements are stored in a temporary requirement list; and step 4, recycling the resources in the resource pool according to the request of the users. The virtual IP numbers of the virtual servers are storedin the resource list; and the resource list stores resource records corresponding to the virtual servers. According to the dynamic resource allocation method disclosed by the invention, the pluralityof virtual servers instead of other excessive resources are created in the resource pool in advance, thereby realizing the creation of the effective virtual resources in advance and solving the problem of inconsistency between the time saving of the advanced resources and the waste caused by the creation of excessive resources in advance.

The invention discloses a cloud computing resource allocation method. The method includes the following steps that when a user needs to apply to a cloud service provider to reallocate resources or replace a host machine, the user can obtain an IP address of the host machine by using the RARP through a virtual machine; the user makes a request to the host machine where the user is located for reallocating the resources or replacing the host machine; the host machine where the user is located negotiates with a management center according to the SLA to judge whether the request made by the user meets the SLA or not; if not, the request of the user is refused; if yes, the host machine examines whether existing resources can meet the request of the user or not; if not, the virtual machine is informed through an IP of the virtual machine used by the user, and then the user is informed by the virtual machine; if yes, the resources are reallocated or the host machine is replaced. According to the method, by improving the initiative of the user and establishing a user-centered schedule strategy, convenience is brought to the user and the resource utilization ratio is increased.

The invention relates to a cloud computing resource allocation method and device, equipment and a storage medium. The invention discloses a cloud computing resource allocation method, which comprisesthe steps of obtaining the matching degree of each node in a cloud system based on a target task, and allocating the target task to the node with the highest matching degree, wherein the matching degree is obtained according to the sub-matching degree corresponding to each resource, and the sub-matching degree is obtained according to the demand of the target task for the resources, the weight ofthe resources and the remaining amount of the resources in the nodes; when the node with the highest matching degree corresponding to the target task is determined, distributing the target task to thenode with the highest matching degree; sequentially allocating each target task to the corresponding node with the highest matching degree. According to the method and the system, dynamic resource allocation of each target task is realized, so that resources in the cloud system can be fully utilized under the condition that the demand of the target task for each resource can be met, the number ofthe target tasks which can be executed by the system in unit time is increased, and the resource use efficiency of the system is optimized.

The invention discloses a cloud computing resource allocation method in a multi-user MEC system. The method is based on task information of a mobile user and channel information between the mobile user and an MEC server. A miswork loss model is established by taking income maximization as a target; task waiting time is not included. Tasks of which the completion time is greater than or equal to the deadline are rejected by utilizing a function in the miss work loss model. EDD sorting is performed on remaining tasks. An execution sequence is determined by utilizing a branch and bound method; the MEC server executes the tasks of which the completion time is less than the deadline according to the execution sequence to acquire maximum income. According to the invention, benefit maximizationis taken as a target. An MEC server miss work minimization problem is modeled into an optimization problem taking a task execution sequence as an optimization variable. The problem is solved, a miswork loss model is established, a sorting algorithm based on a branch and bound method is provided to search for the optimal solution of the problem, tasks with small loss are refused as much as possiblewhile the deadline of an unloading task is met, and income maximization is achieved.