40 results about "Queue stability" patented technology

The invention relates to a heterogeneous cloud wireless access network resource allocation method based on deep reinforcement learning, and belongs to the technical field of mobile communication. Themethod comprises the following steps: 1) taking queue stability as a constraint, combining congestion control, user association, subcarrier allocation and power allocation, and establishing a random optimization model for maximizing the total throughput of the network; 2) considering the complexity of the scheduling problem, the state space and the action space of the system are high-dimensional,and the DRL algorithm uses a neural network as a nonlinear approximation function to efficiently solve the problem of dimensionality disasters; and 3) aiming at the complexity and the dynamic variability of the wireless network environment, introducing a transfer learning algorithm, and utilizing the small sample learning characteristics of transfer learning to enable the DRL algorithm to obtain an optimal resource allocation strategy under the condition of a small number of samples. According to the method, the total throughput of the whole network can be maximized, and meanwhile, the requirement of service queue stability is met. And the method has a very high application value in a mobile communication system.

The invention discloses a vehicle queue stability control method considering communication delay. The method comprises the steps that 1, a vehicle queue following mathematical model is established; 2,a nonlinear lower layer control gain is constructed by a feedback linearization strategy, and a node power unit is described as a node linear model; 3, a high-dimensional closed-loop state equation of a vehicle queue following control system under dynamic parameter uncertainty is established; 4, sufficient conditions are used for giving sufficient conditions that a vehicle queue with communication delay has a stabilization controller under the symmetric communication topology; and 5, the stabilization controller is constructed to obtain a controller gain so as to control static feedback control of a distributed controller, and the stability of the vehicle queue following control system is ensured. The method can ensure the stability of the vehicle queue following control system, reduces the vehicle queue following interval, increases the traffic flow, and reduces the energy consumption.

The invention provides a heterogeneous fleet fault tolerance control method based on a variable time interval strategy. The method comprises the following steps of carrying out force analysis on longitudinal motion of vehicles and combining an actuator fault model to establish a vehicle longitudinal dynamics model under an actuator fault; constructing the variable time interval strategy with a lower boundary of fault information according to information of the vehicles; based on the constructed variable time interval strategy, establishing a proportional integral differential sliding mode surface and a coupled sliding mode surface; and selecting an appropriate Lyapunov function to design a fault-tolerant controller and an adaptive update rate, and proving finite time stability of a system.Traffic flow stability is proved based on the variable time interval strategy with the lower boundary of the fault information. Queue stability is proved based on the proportional integral differential sliding mode surface and the coupled sliding mode surface. Compared with a traditional variable time interval strategy, by using the technical scheme of the invention, a problem of a non-zero initial spacing error can be solved, and a critical traffic capacity can be increased.

The invention discloses a vehicle queue stability control method considering vehicle dynamics parameter uncertainty. The method comprises the steps that 1 a mathematical model of vehicle queue following is established; 2 nonlinear lower-layer control gain is constructed through a feedback linearization strategy to describe a node dynamic unit as a node linear model; 3 the high-dimensional closed-loop state equation of a vehicle queue following control system under dynamics parameter uncertainty is established; 4 the stability of the high-dimensional closed-loop state equation is converted intothe stability of several low-dimensional sub-modal systems, and sufficient conditions for the existence of a stabilization controller for vehicle queues with dynamics parameter uncertainty under symmetric communication topology are given; and 5 the sufficient conditions are used to propose a low-dimensional Riccati inequality, and the solution of the Riccati inequality is used to construct a stabilization controller to acquire controller gain. The method provided by the invention can ensure the stability of the vehicle queue following control system, reduces the following interval of vehiclequeues, increases traffic flow, and reduces energy consumption.

The invention discloses a resource optimization method in mobile edge computing task unloading and electronic equipment. The method comprises the following steps: constructing a queue stability indextaking minimization of the task queue length of a user terminal and the task queue length of an edge server as a target; constructing a network resource overhead index; constructing a random network resource optimization model by taking the queue stability index as a constraint condition; introducing a Lagrange multiplier to carry out variable relaxation on constraint conditions of the random network resource optimization model, and constructing a coupling model; and solving the coupling model based on a momentum stochastic gradient descent algorithm to obtain an optimal resource allocation decision of each time slot. According to the method, the coupling model of the random network resource optimization model is constructed based on the original coupling theory, the coupling problem is solved online based on the momentum stochastic gradient descent algorithm, and task queue overstock is reduced while algorithm convergence is accelerated. The task queue backlog can be further reduced under the condition that the network resource overhead is not increased.

The invention relates to a wireless self-backhauling resource scheduling method based on system stability, and belongs to the field of mobile communication. The method ensures system queue stability,wireless backhauling constraint conditions and rate matching corresponding to a system achievable rate and minimum user service quality, i.e., an overflow probability meets a certain constraint, and aiming to maximize a grade of relative user quality satisfaction, the method carries out dynamic resource scheduling. In each discrete time slot, according to a queuing case with combined considerationto channel state information of users, a macro base station and a mini base station, suitable wireless resources are allocated to each user, and according to the overflow probability, a queue lengthis dynamically regulated so as to change a system actual achievable rate, combined dynamic regulation on the wireless self-backhauling mini base station and a backhauling and access resource allocation ratio of each user. The wireless self-backhauling resource scheduling method based on system stability, which is disclosed by the invention, can keep system queue stability when maximizing the gradeof relative user quality satisfaction.

An advance is made over the prior art in accordance with the principles of the present invention that is directed to a new approach for a system and method for a buffer management scheme. Certain embodiments of the invention improve the response of AQM schemes with controllable parameters to variations of the output rate of the bottleneck buffer. The impact on TCP performance can be substantial in most cases where the bottleneck rate is not guaranteed to be fixed. The new solution allows AQM schemes to achieve queue stability despite continuous variations of the bottleneck rate.

The invention discloses a spectrum access method for a distributed cognitive radio system, which mainly aims to solve the problem of low queue stability of secondary users in the conventional cognitive radio system. The method is implemented by the following steps of: 1) defining primary users and the secondary users in the cognitive radio system; 2) regulating the arrival rate of the secondary users to make the arrival rate of the secondary users lower than a maximum service rate under interference limitation; 3) continuously snooping channels of the primary users by adopting a carrier sensemultiple access (CSMA) protocol, and accessing the channels after snooping results indicate random withdrawal when idle by the secondary users; and 4) adaptively regulating withdrawal time length parameters by the secondary users to make the stable service rate close to the arrival rate to finally achieve queue stability. The method has the advantages that the queue stability of the secondary user is achieved and that primary and secondary user collision probability is lower than the interference limitation, and can be used for the cognitive radio system with strict requirements on queue delay in the field of wireless communication.

The invention discloses a distributed dynamic service deployment method based on mobile edge computing, which considers the high mobility of a user and the limited storage capacity of an edge server,maximizes the long-term system utility while ensuring the stability of a storage queue of the server, and achieves efficient unloading in a mobile edge network environment. According to the method, the long-term system utility maximization problem is decomposed into the online Lyapunov drift and penalty function minimization problem by utilizing Lyapunov optimization. Under the condition of no priori knowledge of the future moving track of the user, the future system utility is obtained through a sampling average approximation algorithm. In addition, service deployment probability distributionis introduced, and a Markov approximation model is utilized to dynamically deploy service request data. Theoretical analysis shows that the hybrid strategy service deployment decision provided by theinvention is a progressive optimal solution. The invention provides a new method for distributed dynamic service data deployment.

An advance is made over the prior art in accordance with the principles of the present invention that is directed to a new approach for a system and method for a buffer management scheme. Certain embodiments of the invention improve the response of AQM schemes with controllable parameters to variations of the output rate of the bottleneck buffer. The impact on TCP performance can be substantial in most cases where the bottleneck rate is not guaranteed to be fixed. The new solution allows AQM schemes to achieve queue stability despite continuous variations of the bottleneck rate.

The invention provides an effectiveness-perception redundancy-included data uploading method in a collaboration moving cloud. During a (t+D)th uploading process, all mobile terminals receive all state and decision information of all mobile terminal during a t th uploading process, wherein the D expresses a feedback delay of the system. An employed core conception of a distributed correlated optimization method is characterized in that each mobile terminal searches for an optimal solution in all uploading strategies during each uploading process; an energy consumption constraint is converted into a queue stability problem. Therefore, each mobile terminal can make a decision independently under the circumstance that future channel information is not obtained.

Two algorithms for different functional-split network models are provided, which are the CU-based (central unit based) beam allocation and admission control algorithm (CU-BAACA) and the DU-based (distributed unit based) beam allocation and admission control algorithm (DU-BAACA). Difference between the CU-BAACA and DU-BAACA includes whether the algorithm is implemented at the CU site or at the DU site. Proposed algorithms aim to optimize DUs' quality of experience (QoE) by admission control to determine the amount of data from application layer entering into traffic queue and allocating beam in physical layer at the fronthaul network between CU and DUs. On the other hand, queueing delay and queue stability are taken into consideration to maintain the system steadiness. Simulation results compare performance of two functional split models to find the appropriate scenario for each function split option, which provide technical requirement and applicability of the proposed algorithms for practical system.

The invention discloses a multi-vehicle cooperative control method and device for guaranteeing rapid formation and stability of vehicles, and the method comprises the steps: 1), an information collection module which is used for a controlled vehicle to collect the real-time state information of a pilot vehicle, an adjacent vehicle and the controlled vehicle; 2) a queue forming control module which ensures that a multi-vehicle system which is located on different lanes and runs at different vehicle speeds forms a queue; and 3) a queue stability control module which realizes the stability of a queue system by applying a queue stability robust cooperative control algorithm. According to the control method, a vehicle dynamic system and a cluster motion control algorithm are combined, and the problem that traditional queue forming control neglects vehicle dynamic characteristics is solved; according to the method, the stability of the queue system is guaranteed based on the Lyapunov-Crasovski stability theory, the redundancy of the control system can be reduced, and the method is suitable for popularization and application; in addition, the method also considers the phenomena of data packet loss and information time delay which sometimes occur in the information transmission process, and the control security level is higher.

The invention discloses a secure transmission method based on Key assistance. The method comprises the following steps that: a legal user has a data queue and a Key queue; when a channel is secure and reliable, the legal user transmits a data packet and a key packet respectively at a certain probability; when the channel is reliable but unsecure, the legal user transmits the data packet in a way of encrypting the data packet with the Key packet; and when the channel is reliable and the Key queue is empty or the channel is unreliable, the legal user stops transmission. According to a secure transmission protocol, corresponding delay and energy efficiency can be obtained through a queue analysis method. Under the constraints of the energy efficiency and queue stability, a scheme for minimizing delay of the legal user is constructed, and dual decomposition, primary decomposition and secondary decomposition are adopted for resolving. As proved by a simulation result, the method provided by the invention has the advantages that a secure transmission opportunity can be utilized fully in the absence of an external assistance node; the secure transmission rate is increased; and the transmission delay is reduced.

The invention discloses a packet scheduling method and device, a terminal and a storage medium, and the method comprises the steps: when a virtual queue is not empty, carrying out the calculation according to queue state information and a packet state update sending cost estimation formula, and updating a first estimation cost according to an obtained calculation result; when the virtual queue is empty, calculating according to the queue state information in combination with a packet forwarding cost pre-estimation formula, and updating a second pre-estimation cost according to an obtained calculation result; and determining a scheduling task executed by the scheduling system in the current scheduling period according to a comparison result of the latest first estimated cost and the latest second estimated cost. While the queue stability and the queue length are considered, the freshness of the information in the queue is also used as a scheduling index. The two methods compromise to perform task scheduling on the queue together, the queue length is stabilized, fresh information of the queue is effectively utilized, and balance of information freshness and queue stability is realized.