CN-121985314-A - Internet of vehicles resource scheduling method based on self-adaptive variable step optimization algorithm

CN121985314ACN 121985314 ACN121985314 ACN 121985314ACN-121985314-A

Abstract

The invention is suitable for the technical field of Internet of vehicles communication, and provides an Internet of vehicles resource scheduling method based on a self-adaptive variable step optimization algorithm, which comprises the steps of firstly constructing a scene model and a communication model, constructing an optimization problem, calculating fitness of all individuals and selecting a group length and a command officer; and determining the behavior strategy of each individual according to the size relation between the set pr value and the randomly generated p value, obtaining a new position by the individual execution strategy, recalculating the fitness, and upgrading the weight and the grade of the individual if the fitness of the individual becomes better after updating the position. After all individual updates are completed, the location of the group leader and commander is updated and a new group leader and commander is reselected according to the current fitness. Finally, by repositioning soldiers with poor fitness, the soldiers are prevented from being trapped in local optimum, and the soldiers are continuously updated in an iterative manner until the maximum iteration times are reached. The invention can effectively reduce the time delay of the vehicle task, optimize the communication resource allocation and improve the system performance.

Inventors

JIANG YUJIE

Assignees

江苏大学

Dates

Publication Date: 20260505
Application Date: 20260127

Claims (8)

1. The Internet of vehicles resource scheduling method based on the self-adaptive variable step optimization algorithm is characterized by comprising the following steps: s1.1, initializing resource parameters including bandwidth, computing capacity and other resource parameters of a vehicle and a base station, and resource demand parameters of each task including bandwidth, computing capacity and delay requirements; S1.2, defining a fitness function for evaluating the resource allocation effect of the task, wherein the fitness function considers the matching degree of the resource requirement of the task and the resources of the vehicle, the base station and the MEC server; S1.3, adopting an adaptive step-variable strategy according to the resource requirement of the vehicle and the priority of the task, Step length adjustment To optimize resource allocation; s1.4, maximizing the resource utilization rate through an optimization algorithm, and simultaneously ensuring that the delay requirement of task completion meets the requirement of the Internet of vehicles; S1.5, performing dynamic resource allocation on tasks, and performing priority sorting according to the resource requirements and delay requirements of the current tasks to allocate proper resources; S1.6, continuously updating resource allocation through repeated iterative optimization and step length adjustment until the requirements of all tasks are met and the optimal solution is converged; S1.7, outputting a final resource allocation scheme, and performing scheduling adjustment according to task demands and system load conditions to ensure efficient operation of the Internet of vehicles system.
2. The internet of vehicles resource scheduling method according to claim 1, wherein in the step (2), the calculation formula of the fitness function is: Where Di is the resource requirement of task Ti, ti is the actual completion time of the task, tmax is the maximum tolerance time of the task, and λi is the penalty factor associated with the task delay.
3. The internet of vehicles resource scheduling method according to claim 1, wherein the steps of The length adjustment formula is: Where γ is the adjustment coefficient, dtarget is the ideal resource requirement of the target task, and Dcurrent is the resource requirement of the current task.
4. The internet of vehicles resource scheduling method according to claim 1, wherein the objective function calculation formula is: 。
5. The internet of vehicles resource scheduling method of claim 1, wherein the final resource allocation scheme ensures that the resource requirements of each task in the internet of vehicles are satisfied and each task is appropriately allocated resources based on its priority and resource requirements.
6. The method for scheduling internet of vehicles resources according to claim 1, wherein the resource allocation is continuously adjusted by iterative optimization for a plurality of times, step adjustment and task priority ordering until the delay and bandwidth requirements of the tasks reach the maximum resource utilization of the system.
7. The internet of vehicles resource scheduling method according to claim 1, wherein the method is applied to dynamic resource allocation and scheduling in an internet of vehicles system to ensure efficient communication between vehicles and reasonable allocation of computing resources, avoid resource waste and maximize system efficiency.
8. The internet of vehicles resource scheduling method according to claim 1, wherein the method enables the resource allocation and the demand of the communication task to be consistent all the time and can effectively cope with the change of the mobility of the vehicle and the demand of the communication by performing adaptive resource optimization and dynamic adjustment in the internet of vehicles.

Description

Internet of vehicles resource scheduling method based on self-adaptive variable step optimization algorithm The invention relates to the technical field of Internet of vehicles (V2X) communication, in particular to an Internet of vehicles resource scheduling method based on a self-adaptive variable step optimization algorithm, which is particularly applied to the optimized allocation of communication resources among vehicles and roadside units (RSUs). The method improves the communication efficiency of the Internet of vehicles system and reduces the communication time delay by optimizing the resource scheduling, thereby solving the problem of resource scheduling efficiency in the high dynamic environment in the prior art Low rate and slow convergence speed. Technical Field The invention relates to the technical field of Internet of vehicles (V2X) communication, in particular to an Internet of vehicles resource scheduling method based on a self-adaptive variable step optimization algorithm, which is particularly applied to the optimized allocation of communication resources among vehicles and roadside units (RSUs). The method improves the communication efficiency of the Internet of vehicles system and reduces the communication time delay by optimizing the resource scheduling, thereby solving the problem of resource scheduling efficiency in the high dynamic environment in the prior art Low rate and slow convergence speed. Background With the rapid development of intelligent transportation systems and internet of vehicles (V2X) technology, communication between vehicles and roadside units (RSUs) has become increasingly important. The internet of vehicles communication system not only needs to realize high-speed data transmission, but also meets the requirements of low time delay and high reliability. However, in real world applications, internet of vehicles communication presents a number of challenges. How to reasonably allocate limited communication resources according to different network states in a dynamic Internet of vehicles environment, improve the transmission rate of the system and reduce the time delay becomes a difficult problem to be solved in the Internet of vehicles resource scheduling field. In the prior art, although some resource scheduling methods based on static rules exist, the influence of uncertain factors such as vehicle speed change, environment interference and the like on network performance is difficult to deal with, and an ideal scheduling effect cannot be achieved. In order to solve the problems, an Internet of vehicles resource scheduling method based on an adaptive variable step optimization algorithm is provided, and the scheduling strategy is flexibly adjusted to adapt to the speed change and the channel fluctuation, so that More efficient resource scheduling and more optimized internet of vehicles communication are achieved. Disclosure of Invention The invention aims to provide a vehicle networking resource scheduling method based on a self-adaptive variable step optimization algorithm, which aims to solve the problems of low resource utilization rate and tasks existing in the existing vehicle networking resource scheduling technology Long response time, unbalanced resource allocation and the like. In order to achieve the above purpose, the present invention provides the following technical solutions: step 1, initializing resource parameters including bandwidth, computing capacity and other resource parameters of a vehicle and a base station, and resource demand parameters of each task including bandwidth, computing capacity and delay requirements; step 2, defining a fitness function for evaluating the resource allocation effect of the task, wherein the fitness function considers the matching degree of the resource requirement of the task and the resources of the vehicle, the base station and the MEC server; Step 3, according to the resource requirement of the vehicle and the priority of the task, adopting a self-adaptive step-changing strategy to adjust the step delta t so as to optimize the resource allocation; step 4, searching for the maximized resource utilization rate through an optimization algorithm, and simultaneously ensuring that the delay requirement of task completion meets the requirement of the Internet of vehicles; step 5, carrying out dynamic resource allocation on the task, carrying out priority sequencing according to the resource requirement and the delay requirement of the current task, and allocating proper resources; step 6, continuously updating resource allocation through repeated iterative optimization and adjustment until the requirements of all tasks are met and the optimal solution is converged; And 7, outputting a final resource allocation scheme, and performing scheduling adjustment according to task demands and system load conditions to ensure the efficient operation of the Internet of vehicles system. 1:Fitnessi ⋅ c Where Di is the resource re