群智感知需求不确定任务的资源分配方法
A Resource Allocation Method for Task with Demand Uncertainty in Crowd Sensing
姚秋言 1赵丹1
作者信息
- 1. 上海理工大学光电信息与计算机工程学院 上海 200093
- 折叠
摘要
对群智感知任务类型中的突发任务资源分配问题进行研究.首先分析突发任务的特点,建立突发任务需求不确定的多阶段随机规划模型,并使用三个指标:效率、效力和公平来衡量资源的分配,提出以最小化成本为目标的非线性优化问题.然后,针对优化问题,提出基于Q学习算法的资源分配方法,并与动态规划算法和启发式算法作对比.实验结果表明,Q学习算法在精度上优于启发式算法,在计算速度上优于动态规划算法.
Abstract
The problem of resource allocation for sudden tasks in crowd sensing has been studied.Firstly,the characteristics of sudden tasks are analyzed and a multi-period stochastic programming model with uncertain demand for sudden tasks is estab-lished.Three indicators are used to measure the allocation of resources,which are efficiency,effectiveness and fairness.A nonlin-ear optimization problem for minimizing cost is proposed.Then,aiming at the optimization problem,a resource allocation method based on Q learning algorithm has put forward and compare with dynamic programming algorithm and heuristic algorithm.Experi-mental results show that Q learning algorithm is better than heuristic algorithm in accuracy and dynamic programming algorithm in computing speed.
关键词
群智感知/需求不确定/多阶段随机规划/Q学习Key words
crowd sensing/demand uncertainty/multi-period stochastic programming/Q learning引用本文复制引用
出版年
2024
国家科技期刊平台
NSTL
万方数据