A Resource Allocation Method for Task with Demand Uncertainty in Crowd Sensing
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.
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