Resource Allocation Algorithm Based on Profit Maximization for Crowd Sensing

The key to realizing the crowd sensing network is to overcome the resource restrictions of energy, bandwidth, computing, and so on. First of all, due to the number of users and sensor availability will be dynamic change over time, crowd sensing system is difficult to accurately predict and allocate resource to accomplish a specific task. Secondly, there is a need to consider how to choose an effective subset from a large number of users with different sensing ability, so as to allocate the sensing devices in communication resources under the constraint conditions. This paper proposes a profit maximization algorithm for resource allocation component in crowd sensing environment. The proposed algorithm not only considers the current profit of crowd sensing service request but also considers the long-term expected profits, so as to ensure long-term maximum profit. The objective function is no longer to minimize the completion time but rather to achieve the target profit maximization. The experimental results show that the new algorithm is feasible and superior to the traditional algorithms.