移动群智感知中的空间任务分配机制

在移动群智感知的空间任务分配问题中用户与任务的空间距离直接影响完成任务所需的成本，而现有的研究在这方面却考虑不足，因此以最小化感知成本为目标设计了移动群智感知中的空间任务分配机制。首先，以感知成本最小为目标，基于遗传算法和贪心算法设计了一种高效的任务分配方法；其次，针对用户感知质量的随机性，基于用户的历史感知情况和当前任务的执行情况设计了用户感知质量的更新机制。为验证所提机制的效果，通过仿真实验与两种基准的任务分配方法作比较。实验结果表明，所提机制在感知总成本和用户执行任务所移动的总距离等方面均有更好的效果，因此该空间任务分配机制具有很好的应用前景。

Assignment mechanism for spatial tasks in mobile crowd sensing

For the allocation of spatial tasks in mobile crowd sensing, the spatial distance between users and tasks directly affects the cost required to complete the tasks, while the existing research about this is considered inadequate. In order to minimize cost, the paper proposed a spatial task allocation mechanism. Firstly, based on genetic algorithm and greedy algorithm, it designed an efficient task allocation method to minimize the cost required to complete the tasks. Secondly, considering the randomness of user sensing quality, it designed a mechanism of user sensing quality updating based on the historical quality and the quality of the current task. To verify the effectiveness of the proposed mechanism, it conducted simulations compared with the two benchmarks. The results show that for spatial task allocation the proposed mechanism has better results in terms of total cost and spatial distance that the user needs to move to perform the task. Therefore, the allocation mechanism proposed has better foreground.