【摘要】 移动群智感知技术基于众包思想，募集移动感知设备对周围环境进行感知，能够使得环境感知和信息收集更加灵活、方便、高效。任务分配方案的合理性直接影响到感知任务能否成功，因此制定合理的任务分配方案是移动群智感知相关研究中的热点和重点。目前，移动群智感知系统中的任务分配方法多是离线的，针对的是单一类型的任务，但是在实际中，在线的、多类型的任务分配更贴近实际。因此，文中针对多类型任务，将移动群智感知技术应用于军事末端感知中，结合移动群智感知技术在军事领域的应用特点，对移动群智感知中的任务分配方法进行了研究，提出了面向系统效益的在线任务分配策略。文中建立了长期的、动态的在线任务分配系统模型，并以系统效益为优化目标，基于李雅普诺夫优化理论对问题进行了求解，实现了任务准入策略和任务分配方案的长期在线动态控制。实验结果表明，所提出的在线任务分配算法是有效可行的，能够在线、合理地分配到达移动群智感知系统的任务，保证任务队列的稳定性，且可以通过调整参数值增加系统效益。更多还原

【Abstract】 Based on the idea of crowdsourcing, mobile crowdsensing(MCS) collects mobile sensing devices to sense the surroun-ding environment, which can make environment sensing and information collection more flexible, convenient and efficient.Whe-ther the task allocation strategy is reasonable or not directly affects the success of the sensing task.Therefore, formulating a reasonable task allocation strategy is a hotspot and focus in the research of MCS.At present, most of the task allocation methods in MCS systems are offline and targeted at single type tasks.However, in practice, online multi-type task allocation is more common.Therefore, this paper studies the task allocation method in MCS for multiple types of tasks, and proposes an online task allocation strategy oriented to system benefits combined with the characteristics of MCS technology in the military field.In this paper, a long-term, dynamic online task allocation system model is established, and the problem is solved based on Lyapunov optimization theory with the system benefit as the optimization goal, so that the online dynamic control of task admission strategy and task allocation scheme is realized.Experiment shows that the online task allocation algorithm proposed in this paper is effective and feasible.It can reasonably allocate the tasks arriving at the MCS system online, ensure the stability of the task queue, and increase the system utility by adjusting the parameter value.更多还原