Aiming at the problem of unreliable data quality caused by sensing node uncertainty in mobile crowd sensing, a cross-domain collaborative filtering trusted sensing node recommendation method based on SDN is proposed. Firstly, SDN is introduced to decouple the service surface and the control surface, and it is convenient to manage sensing nodes and reduce the burden of server for task allocation. Then, through cross-domain collaborative filtering method, find sensing nodes which show similar credibility in the historical task allocation and complete some similar tasks with target sensing nodes. Finally, the recommendation value of the sensing node in the target task is obtained though the current ability of sensing nodes, and their distance from target tasks, and similar sensing nodes’ credibility in the target task and time decay, at last, the trusted sensing node is selected. Simulation experiments verify that when selecting a trusted sensing node, the method proposed in this paper has better recommendation accuracy, and the time is shorter. In addition, it also proves that when the sensing data of the same data quality is obtained, the incentive cost is lower.

针对移动人群感知中感知节点不确定性导致数据质量不可靠的问题，提出了一种基于SDN的跨域协同过滤可信感知节点推荐方法。首先引入SDN来解耦服务面和控制面，方便感知节点的管理，减轻服务器分配任务的负担。然后，通过跨域协同过滤的方法，找出在历史任务分配中表现出相似可信度的感知节点，并完成一些与目标感知节点相似的任务。最后，通过感知节点当前的能力、与目标任务的距离、相似感知节点在目标任务中的可信度和时间衰减，得到目标任务中感知节点的推荐值，最后，选择可信感知节点。仿真实验验证了本文提出的方法在选择可信感知节点时具有较好的推荐精度，且时间较短。此外，也证明了在获得相同数据质量的传感数据时，激励成本更低。