摘要
现有的感知信息质量研究主要集中在节点的招募、选择和感知任务的分配阶段,缺少对感知任务执行过程的优化。为此,借鉴移动设备云中的感知任务迁移理念,设计基于效用的感知任务迁移算法,提出一种移动群体内节点间直接协作的感知方法。对感知任务的执行阶段进行优化,以解决移动设备的异构性与感知信息质量需求之间的矛盾。实验结果表明,与随机选择算法和基于多任务的参与者选择算法相比,该算法可有效提高感知数据覆盖率和感知任务完成率。
The existing researchon sensing information quality mainly focuses on the mobile nodes recruiting,selecting and sensing task allocating,lacking optimizing the execution of sensing tasks. This paper proposes Sensing Task Migrating（ STM） method based on utility among the distributed heterogeneous mobile sensing devices which can collect sensing data collaboratively. The process of task execution is optimized to solve the contradiction between the heterogeneity of mobile devices and the qualty reauirement of sensing information. Experimental results showthat,compared with random selecting algorithm and participant selecting algorithm based on multi-tasking,the algorithm improves the ratio of sensing data coverage and the ratio of sensing task finished.
出处
《计算机工程》
CAS
CSCD
北大核心
2017年第7期15-21,共7页
Computer Engineering
基金
国家自然科学基金(61370197)
关键词
移动群智感知
效用
感知任务迁移
协作感知
信息质量
Mobile Crowd Sensing（MCS）
utility
Sensing Task Migrating（STM）
collaborative sensing
information quality
