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在移动群体感知中,移动终端集成了丰富的感知设备和通信端口且分布广泛,能够收集、共享各类感知数据。然而,由于移动设备在感知能力、通信端口、移动规律等方面存在异构性,这与要收集实时、精确且覆盖全面的感知信息之间存在矛盾。为了在异构群体中收集优质的感知信息,提出了一种带有任务拆分的感知任务迁移算法(简称STOTS算法)。该方法感知信息质量在感知数据覆盖率方面有所提高。
In mobile group awareness, the mobile terminal integrates a wealth of sensing devices and communication ports and is widely distributed to collect and share various types of perceptual data. However, due to the heterogeneity of mobile devices in terms of their perception, communication ports and movement patterns, there is a contradiction between collecting real-time, accurate and comprehensive perception information. In order to collect high-quality perceptual information in heterogeneous groups, a perceptual task migration algorithm with task splitting (STOTS algorithm) is proposed. The method perceived quality of information has increased in perceived data coverage.