Abstract
Many novel and exhilarating applications emerged in the past decade, thanks to the ubiquity and the volume of data in this big data era. However, large-scale data collection is often expensive and time-consuming, especially in the physical world. To address this issue, in this paper, we study a new research problem, named k-Collector Problem (k- CP)}, which considers to minimize the data collection time for a set of k data collectors in the road network. We propose a constant- ratio approximation algorithm, called Collective Search Walk Planning (CSP). Moreover, we also discuss different strategies to boost the efficiency of CSP. Experimental results on 3 real datasets show that our proposed CSP algorithm outperforms other baselines in both solution quality and efficiency.