Optimizing k-Collector Routing for Big Data Collection in Road Networks

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.