A Comprehensive Data Gathering Network Architecture in Large-Scale Visual Sensor Networks

• Published in: PloS one 2020-01, Vol.15 (1), p.e0226649-e0226649
• Main Authors: Zhang, Jing, Tsai, Pei-Wei, Xue, Xingsi, Ye, Xiucai, Zhang, Shunmiao
• Format: Article
• Language: English
• Subjects: Algorithms; Architecture; Computer and Information Sciences; Computer Communication Networks - instrumentation; Computer science; Computer Simulation; Data collection; Data management; Data mining; Ecology and Environmental Sciences; Electric power transmission; Electronic Data Processing - instrumentation; Electronic Data Processing - methods; Energy consumption; Engineering; Engineering and Technology; Humans; Image Interpretation, Computer-Assisted - methods; Information management; Information science; Laboratories; Linear programming; Maintenance; Methods; Models, Theoretical; Novels; Pattern Recognition, Automated - methods; Physical Sciences; Research and Analysis Methods; Sensors; Visual Perception; Wireless Technology - instrumentation
• ISSN: 1932-6203; 1932-6203
• DOI: 10.1371/journal.pone.0226649

The fundamental utility of the Large-Scale Visual Sensor Networks (LVSNs) is to monitor specified events and to transmit the detected information back to the sink for achieving the data aggregation purpose. However, the events of interest are usually not uniformly distributed but frequently detected in certain regions in real-world applications. It implies that when the events frequently picked up by the sensors in the same region, the transmission load of LVSNs is unbalanced and potentially cause the energy hole problem. To overcome this kind of problem for network lifetime, a Comprehensive Visual Data Gathering Network Architecture (CDNA), which is the first comparatively integrated architecture for LVSNs is designed in this paper. In CDNA, a novel α-hull based event location algorithm, which is oriented from the geometric model of α-hull, is designed for accurately and efficiently detect the location of the event. In addition, the Chi-Square distribution event-driven gradient deployment method is proposed to reduce the unbalanced energy consumption for alleviating energy hole problem. Moreover, an energy hole repairing method containing an efficient data gathering tree and a movement algorithm is proposed to ensure the efficiency of transmitting and solving the energy hole problem. Simulations are made for examining the performance of the proposed architecture. The simulation results indicate that the performance of CDNA is better than the previous algorithms in the realistic LVSN environment, such as the significant improvement of the network lifetime.