A Tree-Cluster-Based Data-Gathering Algorithm for Industrial WSNs With a Mobile Sink

作者：Chuan Zhu, Shuai Wu, Guangjie Han, Lei Shu, Hongyi Wu · 发表于：IEEE Access · 年份：2015 · DOI：10.1109/access.2015.2424452 · 被引用次数：156 · 研究领域：Energy Efficient Wireless Sensor Networks、Energy Harvesting in Wireless Networks、Opportunistic and Delay-Tolerant Networks

Wireless sensor networks (WSNs) have been widely applied in various industrial applications, which involve collecting a massive amount of heterogeneous sensory data. However, most of the data-gathering strategies for WSNs cannot avoid the hotspot problem in local or whole deployment area. Hotspot problem affects the network connectivity and decreases the network lifetime. Hence, we propose a tree-cluster-based data-gathering algorithm (TCBDGA) for WSNs with a mobile sink. A novel weight-based tree-construction method is introduced. The root nodes of the constructed trees are defined as rendezvous points (RPs). Additionally, some special nodes called subrendezvous points (SRPs) are selected according to their traffic load and hops to root nodes. RPs and SRPs are viewed as stop points of the mobile sink for data collection, and can be reselected after a certain period. The simulation and comparison with other algorithms show that our TCBDGA can significantly balance the load of the whole network, reduce the energy consumption, alleviate the hotspot problem, and prolong the network lifetime.