Natural Disaster Monitoring with Wireless Sensor Networks: A Case Stud y of Data-intensive Applications upon Low-Cost Scalable Systems - Chen, Dan; Liu, Zhixin; Wang, Lizhe; Dou, Minggang; Chen, Jingying; Li, Hui (Mobile Networks and Applications, 2013)
The wireless sensor network (WSN) technology has applied in monitoring natural disasters for more than one decade. Disasters can be closely monitored by augmenting a variety of sensors, and WSN has merits in (1 ) low cost, (2) quick response, and (3) salability and flexibility. Na tural disaster monitoring with WSN is a well-known data intensive appl ication for the high bandwidth requirements and stringent delay constr aints. It manifests a typical paradigm of data-intensive application u pon low-cost scalable system. In this study, we first assessed represe ntative works in this area by classifying those in the domains of appl ication of WSNs for disasters and optimization technologies significan tly distinguishing these from general-purpose WSNs. We then described the design of an early warning system for geohazards in reservoir regi on, which relies on the WSN technology inspired by the existing work w ith focuses on issues of (1) supporting reliable data transmission, (2 ) handling huge data of heterogeneous sources and types, and (3) minim izing energy consumption. This study proposes a dynamic routing protoc ol, a method for network recovery, and a method for managing mobile no des to enable real-time and reliable data transmission. The system inc orporates data fusion and reconstruction approaches to bring together all data into a single view of the geohazard under monitoring. A distr ibuted algorithm for joint optimal control of power and rate has been developed, which can improve utility of network (> 95 %) and to minimi ze the energy consumption (reduction by > 20 % in comparison with LEAC H). Experimental results indicate the potentials of the proposed appro aches in terms of adapting to the needs of early warning on geohazards .
Keywords: Data-intensive application; Geohazard; Natural disaster monitoring; Scalable system; Wireless sensor network