title: SSL: Signal Similarity-Based Localization for Ocean Sensor Networks.
abstract: Nowadays, wireless sensor networks are often deployed on the sea surface for ocean scientific monitoring. One of the important challenges is to localize the nodes' positions. Existing localization schemes can be roughly divided into two types: range-based and range-free. The range-based localization approaches heavily depend on extra hardware capabilities, while range-free ones often suffer from poor accuracy and low scalability, far from the practical ocean monitoring applications. In response to the above limitations, this paper proposes a novel signal similarity-based localization (SSL) technology, which localizes the nodes' positions by fully utilizing the similarity of received signal strength and the open-air characteristics of the sea surface. In the localization process, we first estimate the relative distance between neighboring nodes through comparing the similarity of received signal strength and then calculate the relative distance for non-neighboring nodes with the shortest path algorithm. After that, the nodes' relative relation map of the whole network can be obtained. Given at least three anchors, the physical locations of nodes can be finally determined based on the multi-dimensional scaling (MDS) technology. The design is evaluated by two types of ocean experiments: a zonal network and a non-regular network using 28 nodes. Results show that the proposed design improves the localization accuracy compared to typical connectivity-based approaches and also confirm its effectiveness for large-scale ocean sensor networks.
authors.affiliation: School of Computer Science and Technology, China University of Mining and Technology, Xuzhou 221116, China. chenp@cumt.edu.cn.
authors.forename: Pengpeng
authors.initials: P
authors.lastname: Chen
authors.affiliation: School of Computer Science and Technology, China University of Mining and Technology, Xuzhou 221116, China. cumtmahonglu@163.com.
authors.forename: Honglu
authors.initials: H
authors.lastname: Ma
authors.affiliation: School of Computer Science and Technology, China University of Mining and Technology, Xuzhou 221116, China. gaoshouwan@cumt.edu.cn.
authors.forename: Shouwan
authors.initials: S
authors.lastname: Gao
authors.affiliation: Transportation Bureau of Dinghai District, Zhoushan 316000, China. believesea@126.com.
authors.forename: Yan
authors.initials: Y
authors.lastname: Huang
keywords: localization; sea surface; similarity; wireless sensor networks