Geometry-Based Distributed Spatial Skyline Queries in Wireless Sensor Networks

Abstract

Algorithms for skyline querying based on wireless sensor networks (WSNs) have been widely used in the field of environmental monitoring. Because of the multi-dimensional nature of the problem of monitoring spatial position, traditional skyline query strategies cause enormous computational costs and energy consumption. To ensure the efficient use of sensor energy, a geometry-based distributed spatial query strategy (GDSSky) is proposed in this paper. Firstly, the paper presents a geometry-based region partition strategy. It uses the skyline area reduction method based on the convex hull vertices, to quickly query the spatial skyline data related to a specific query area, and proposes a regional partition strategy based on the triangulation method, to implement distributed queries in each sub-region and reduce the comparison times between nodes. Secondly, a sub-region clustering strategy is designed to group the data inside into clusters for parallel queries that can save time. Finally, the paper presents a distributed query strategy based on the data node tree to traverse all adjacent sensors’ monitoring locations. It conducts spatial skyline queries for spatial skyline data that have been obtained and not found respectively, so as to realize the parallel queries. A large number of simulation results shows that GDSSky can quickly return the places which are nearer to query locations and have larger pollution capacity, and significantly reduce the WSN energy consumption.

Efficiently computing Pareto optimal G-skyline query in wireless sensor network

“…Few articles 4,[29][30][31][32] discussed different skyline applications in WSNs, such as continuous reverse skyline, spatial skyline, distributed dynamic skyline, and probabilistic skyline query in the WSNs.…”

Efficient Continuous Skyline Query Processing in Wireless Sensor Networks

“…Roh et al [18] propose a filter-based method for two-dimensional skyline query processing in WSNs, which provides an enhanced efficiency by reduction of the total wireless communication between sensor nodes. Furthermore, more aspects of skyline computation in WSNs, such as G-skyline query [19] and Geometry-Based Distributed Spatial Skyline Query [20], have been studied. However, none of these methods described above provides support for continuous skyline queries.…”

“…The size of query time interval [ t s , t e ] for the continuous skyline query varies from 200 to 400. Similar to the literature [20], we choose total communication cost as the main performance metric. Total communication cost , called TCC, denotes the number of the messages transmitted for computing the continuous skyline query in a time interval [ t s , t e ].…”

G-skyline query over data stream in wireless sensor network

“…Paper [42] proposed the skyline algorithms over data stream, but they focus on individual subjects rather than groups. [33][34][35][36][37][38][39][40] discussed different skyline applications in wireless sensor networks, such as continuous reverse skyline, spatial skyline, distributed dynamic skyline and probabilistic skyline query in the wireless sensor networks.…”