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.
Highlights
Considering that environmental monitoring involves more spatial attributes, and often incurs a lot of computational cost for general skyline queries, we propose the geometry-based distributed spatial skyline query method in wireless sensor networks (GDSSky)
We design a clustering strategy for the parallel execution of general skyline queries on the non-spatial attributes of the spatial skyline, and conduct the spatial skyline query on the remaining spatial skyline points which are still not found by the tree method at the same time, so we can implement a distributed execution between different sub-regions
The attributes detected by the sensors include the spatial attributes (i.e., the distance to each query and non-spatial attributes, the paper presents a node) and non-spatial attributes, the paper geometry-based spatial skyline query method to quickly query a part of the geographical positions presents a geometry-based spatial skyline query method to quickly query a part of the geographical withpositions greater with domination ability in spatial calculate the maximum query boundary greater domination ability distance, in spatial distance, calculate the maximum query formed by query nodes
Summary
Nowadays applications using the sensor network monitoring strategy are being more and more widely used, such as in forest fire monitoring systems, CitySee, real time CO2 monitoring systems, real time shortest path for drivers [1], a complex embedded system-CPS [2], graph similarity issue [3], digital library services [4], data security [5], the development of the Internet of Things [6,7], the development of the Web of Things [8], Semantic Link Network (SLN) [9,10], different bird species’. In China, the current information people get is from placing in cities several monitoring sub-stations, which locations must be set in places which are widely apart and not disturbed by people, rather than in places near to the pollution sources This deployment can reflect the average air quality level of a city. As traditional monitoring strategies can only monitor the average situation of a large area and have limited flexibility for any small range, this paper proposes a skyline query method for sensor networks. We propose a distributed query method based on the data node tree concept to traverse all the neighbor sensor monitoring regions, and enter them into the queue according to the distance by the monotone function, so it can implement the execution in parallel.
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