Abstract
Cyber physical systems (CPS) sense the environment based on wireless sensor networks. The sensing data of such systems present the characteristics of massiveness and multi-dimensionality. As one of the major monitoring methods used in in safe production monitoring and disaster early-warning applications, skyline query algorithms are extensively adopted for multiple-objective decision analysis of these sensing data. With the expansion of network sizes, the amount of sensing data increases sharply. Then, how to improve the query efficiency of skyline query algorithms and reduce the transmission energy consumption become pressing and difficult to accomplish issues. Therefore, this paper proposes a new energy-efficient skyline query method for massively multidimensional sensing data. First, the method uses a node cut strategy to dynamically generate filtering tuples with little computational overhead when collecting query results instead of issuing queries with filters. It can judge the domination relationship among different nodes, remove the detected data sets of dominated nodes that are irrelevant to the query, modify the query path dynamically, and reduce the data comparison and computational overhead. The efficient dynamic filter generated by this strategy uses little non-skyline data transmission in the network, and the transmission distance is very short. Second, our method also employs the tuple-cutting strategy inside the node and generates the local cutting tuples by the sub-tree with the node itself as the root node, which will be used to cut the detected data within the nodes of the sub-tree. Therefore, it can further control the non-skyline data uploading. A large number of experimental results show that our method can quickly return an overview of the monitored area and reduce the communication overhead. Additionally, it can shorten the response time and improve the efficiency of the query.
Highlights
The cyber physical system (CPS) senses the environment based on wireless sensor networks (WSNs)
To improve the skyline query efficiency and reduce the data comparison and the amount of data transmission, this paper proposes to select a tuple that has the largest domination ability as the local cutting tuple in the query child tree whose root is the node in a bottom-up manner
When collecting the query results, E2Sky uses efficient dynamic filters to cut a large number of non-skyline results, and only small amounts of the non-skyline data must be transmitted in the network
Summary
The cyber physical system (CPS) senses the environment based on wireless sensor networks (WSNs). Reducing the transmission energy consumption is necessary and important [8] Because these systems have strict requirements on the data validity and the timeliness of the feedback control, they must address the massive data more quickly [9,10] and implement the energy efficient query for the area that is prone to danger or disaster [11,12,13]. E2Sky, an Energy-Efficient Skyline query method for massively multidimensional sensing data This method uses a node cut strategy to dynamically generate filtering tuples that have little computational overhead when collecting query results instead of issuing queries with filters.
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