Abstract
Wireless sensor networks (WSNs) are important parts of Internet of Things or Cyber-Physical Systems (CPS). WSNs can be seen as a new type of distributed database systems. The data query processing is very important for WSNs. In this paper, we proposed a Continuous Top-k Contour Regions Querying algorithm (CTCRQ) which can continuously obtain the top-k contour regions and does not lose the rate of precision (accuracy). We take full advantage of the kth value of top-k result in current round as the threshold to suppress the nodes whose readings do not belong to the top-k result in next round. Extensive experiments are conducted to evaluate the performance of the proposed CTCRQ approach by using a synthetic data set. The results provide a number of insightful observations and show that CTCRQ substantially outperforms Centralized algorithm, Centralized Optimized algorithm, and CCM algorithm in terms of data transmitted.
Highlights
With the development of microelectronics, embedded computing, and wireless communication technology, sensor hardware technology is improved
(1) initialize (2) ThresholdSuffix = min suffix; (3) end-initialize Main program: (4) Waits and receives the reported values from sensor nodes; (5) for (6) Finds old location in NodesList of StrContour based on suffix and deletes it; (7) Links to the new location in NodesList of other StrContour; (8) end-for (9) Sorts StrContour based on suffixin the VecContour; (10) for (11) Calculates the top-k results; (12) end-for (13) if ⩾ k (14) ThresholdSuffix = TopkSuffix; // The suffix of the kth StrContour
We randomly deployed 300 homogeneous sensor nodes in the 400 ∗ 400 m2 rectangular region and the sink is located at the center
Summary
With the development of microelectronics, embedded computing, and wireless communication technology, sensor hardware technology is improved. There are many continuous contour regions querying schemes for WSNs, including eScan [9], isoline aggregation [10], Iso-Map [11, 12], CCM [13], the literature in [14], and improved Isoline aggregation [15]. These schemes will obtain the overall contour mapping regions Most of these protocols use approximate algorithms to reduce the data transmitted but may lose the rate of precision (accuracy). In other words, these algorithms obtain approximate contour mapping regions. If top-k highest (or lowest) contour regions can satisfy the user’s requirements, it will significantly reduce the data transmitted and save a great number of energy as well as prolong the network lifetime.
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