Abstract
Owning to the proliferation of cost-effective sensors, there has been an increased growth in a number of applications of wireless sensor networks (WSNs). In addition, the skyline operator as well as its variants such as the dynamic skyline and reverse skyline operator has attracted increasing attention since those are useful for multicriteria decision making applications. Since the energy efficiency is utmost important issue to prolong the network lifetime, in this paper, we proposed efficient algorithms to process a reverse skyline query over a sliding window in WSN environments. We first devise our algorithm for the data stream environments and extend it to WSN environments. To compute the reverse skyline, we partition the data space into several orthants with respect to a query point. And, in each orthant, we compute the reverse skyline independently using two buffers. In our experiment study, we demonstrate that our algorithm is much better than other algorithms.
Highlights
Since being introduced in the database community, the skyline operator [1] and its variants such as dynamic skyline [2] and reverse skyline [3] operators have attracted increasing attention in multicriteria decision making applications such as product recommendations [4, 5], querying wireless sensor networks [6], and graph analysis [7].Given a d-dimensional point set P, a point pi ∈ P dominates another point pj ∈ P if pi is smaller than p2 in at least one dimension and not greater than p2 in all other dimensions
We empirically evaluated the performances of our proposed algorithms in two environments: data stream environments and wireless sensor networks (WSNs) environments
When a point pi becomes a dynamic skyline point, it will stay in o.Buffdsky for a long time and the number of points dynamically dominated by pi increases as w increases
Summary
Since being introduced in the database community, the skyline operator [1] and its variants such as dynamic skyline [2] and reverse skyline [3] operators have attracted increasing attention in multicriteria decision making applications such as product recommendations [4, 5], querying wireless sensor networks [6], and graph analysis [7].Given a d-dimensional point set P, a point pi ∈ P dominates another point pj ∈ P if pi is smaller than p2 in at least one dimension and not greater than p2 in all other dimensions. Papadias et al [2] proposed the dynamic skyline which is a set of points in P not to be dynamically dominated by any other point with respect to (wrt) coordinate-wise distances to a given query point q. Another interesting skyline variant is the reverse skyline operator which returns a set of every point in P, denoted as RSL(q, P), whose dynamic skyline contains a query point q [3]. A wireless sensor network (WSN) is considered as a cost effective platform to monitor environments. Assume a query point q represents the thresholds of a possible fire disaster on different attributes
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