Progressive Skyline Query Processing in Wireless Sensor Networks

Chen, Baichen; Liang, Weifa

doi:10.1109/msn.2009.43

Cited by 15 publications

(14 citation statements)

References 19 publications

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“…It reduces the amount of data transferred and reduces energy consumption, as a consequence, by devising two filter based algorithms: (1) Single point filter based algorithm referred to as a Tuple Filter (TF); and (2) Grid Filter (GF) based algorithm. Chen et al [25] proposed two evaluation algorithms for finding the skyline points on a dataset progressively. The dataset is first partitioned into disjoint subsets.…”

Section: Of 22mentioning

confidence: 99%

Enhanced Distributed Dynamic Skyline Query for Wireless Sensor Networks

Ahmed

Nafi

Gregory

2016

JSAN

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Dynamic skyline query is one of the most popular and significant variants of skyline query in the field of multi-criteria decision-making. However, designing a distributed dynamic skyline query possesses greater challenge, especially for the distributed data centric storage within wireless sensor networks (WSNs). In this paper, a novel Enhanced Distributed Dynamic Skyline (EDDS) approach is proposed and implemented in Disk Based Data Centric Storage (DBDCS) architecture. DBDCS is an adaptation of magnetic disk storage platter consisting tracks and sectors. In DBDCS, the disc track and sector analogy is used to map data locations. A distance based indexing method is used for storing and querying multi-dimensional similar data. EDDS applies a threshold based hierarchical approach, which uses temporal correlation among sectors and sector segments to calculate a dynamic skyline. The efficiency and effectiveness of EDDS has been evaluated in terms of latency, energy consumption and accuracy through a simulation model developed in Castalia.

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Section: Of 22mentioning

confidence: 99%

Enhanced Distributed Dynamic Skyline Query for Wireless Sensor Networks

Ahmed

Nafi

Gregory

2016

JSAN

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“…Supporting skyline query processing in wireless sensor networks (WSNs) has been studied in [7,52]. A wireless sensor network consists of n stationary sensors randomly deployed in a region of interest, and each sensor measures d attribute values.…”

Section: Wireless Sensor Networkmentioning

confidence: 99%

“…In order to improve SWSMA, Chen et al [7] propose an algorithm that proceeds in k iterations. In each iteration, the skyline set of a partition of the data space is computed.…”

Section: Wireless Sensor Networkmentioning

confidence: 99%

A survey of skyline processing in highly distributed environments

2011

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During the last decades, data management and storage have become increasingly distributed. Advanced query operators, such as skyline queries, are necessary in order to help users to handle the huge amount of available data by identifying a set of interesting data objects. Skyline query processing in highly distributed environments poses inherent challenges and demands and requires non-traditional techniques due to the distribution of content and the lack of global knowledge. This paper surveys this interesting and still evolving research area, so that readers can easily obtain an overview of the state-of-the-art. We outline the objectives and the main principles that any distributed skyline approach has to fulfill, leading to useful guidelines for developing algorithms for distributed skyline processing. We review in detail existing approaches that are applicable for highly distributed environments, clarify the assumptions of each approach, and provide a comparative performance analysis. Moreover, we study the skyline variants each approach supports. Our analysis leads to a taxonomy of existing approaches. Finally, we present interesting research topics on distributed skyline computation that have not yet been explored.

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“…In [17] the author proposes an energy efficient optimized routing structure based algorithm, considering optimizing the data communication from the routing layer. In [18] the author proposed a progressive skyline algorithm, making use of geometric spatial decomposition, return the data of subspaces gradually, and broadcasting the subspace skyline results to filter the nodes' unreturned sensor data. But the criterion for dividing the data is too rough, having not fully considering the data's distribution.…”

Section: Related Workmentioning

confidence: 99%

A novel lightweight iteration filtering algorithm research in wireless sensor networks

Xie

Zheng³

2011

2011 6th International Conference on Computer Science &Amp; Education (ICCSE)

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In this paper, we propose a novel skyline query algorithm in wireless sensor networks, according to the data's dominate ability progressively return the sensor data to construct the filter. At the same time, in order to reduce the overhead of the filter construction and broadcasting, we adopt mapping strategy to further eliminate the filtering cost. Theoretical analysis and experimental results all show that it can effectively reduce the communication cost, and eventually prolong the lifetime of the network.

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Progressive Skyline Query Processing in Wireless Sensor Networks

Cited by 15 publications

References 19 publications

Enhanced Distributed Dynamic Skyline Query for Wireless Sensor Networks

Enhanced Distributed Dynamic Skyline Query for Wireless Sensor Networks

A survey of skyline processing in highly distributed environments

A novel lightweight iteration filtering algorithm research in wireless sensor networks

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