Enhanced Distributed Dynamic Skyline Query for Wireless Sensor Networks
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 ne...
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doaj-356b1e6b8df14878bbc0da526820d7702020-11-24T22:21:38ZengMDPI AGJournal of Sensor and Actuator Networks2224-27082016-02-0151210.3390/jsan5010002jsan5010002Enhanced Distributed Dynamic Skyline Query for Wireless Sensor NetworksKhandakar Ahmed0Nazmus S. Nafi1Mark A. Gregory2School of Electrical and Computer Engineering, RMIT University, Melbourne, VIC 3000, AustraliaSchool of Electrical and Computer Engineering, RMIT University, Melbourne, VIC 3000, AustraliaSchool of Electrical and Computer Engineering, RMIT University, Melbourne, VIC 3000, AustraliaDynamic 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.http://www.mdpi.com/2224-2708/5/1/2wireless sensor networksdistributed data centric storageskyline querysector based distance routinguniform distributionlower bound distributionand upper bound distribution |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Khandakar Ahmed Nazmus S. Nafi Mark A. Gregory |
spellingShingle |
Khandakar Ahmed Nazmus S. Nafi Mark A. Gregory Enhanced Distributed Dynamic Skyline Query for Wireless Sensor Networks Journal of Sensor and Actuator Networks wireless sensor networks distributed data centric storage skyline query sector based distance routing uniform distribution lower bound distribution and upper bound distribution |
author_facet |
Khandakar Ahmed Nazmus S. Nafi Mark A. Gregory |
author_sort |
Khandakar Ahmed |
title |
Enhanced Distributed Dynamic Skyline Query for Wireless Sensor Networks |
title_short |
Enhanced Distributed Dynamic Skyline Query for Wireless Sensor Networks |
title_full |
Enhanced Distributed Dynamic Skyline Query for Wireless Sensor Networks |
title_fullStr |
Enhanced Distributed Dynamic Skyline Query for Wireless Sensor Networks |
title_full_unstemmed |
Enhanced Distributed Dynamic Skyline Query for Wireless Sensor Networks |
title_sort |
enhanced distributed dynamic skyline query for wireless sensor networks |
publisher |
MDPI AG |
series |
Journal of Sensor and Actuator Networks |
issn |
2224-2708 |
publishDate |
2016-02-01 |
description |
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. |
topic |
wireless sensor networks distributed data centric storage skyline query sector based distance routing uniform distribution lower bound distribution and upper bound distribution |
url |
http://www.mdpi.com/2224-2708/5/1/2 |
work_keys_str_mv |
AT khandakarahmed enhanceddistributeddynamicskylinequeryforwirelesssensornetworks AT nazmussnafi enhanceddistributeddynamicskylinequeryforwirelesssensornetworks AT markagregory enhanceddistributeddynamicskylinequeryforwirelesssensornetworks |
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1725770367161597952 |