Citation Export
DC Field | Value | Language |
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dc.contributor.author | Choi, Hong Beom | - |
dc.contributor.author | Ko, Young Bae | - |
dc.contributor.author | Lim, Keun Woo | - |
dc.date.issued | 2018-12-03 | - |
dc.identifier.uri | https://aurora.ajou.ac.kr/handle/2018.oak/36317 | - |
dc.identifier.uri | https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85060487586&origin=inward | - |
dc.description.abstract | In this paper, we study and analyze data fragment placement techniques to exploit their problems and design an energy-aware fragment placement method in Unattended Wireless Sensor Networks (UWSN). In UWSN, the survivability of data is of utmost importance because sensed data cannot be immediately transmitted and must reside in the storage of sensor nodes for extended periods of time. The data, which have delay-tolerant characteristics, can be exploited by attackers that access the storage to erase or steal the data. Even though data fragmentation methods have been designed to solve this problem, these works do not consider a critical issue of where to place data fragments in the sensor network. In this work, we show that basic existing methods of data fragment placement have some problems, especially in terms of energy efficiency and data survival probability. Based on our analysis, we propose a lightweight method that allows us to efficiently select sensor nodes that are used to safely distribute and place data fragments. We show through simulation and preliminary testbed analysis that our proposed method can improve the overall performance of data fragmentation. | - |
dc.description.sponsorship | This research was supported by the MIST(Ministry of Science and ICT), Korea, under the National Program for Excellence in SW supervised by the IITP(Institute for Information communications Technology Promotion)(2015-0-00908) Some of the experiments presented in this work were conducted in the FIT/Iot-Lab testbed [1] * Corresponding Author | - |
dc.language.iso | eng | - |
dc.publisher | Institute of Electrical and Electronics Engineers Inc. | - |
dc.subject.mesh | Critical issues | - |
dc.subject.mesh | Data fragmentation | - |
dc.subject.mesh | Data survivabilities | - |
dc.subject.mesh | Network lifetime | - |
dc.subject.mesh | Placement methods | - |
dc.subject.mesh | Survival probabilities | - |
dc.subject.mesh | Testbed Analysis | - |
dc.subject.mesh | Unattended wireless sensor networks | - |
dc.title | Energy-Aware Distribution of Data Fragments in Unattended Wireless Sensor Networks | - |
dc.type | Conference | - |
dc.citation.conferenceDate | 2018.10.18. ~ 2018.10.19. | - |
dc.citation.conferenceName | 3rd International Conference on Security of Smart Cities, Industrial Control System and Communications, SSIC 2018 | - |
dc.citation.edition | 2018 3rd International Conference on Security of Smart Cities, Industrial Control System and Communications, SSIC 2018 - Proceedings | - |
dc.citation.title | 2018 3rd International Conference on Security of Smart Cities, Industrial Control System and Communications, SSIC 2018 - Proceedings | - |
dc.identifier.bibliographicCitation | 2018 3rd International Conference on Security of Smart Cities, Industrial Control System and Communications, SSIC 2018 - Proceedings | - |
dc.identifier.doi | 10.1109/ssic.2018.8556816 | - |
dc.identifier.scopusid | 2-s2.0-85060487586 | - |
dc.identifier.url | http://ieeexplore.ieee.org/xpl/mostRecentIssue.jsp?punumber=8537784 | - |
dc.subject.keyword | Data fragmentation | - |
dc.subject.keyword | Data survivability | - |
dc.subject.keyword | Network lifetime | - |
dc.subject.keyword | Unattended wireless sensor networks | - |
dc.type.other | Conference Paper | - |
dc.description.isoa | false | - |
dc.subject.subarea | Artificial Intelligence | - |
dc.subject.subarea | Computer Networks and Communications | - |
dc.subject.subarea | Energy Engineering and Power Technology | - |
dc.subject.subarea | Industrial and Manufacturing Engineering | - |
dc.subject.subarea | Safety, Risk, Reliability and Quality | - |
dc.subject.subarea | Control and Optimization | - |
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