Evaluating distributed IoT databases for edge/cloud platforms using the analytic hierarchy process
Decision-making is not a trivial process. It involves studying and analyzing different alternatives. In addition, it requires defining criteria for evaluating the alternatives. A problem arises when evaluating criteria that conflict or when dealing with qualitative criteria. The analytic hierarchy p...
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| Published in: | Journal of parallel and distributed computing Vol. 124; pp. 41 - 46 |
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| Format: | Journal Article |
| Language: | English |
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Elsevier Inc
01.02.2019
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| ISSN: | 0743-7315, 1096-0848 |
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| Abstract | Decision-making is not a trivial process. It involves studying and analyzing different alternatives. In addition, it requires defining criteria for evaluating the alternatives. A problem arises when evaluating criteria that conflict or when dealing with qualitative criteria. The analytic hierarchy process (AHP) is a multi-criteria decision tool that simplifies the decision-making process. It can evaluate both qualitative and quantitative criteria. Moreover, AHP justifies the final decision by providing the mathematical reasoning behind the judgment. The aim of this research is to evaluate available Internet of Things (IoT) databases in an edge/cloud platform by applying AHP and to suggest a suitable approach for developing a database application. In this study, four alternative database development tools are evaluated: DaDaBIK, DataFlex, Oracle Application Express, and FileMaker. We define our criteria, explain why they are selected, and assign each a weight based on its importance. We then evaluate the candidates using the weighted criteria. FileMaker is found to be the best choice because it offers the best usability, portability, and supportability for IoT scenarios.
•Evaluation of distributed IoT database for Edge/Cloud Platform.•Used the Analytic Hierarchy Process as simulation and emulation platform IoT.•Performance evaluation of AHP for distributed IoT database in Edge/Cloud. |
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| AbstractList | Decision-making is not a trivial process. It involves studying and analyzing different alternatives. In addition, it requires defining criteria for evaluating the alternatives. A problem arises when evaluating criteria that conflict or when dealing with qualitative criteria. The analytic hierarchy process (AHP) is a multi-criteria decision tool that simplifies the decision-making process. It can evaluate both qualitative and quantitative criteria. Moreover, AHP justifies the final decision by providing the mathematical reasoning behind the judgment. The aim of this research is to evaluate available Internet of Things (IoT) databases in an edge/cloud platform by applying AHP and to suggest a suitable approach for developing a database application. In this study, four alternative database development tools are evaluated: DaDaBIK, DataFlex, Oracle Application Express, and FileMaker. We define our criteria, explain why they are selected, and assign each a weight based on its importance. We then evaluate the candidates using the weighted criteria. FileMaker is found to be the best choice because it offers the best usability, portability, and supportability for IoT scenarios.
•Evaluation of distributed IoT database for Edge/Cloud Platform.•Used the Analytic Hierarchy Process as simulation and emulation platform IoT.•Performance evaluation of AHP for distributed IoT database in Edge/Cloud. |
| Author | Alelaiwi, Abdulhameed |
| Author_xml | – sequence: 1 givenname: Abdulhameed surname: Alelaiwi fullname: Alelaiwi, Abdulhameed email: aalelaiwi@Ksu.edu.sa organization: Department of Software Engineering, College of Computer & Information Sciences, King Saud University, Riyadh, Saudi Arabia |
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| Cites_doi | 10.1016/j.chb.2015.02.002 10.1016/j.future.2018.07.050 10.1007/s41872-017-0004-x 10.1109/ACCESS.2017.2778504 10.1016/j.future.2018.05.056 10.1109/JIOT.2017.2683200 10.4103/0256-4602.55275 10.1109/JIOT.2017.2767608 10.3390/s17092014 10.1016/0022-2496(77)90033-5 |
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| Title | Evaluating distributed IoT databases for edge/cloud platforms using the analytic hierarchy process |
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