IEICE TRANSACTIONS on Information
An Efficient and Privacy-Aware Meeting Scheduling Scheme Using Common Computational Space
Summary :
Privacy is increasingly viewed as a key concern in multi-agent based algorithms for Distributed Constraint Satisfaction Problems (DCSP) such as the Meeting Scheduling (MS) problem. Many algorithms aim for a global objective function and as a result, incur performance penalties in computational complexity and personal privacy. This paper describes a mobile agent-based scheduling scheme called Efficient and Privacy-aware Meeting Scheduling (EPMS), which results in a tradeoff among complexity, privacy, and global utility. It also introduces a privacy loss model for collaborative computation, multiple criteria for evaluating privacy in the MS problem, and a privacy measurement metric called the Min privacy metric. We have utilized a common computational space in EPMS for reducing the complexity and the privacy loss in the MS problem. The analytical results show that EPMS has a polynomial time computational complexity. In addition, simulation results show that the obtained global utility for scheduling multiple meetings with EPMS is close to the optimal level and the resulting privacy loss is less than for those in existing algorithms.
- Publication
- IEICE TRANSACTIONS on Information Vol.E90-D No.3 pp.656-667
- Publication Date
- 2007/03/01
- Publicized
- Online ISSN
- 1745-1361
- DOI
- 10.1093/ietisy/e90-d.3.656
- Type of Manuscript
- PAPER
- Category
- Distributed Cooperation and Agents
Authors
Keyword
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Md. Nurul HUDA, Eiji KAMIOKA, Shigeki YAMADA, "An Efficient and Privacy-Aware Meeting Scheduling Scheme Using Common Computational Space" in IEICE TRANSACTIONS on Information,
vol. E90-D, no. 3, pp. 656-667, March 2007, doi: 10.1093/ietisy/e90-d.3.656.
Abstract: Privacy is increasingly viewed as a key concern in multi-agent based algorithms for Distributed Constraint Satisfaction Problems (DCSP) such as the Meeting Scheduling (MS) problem. Many algorithms aim for a global objective function and as a result, incur performance penalties in computational complexity and personal privacy. This paper describes a mobile agent-based scheduling scheme called Efficient and Privacy-aware Meeting Scheduling (EPMS), which results in a tradeoff among complexity, privacy, and global utility. It also introduces a privacy loss model for collaborative computation, multiple criteria for evaluating privacy in the MS problem, and a privacy measurement metric called the Min privacy metric. We have utilized a common computational space in EPMS for reducing the complexity and the privacy loss in the MS problem. The analytical results show that EPMS has a polynomial time computational complexity. In addition, simulation results show that the obtained global utility for scheduling multiple meetings with EPMS is close to the optimal level and the resulting privacy loss is less than for those in existing algorithms.
URL: https://global.ieice.org/en_transactions/information/10.1093/ietisy/e90-d.3.656/_p
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@ARTICLE{e90-d_3_656,
author={Md. Nurul HUDA, Eiji KAMIOKA, Shigeki YAMADA, },
journal={IEICE TRANSACTIONS on Information},
title={An Efficient and Privacy-Aware Meeting Scheduling Scheme Using Common Computational Space},
year={2007},
volume={E90-D},
number={3},
pages={656-667},
abstract={Privacy is increasingly viewed as a key concern in multi-agent based algorithms for Distributed Constraint Satisfaction Problems (DCSP) such as the Meeting Scheduling (MS) problem. Many algorithms aim for a global objective function and as a result, incur performance penalties in computational complexity and personal privacy. This paper describes a mobile agent-based scheduling scheme called Efficient and Privacy-aware Meeting Scheduling (EPMS), which results in a tradeoff among complexity, privacy, and global utility. It also introduces a privacy loss model for collaborative computation, multiple criteria for evaluating privacy in the MS problem, and a privacy measurement metric called the Min privacy metric. We have utilized a common computational space in EPMS for reducing the complexity and the privacy loss in the MS problem. The analytical results show that EPMS has a polynomial time computational complexity. In addition, simulation results show that the obtained global utility for scheduling multiple meetings with EPMS is close to the optimal level and the resulting privacy loss is less than for those in existing algorithms.},
keywords={},
doi={10.1093/ietisy/e90-d.3.656},
ISSN={1745-1361},
month={March},}
Copy
TY - JOUR
TI - An Efficient and Privacy-Aware Meeting Scheduling Scheme Using Common Computational Space
T2 - IEICE TRANSACTIONS on Information
SP - 656
EP - 667
AU - Md. Nurul HUDA
AU - Eiji KAMIOKA
AU - Shigeki YAMADA
PY - 2007
DO - 10.1093/ietisy/e90-d.3.656
JO - IEICE TRANSACTIONS on Information
SN - 1745-1361
VL - E90-D
IS - 3
JA - IEICE TRANSACTIONS on Information
Y1 - March 2007
AB - Privacy is increasingly viewed as a key concern in multi-agent based algorithms for Distributed Constraint Satisfaction Problems (DCSP) such as the Meeting Scheduling (MS) problem. Many algorithms aim for a global objective function and as a result, incur performance penalties in computational complexity and personal privacy. This paper describes a mobile agent-based scheduling scheme called Efficient and Privacy-aware Meeting Scheduling (EPMS), which results in a tradeoff among complexity, privacy, and global utility. It also introduces a privacy loss model for collaborative computation, multiple criteria for evaluating privacy in the MS problem, and a privacy measurement metric called the Min privacy metric. We have utilized a common computational space in EPMS for reducing the complexity and the privacy loss in the MS problem. The analytical results show that EPMS has a polynomial time computational complexity. In addition, simulation results show that the obtained global utility for scheduling multiple meetings with EPMS is close to the optimal level and the resulting privacy loss is less than for those in existing algorithms.
ER -
English
