An efficient and privacy-aware meeting scheduling scheme using common computational space

Md Nurul Huda, Eiji Kamioka, Shigeki Yamada

Research output: Contribution to journalArticlepeer-review

3 Citations (Scopus)


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.

Original languageEnglish
Pages (from-to)656-667
Number of pages12
JournalIEICE Transactions on Information and Systems
Issue number3
Publication statusPublished - 2007 Mar
Externally publishedYes


  • Algorithm
  • Constraint
  • Distributed computing
  • Mobile agent
  • Privacy

ASJC Scopus subject areas

  • Software
  • Hardware and Architecture
  • Computer Vision and Pattern Recognition
  • Electrical and Electronic Engineering
  • Artificial Intelligence


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