| Project/Area Number |
12680428
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| Research Category |
Grant-in-Aid for Scientific Research (C)
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| Allocation Type | Single-year Grants |
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| Section | 一般 |
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| Research Field |
社会システム工学
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| Research Institution | The University of Electro-Communications (2001)
Yamagata University (2000) |
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Principal Investigator |
YAMADA Takako The Univ. of Electro-Communications, Graduate School of Information Systems, Associate Professor, 大学院・情報システム学研究科, 助教授 (80272053)
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| Co-Investigator(Kenkyū-buntansha) |
BAROLLI Leonard Yamagata University, Dept. of Public policy and Social Studies, Assistant Professor, 人文学部, 助手 (40312722)
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| Project Period (FY) |
2000 – 2001
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| Project Status |
Completed (Fiscal Year 2001)
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| Budget Amount *help |
¥4,000,000 (Direct Cost: ¥4,000,000)
Fiscal Year 2001: ¥1,600,000 (Direct Cost: ¥1,600,000)
Fiscal Year 2000: ¥2,400,000 (Direct Cost: ¥2,400,000)
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| Keywords | Mobile Communication network / Base Station / Simulation / Traffic / Fuzzy / routing / Admission Control / Artificial Intelligence / トフヒック / 制御 |
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| Research Abstract |
In our research project, we treated two kinds of network. One is the high-speed transmission of wired networks and the other is the low bandwidth of mobile wireless networks both of which need flexible traffic control mechanism. To cope with control problems of high-speed and mobile networks, the network traffic methods must be adaptive, flexible, and intelligent for efficient network management. Therefore, use of intelligent methods can be a solution for the traffic control of telecommunication networks. At first, we introduce an integrated fuzzy policing-routing mechanism for high-speed networks. It covers the source and network models ; fuzzy policing mechanism ; tagging switchfetation scheme ; direct path fuzzy controller ; fuzzy routing mechanism ; and simulation results. We proposed a fuzzy admission control scheme to discuss the previous work ; proposed scheme ; and simulation results. An intelligent call admission control and routing framework for large scale networks based on
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cooperative agents as also proposed including distributed artificial intelligence approach. We proposed distributed network architecture to explanate different agents. As an another side of our approach , we introduce a simulation system for base station allocation in mobile communication networks. We give consideration for simulation. We show a simulation flowchart ; simulation parameters ; base station allocation procedure ; and simulation results. In this approach we propose a base station allocation policy for IMT-2000 mobile phone systems. We consider a situation where a region is to be covered by two different kinds of cells, macro cells and micro cells, each of which has its own base station at the center. We compare several variants of allocation policies through simulation experiments and show that a better allocation is obtained by a simple algorithm stated in the paper. Further, we show that the use of two kinds of cells/base stations is effective to get more flexible allocation for time variations of user locations. Less
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