### Abstract

Recently there has been some interest in extending ATM (Asynchronous Transfer Mode) technology to the wireless environment. The motivation behind this extension (termed wireless ATM) includes the desire for seamless interconnection of wireless and ATM networks, and the need to support emerging mobile multimedia services. In this paper, we investigate the problem of optimum assignment of cells in PCS (Personal Communication Service) to switches in a wireless ATM network. Given cells and switches in an ATM network (whose locations are fixed and known), the problem is assigning cells to switches such that the cost can be minimized. The cost has two components, one is the cost of handoffs that involve two switches, and the other is the cost of cabling. This problem is modeled as a complex integer programming problem, and finding an optimal solution to this problem is NP-complete. Two stochastic search methods. SGA (Simple Genetic Algorithm) and EGA (Extended Genetic Algorithm), based on a genetic approach, are proposed to solve this problem. Simulation results show that genetic algorithms are robust for this problem.

Original language | English |
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Pages (from-to) | 151-162 |

Number of pages | 12 |

Journal | Proceedings of the National Science Council, Republic of China, Part A: Physical Science and Engineering |

Volume | 25 |

Issue number | 3 |

Publication status | Published - 2001 May 1 |

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### All Science Journal Classification (ASJC) codes

- Engineering(all)

### Cite this

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*Proceedings of the National Science Council, Republic of China, Part A: Physical Science and Engineering*, vol. 25, no. 3, pp. 151-162.

**Genetic algorithms for optimal design of the two-Level wireless ATM network.** / Din, Der-Rong; Tseng, S. S.

Research output: Contribution to journal › Article

TY - JOUR

T1 - Genetic algorithms for optimal design of the two-Level wireless ATM network

AU - Din, Der-Rong

AU - Tseng, S. S.

PY - 2001/5/1

Y1 - 2001/5/1

N2 - Recently there has been some interest in extending ATM (Asynchronous Transfer Mode) technology to the wireless environment. The motivation behind this extension (termed wireless ATM) includes the desire for seamless interconnection of wireless and ATM networks, and the need to support emerging mobile multimedia services. In this paper, we investigate the problem of optimum assignment of cells in PCS (Personal Communication Service) to switches in a wireless ATM network. Given cells and switches in an ATM network (whose locations are fixed and known), the problem is assigning cells to switches such that the cost can be minimized. The cost has two components, one is the cost of handoffs that involve two switches, and the other is the cost of cabling. This problem is modeled as a complex integer programming problem, and finding an optimal solution to this problem is NP-complete. Two stochastic search methods. SGA (Simple Genetic Algorithm) and EGA (Extended Genetic Algorithm), based on a genetic approach, are proposed to solve this problem. Simulation results show that genetic algorithms are robust for this problem.

AB - Recently there has been some interest in extending ATM (Asynchronous Transfer Mode) technology to the wireless environment. The motivation behind this extension (termed wireless ATM) includes the desire for seamless interconnection of wireless and ATM networks, and the need to support emerging mobile multimedia services. In this paper, we investigate the problem of optimum assignment of cells in PCS (Personal Communication Service) to switches in a wireless ATM network. Given cells and switches in an ATM network (whose locations are fixed and known), the problem is assigning cells to switches such that the cost can be minimized. The cost has two components, one is the cost of handoffs that involve two switches, and the other is the cost of cabling. This problem is modeled as a complex integer programming problem, and finding an optimal solution to this problem is NP-complete. Two stochastic search methods. SGA (Simple Genetic Algorithm) and EGA (Extended Genetic Algorithm), based on a genetic approach, are proposed to solve this problem. Simulation results show that genetic algorithms are robust for this problem.

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M3 - Article

AN - SCOPUS:0035334968

VL - 25

SP - 151

EP - 162

JO - Proceedings of the National Science Council, Republic of China, Part A: Physical Science and Engineering

JF - Proceedings of the National Science Council, Republic of China, Part A: Physical Science and Engineering

SN - 0255-6588

IS - 3

ER -