A genetic algorithm-based system for wireless mesh networks: analysis of system data considering different routing protocols and architectures

被引:42
作者
Oda, Tetsuya [1 ]
Elmazi, Donald [2 ]
Barolli, Admir [3 ]
Sakamoto, Shinji [1 ]
Barolli, Leonard [4 ]
Xhafa, Fatos [5 ]
机构
[1] Fukuoka Inst Technol, Grad Sch Engn, Higashi Ku, 3-30-1 Wajiro Higashi, Fukuoka 8110295, Japan
[2] Polytech Univ Tirana, Fac Informat Technol, Bul Deshmoret & Kombit,Mother Theresa Sq 4, Tirana, Albania
[3] DI Univ Salerno, I-84084 Fisciano, Italy
[4] Fukuoka Inst Technol, Dept Informat & Commun Engn, Higashi Ku, 3-30-1 Wajiro Higashi, Fukuoka 8110295, Japan
[5] Tech Univ Catalonia, Dept Languages & Informat Syst, C Jordi Girona 1-3, Barcelona 08034, Spain
关键词
Wireless mesh networks; Genetic algorithms; ns-3; OLSR; HWMP; Giant component; User coverage;
D O I
10.1007/s00500-015-1663-z
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
Wireless mesh networks (WMNs) are attracting a lot of attention from wireless network researchers. Node placement problems have been investigated for a long time in the optimization field due to numerous applications in location science. In our previous work, we evaluated WMN-GA system which is based on genetic algorithms (GAs) to find an optimal location assignment for mesh routers. In this paper, we evaluate the performance of four different distributions of mesh clients for two WMN architectures considering throughput, delay and energy metrics. For simulations, we used ns-3, optimized link state routing (OLSR) and hybrid wireless mesh protocols (HWMP). We compare the performance for Normal, Uniform, Exponential and Weibull distributions of mesh clients by sending multiple constant bit rate flows in the network. The simulation results show that for HWM protocol the throughput of Uniform distribution is higher than other distributions. However, for OLSR protocol, the throughput of Exponential distribution is better than other distributions. For both protocols, the delay and remaining energy are better for Weibull distribution.
引用
收藏
页码:2627 / 2640
页数:14
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