Intelligent Routing Algorithm Using Genetic Algorithm (IRAGA)

被引：0

作者：

Abdullah, Nibras ^{[1
,2
]}

Al-wesabi, Ola A. ^{[2
,3
]}

Baklizi, Mahmoud ^{[4
]}

Kadhum, Mohammed M. ^{[1
]}

机构：

[1] Univ Sains Malaysia, Natl Adv Ctr IPv6, Gelugor 11800, Penang, Malaysia

[2] Hodeidah Univ, Fac Comp Sci & Engn, Hodeidah, Yemen

[3] Univ Sains Malaysia, Sch Comp Sci, Gelugor 11800, Penang, Malaysia

[4] World Islamic Sci & Educ Univ, Dept Comp Informat & Network Syst, Amman, Jordan

来源：

RECENT TRENDS IN INFORMATION AND COMMUNICATION TECHNOLOGY | 2018年 / 5卷

关键词：

GA; Crossover; Routing; Multi-constraints; OPTIMIZATION;

D O I：

10.1007/978-3-319-59427-9_28

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

In this study, Intelligent Routing Algorithm using Genetic Algorithm (IRAGA) is proposed to find the feasible path based on multi-constraint by using GA which presented the paths in chromosomes to help the algorithm to find the efficient path among the available paths. The proposed crossover-refining operation keeps the genetic variety of the chromosomes and also improve the ability of searching which obtains the good result and increases the rate of convergence between the chromosomes. The objective of this research work is to decrease the time of route selection and select the most efficient path on the basis of fitness value. IRAGA offers a better solution in a few iteration compared to other genetic algorithm-based routing protocols, such as genetic load balancing routing, adaptive routing method based on GA with QoS, and multi-constraint QoS Unicast Routing using GA, in terms of the time taken to find the feasible path.

引用

页码：255 / 263

页数：9

共 20 条

[1]

Abdullah N., 2011, INT J COMPUT SCI, V9, P136

[2]

Abdullah N., 2013, RFID TECHN APPL RFID, P1, DOI DOI 10.1109/RFID-TA.2013.6694537

[3]

[Anonymous], INT J DIGIT APPL CON

[4]

Barolli L., 2003, Transactions of the Information Processing Society of Japan, V44, P544

[5]

Kumar Jaspal, 2013, International Journal of Computer Network and Information Security, V5, P64, DOI 10.5815/ijcnis.2013.05.08

[6] Multi-constraint Qos Unicast Routing Using Genetic Algorithm (MURUGA) [J].

Leela, R. ;

Thanulekshmi, N. ;

Selvakumar, S. .

APPLIED SOFT COMPUTING, 2011, 11 (02) :1753-1761

[7] Genetic algorithm for shortest driving time in intelligent transportation systems [J].

Lin, Chu-Hsing ;

Yu, Jui-Ling ;

Liu, Jung-Chun ;

Lee, Chia-Jen .

MUE: 2008 INTERNATIONAL CONFERENCE ON MULTIMEDIA AND UBIQUITOUS ENGINEERING, PROCEEDINGS, 2008, :402-+

[8] Genetic Algorithm for Energy-Efficient QoS Multicast Routing [J].

Lu, Ting ;

Zhu, Jie .

IEEE COMMUNICATIONS LETTERS, 2013, 17 (01) :31-34

[9]

Munetomo M., 1998, Transactions of the Information Processing Society of Japan, V39, P219

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

Oda, Tetsuya ;

Elmazi, Donald ;

Barolli, Admir ;

Sakamoto, Shinji ;

Barolli, Leonard ;

Xhafa, Fatos .

SOFT COMPUTING, 2016, 20 (07) :2627-2640

← 1 2 →