PERFORMANCE ANALYSIS OF ROUTING WITH GENETIC ALGORITHM METHOD IN OBS NETWORK

Recent studies show that OBS architecture involves a routing and wavelength assignment (RWA) problem which is NP-complete. A common solution of routing problems in OBS networks by using Open Shortest Path First (OSPF) protocol. OSPF is defacto routing protocol in current interdomain IP networks. Bec...

全面介紹

Saved in:
書目詳細資料
主要作者: SIREGAR (NIM 23206335), SIMON
格式: Theses
語言:Indonesia
在線閱讀:https://digilib.itb.ac.id/gdl/view/13116
標簽: 添加標簽
沒有標簽, 成為第一個標記此記錄!
機構: Institut Teknologi Bandung
語言: Indonesia
id id-itb.:13116
spelling id-itb.:131162017-09-27T15:37:39ZPERFORMANCE ANALYSIS OF ROUTING WITH GENETIC ALGORITHM METHOD IN OBS NETWORK SIREGAR (NIM 23206335), SIMON Indonesia Theses INSTITUT TEKNOLOGI BANDUNG https://digilib.itb.ac.id/gdl/view/13116 Recent studies show that OBS architecture involves a routing and wavelength assignment (RWA) problem which is NP-complete. A common solution of routing problems in OBS networks by using Open Shortest Path First (OSPF) protocol. OSPF is defacto routing protocol in current interdomain IP networks. Because of the RWA problems in OBS network, to find exact solution a set of link-weights that optimizes network performance by using OSPF will be to complex too be solved ini reasonable computation time.<p>In this thesis, we proposed a routing algorithm using genetic algorithm (GA) to solve the RWA problem in OBS networks, which is developed in NS-2. This routing will be used in network simulation and will be compared with the existing routing in OBS networks. The perfomance metrics used in this thesis are end-toend delay, probability of blocking dan throughput. Simulation results show that the proposed routing scheme can reduce probability of blocking about 30 %, increase througput about twice of the existing one and still have an optimum end-to-end delay even with higher value. text
institution Institut Teknologi Bandung
building Institut Teknologi Bandung Library
continent Asia
country Indonesia
Indonesia
content_provider Institut Teknologi Bandung
collection Digital ITB
language Indonesia
description Recent studies show that OBS architecture involves a routing and wavelength assignment (RWA) problem which is NP-complete. A common solution of routing problems in OBS networks by using Open Shortest Path First (OSPF) protocol. OSPF is defacto routing protocol in current interdomain IP networks. Because of the RWA problems in OBS network, to find exact solution a set of link-weights that optimizes network performance by using OSPF will be to complex too be solved ini reasonable computation time.<p>In this thesis, we proposed a routing algorithm using genetic algorithm (GA) to solve the RWA problem in OBS networks, which is developed in NS-2. This routing will be used in network simulation and will be compared with the existing routing in OBS networks. The perfomance metrics used in this thesis are end-toend delay, probability of blocking dan throughput. Simulation results show that the proposed routing scheme can reduce probability of blocking about 30 %, increase througput about twice of the existing one and still have an optimum end-to-end delay even with higher value.
format Theses
author SIREGAR (NIM 23206335), SIMON
spellingShingle SIREGAR (NIM 23206335), SIMON
PERFORMANCE ANALYSIS OF ROUTING WITH GENETIC ALGORITHM METHOD IN OBS NETWORK
author_facet SIREGAR (NIM 23206335), SIMON
author_sort SIREGAR (NIM 23206335), SIMON
title PERFORMANCE ANALYSIS OF ROUTING WITH GENETIC ALGORITHM METHOD IN OBS NETWORK
title_short PERFORMANCE ANALYSIS OF ROUTING WITH GENETIC ALGORITHM METHOD IN OBS NETWORK
title_full PERFORMANCE ANALYSIS OF ROUTING WITH GENETIC ALGORITHM METHOD IN OBS NETWORK
title_fullStr PERFORMANCE ANALYSIS OF ROUTING WITH GENETIC ALGORITHM METHOD IN OBS NETWORK
title_full_unstemmed PERFORMANCE ANALYSIS OF ROUTING WITH GENETIC ALGORITHM METHOD IN OBS NETWORK
title_sort performance analysis of routing with genetic algorithm method in obs network
url https://digilib.itb.ac.id/gdl/view/13116
_version_ 1825533742158970880