Upgrade to Pro
— share decks privately, control downloads, hide ads and more …
Speaker Deck
Features
Speaker Deck
PRO
Sign in
Sign up for free
Search
Search
VANET Simulation of AP assistance
Search
Andro Chen Chun-An
June 13, 2011
Research
0
46
VANET Simulation of AP assistance
2011-06-13 VANET Simulation of AP assistance
Final Project of 無線網路導論, 魏宏宇副教授 @ NTUEE
Andro Chen Chun-An
June 13, 2011
Tweet
Share
More Decks by Andro Chen Chun-An
See All by Andro Chen Chun-An
入坑滑雪自由行: 新手入門懶人包 - 雪場,費用,行程,行李,訓練 全攻略
androchentw
0
28
2021-02-17_splunk_cafe.pdf
androchentw
0
83
When Andro Meets Android - Android Taipei
androchentw
0
200
What I've Learned From Startups
androchentw
0
110
Baidu SEO II
androchentw
1
90
Basic HTML + SEO - A Simple Tutorial @5945
androchentw
0
55
Baidu SEO - A Practical Guide
androchentw
0
66
Privacy-Preserving Data Mining and Collusion Resistance
androchentw
0
53
啡˙聞
androchentw
1
62
Other Decks in Research
See All in Research
社内データ分析AIエージェントを できるだけ使いやすくする工夫
fufufukakaka
1
960
それ、チームの改善になってますか?ー「チームとは?」から始めた組織の実験ー
hirakawa51
0
850
An Open and Reproducible Deep Research Agent for Long-Form Question Answering
ikuyamada
0
340
20年前に50代だった人たちの今
hysmrk
0
160
Grounding Text Complexity Control in Defined Linguistic Difficulty [Keynote@*SEM2025]
yukiar
0
120
【SIGGRAPH Asia 2025】Lo-Fi Photograph with Lo-Fi Communication
toremolo72
0
130
2026年1月の生成AI領域の重要リリース&トピック解説
kajikent
0
780
AIスパコン「さくらONE」の オブザーバビリティ / Observability for AI Supercomputer SAKURAONE
yuukit
2
1.2k
都市交通マスタープランとその後への期待@熊本商工会議所・熊本経済同友会
trafficbrain
0
160
"主観で終わらせない"定性データ活用 ― プロダクトディスカバリーを加速させるインサイトマネジメント / Utilizing qualitative data that "doesn't end with subjectivity" - Insight management that accelerates product discovery
kaminashi
16
22k
Community Driveプロジェクト(CDPJ)の中間報告
smartfukushilab1
0
200
姫路市 -都市OSの「再実装」-
hopin
0
1.7k
Featured
See All Featured
What the history of the web can teach us about the future of AI
inesmontani
PRO
1
460
GitHub's CSS Performance
jonrohan
1032
470k
Test your architecture with Archunit
thirion
1
2.2k
HU Berlin: Industrial-Strength Natural Language Processing with spaCy and Prodigy
inesmontani
PRO
0
250
ピンチをチャンスに:未来をつくるプロダクトロードマップ #pmconf2020
aki_iinuma
128
55k
Building Applications with DynamoDB
mza
96
6.9k
Into the Great Unknown - MozCon
thekraken
40
2.3k
Mind Mapping
helmedeiros
PRO
1
110
Leveraging Curiosity to Care for An Aging Population
cassininazir
1
190
Learning to Love Humans: Emotional Interface Design
aarron
275
41k
個人開発の失敗を避けるイケてる考え方 / tips for indie hackers
panda_program
122
21k
Leadership Guide Workshop - DevTernity 2021
reverentgeek
1
230
Transcript
VANET Simulation of AP Assistance AP協助下的車用無線網路模擬 B97901015 陳俊安 B97901087 林蓉瑄
B97901098 周伯威
Introduction • VANET module: MOVE – MObility model generator for
VEhicular networks • AODV+ – use AODV for simulations of wired-cum-wireless scenarios
Motive • Improve VANET performance – Using APs in the
city – Fast & reliable Ethernet • But “where are you?” – If we don’t use Mobile IP… • Implement AODV+ on both wired and wireless nodes
Experiment Design • Car numbers – 9, 26, 32, 44,
55, 65 • AP numbers – 0, 4, 9(3x3), 16, 25, …, 100 • Random traffic – Using MOVE
Modification • AODV+ does not work – wired <--> wireless
– wireless -> wired -> wireless ? • Alternative – motionless cars act as APs
Performance • Success ratio • Pong RTT – Average –
Standard deviation
• In XGraph Success ratio
• In XGraph Average
• In XGraph Standard Deviation
Graph analysis Cars # 9 26 32 44 55 65
Best AP # 9 16 16 9 9 9 Start to drop 81 36 49 36 36 36 Best AP#/Car# 1.00 0.62 0.50 0.20 0.16 0.14 Success ratio 83.26 94.78 90.68 92.68 92.93 96.18 Best = highest success ra.o
Conclusion • Too much water drowned the miller – When
mobility and density is low, AP counts • Trade-off – High transmission rate – Extra routing table overhead
Q & A
Thank you