There is recent research attention as well as vendor programs that implement a connection between a car and its owner's smartphone. The problem is that each vehicles are connected to clouds intermittently, only when owners are inside. This paper discusses the new opportunities that arise from having built-in Internet connections in vehicles. Given that power efficiency is not an issue, such vehicles can be useful for cloud services. This paper discusses the practical technology of cloud storage which depends on Reliable Vehicle Groups (RVGs) for enhanced capacity of cloud-to-vehicle (C2V) syncs.

2. .
Basic Idea
• VANETs, Roadside Infra 09 10 07 → Connected Cars 11
• Vehicle-to-Cloud 07 → VehicleGroup-to-Cloud
• Vehicular Cloud (VC) 06 → Cloud Extension by Vehicles
09 "Amendment 6: Wireless Access in Vehicular Environments" IEEE Standard 802.11p (2010)
10 "IEEE Draft Standard for WAVE - Multi-Channel Operation" IEEE P1609.4/D9 (2010)
07 M.Gerla+3 "Internet of Vehicles: From Intelligent Grid to Autonomous Cars and Vehicular Clouds" WSN Magazine (2014)
11 "Connected Vehicle Cloud: Under the Hood" Ericsson Whitepaper (2013)
06 M.Whaiduzzaman+3 "A Survey on Vehicular Cloud Computing" J. of Network and Computer Applications (2014)
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3. .
Basic Idea (2)
• DC (in-city) + VC (out-city) coverage
• Groups of Vehicles as single units -- GroupConnect 01
• 4G+ networks allow for local routing (content delivery, etc.) 04
4 5G
Reliable
Unit (RU)
4 5G End
Users
Data
Center (DC)
01 myself+0 "Wireless User: A Practical Design for Parallel MultiConnect..." 10th MobiQuitous (2013)
04 X.Zhang+1 "LTE-Advanced Air Interface Technology" CRC Press (2013)
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4. .
Vehicular vs Mobile Clouds
1. (practically) infinite battery
◦ mobile clouds mostly care about battery efficiency 05
2. mobility patterns are useful to clouds
◦ parking lots, moving together, etc.
05 N.Fernando+2 "Mobile cloud computing: A survey" Elsevier J. on Future Generation Comp. Sys. (2013)
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5. .
Step 1: (always) Connected Cars
3G
3G
3G
Basic
Components
Conventional
Advanced
11 "Connected Vehicle Cloud: Under the Hood" Ericsson Whitepaper (2013)
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6. .
Step 2: GroupConnect
WiFi
3G
WiFi
3G
3G
01 myself+0 "Wireless User: A Practical Design for Parallel MultiConnect..." 10th MobiQuitous (2013)
02 myself+0 "Opportunistic Multiconnect with P2P WiFi and Cellular Providers" ...4G and Beyond, CRC (2015)
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7. .
Step 3: Logical Grouping
Cars
Rarely
Meet
Meeting Likely
Travel
Together
Park
Together
DTN MANETs
Traditional
SingleConnect
Sensor
Cloud
Storage
Cloud
Information
Support
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8. .
Dealing with 3G/LTE
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9. .
Problem: 3G/LTE Throughput
0 5 10 15 20
Hour of day
0
350
700
1050
1400
Throughput(kbps)
Holiday 1
0 5 10 15 20
Hour of day
0
350
700
1050
1400
Throughput(kbps)
WSP1WSP2WSP3
Holiday 3+
0 5 10 15 20
Hour of day
0
350
700
1050
1400
Throughput(kbps)
Saturday
0 5 10 15 20
Hour of day
0
350
700
1050
1400
Throughput(kbps)
Workday
• 1xLTE + 2x3G providers in
Japan 01
• April - May 2014
• highest throughput is the
new/fresh 3G player
• overall, throughput is low
and unreliable
01 myself+0 "Wireless User: A Practical Design for Parallel MultiConnect..." 10th MobiQuitous (2013)
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10. .
Solution: GroupConnect
• feasible today: WiFi Direct for local connectivity 01 02
4 5G
Reliable
Unit (RU)
4 5G End
Users
Data
Center (DC)
01 myself+0 "Wireless User: A Practical Design for Parallel MultiConnect..." 10th MobiQuitous (2013)
02 myself+0 "Opportunistic Multiconnect with P2P WiFi and Cellular Providers" ...4G and Beyond, CRC (2015)
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11. .
Analysis
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12. .
(1) Maps2Graphs Dataset
• real FamilyMart locations
09 = density distribution
◦ 50x50km around Fukuoka
• bullet size = inverse of
density
◦ people, car fleet, etc.
• total fleet size in Kyushu is
800k 12
◦ 100k in VC fleet
(optimistic)
09 "Amendment 6: Wireless Access in Vehicular Environments" IEEE Standard 802.11p (2010)
12 "Official Statistics on Kyushu Vehicular Fleets" http://wwwtb.mlit.go.jp/kyushu/toukei (2015)
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13. .
(2) Node Density + Classes
0 20 40 60 80 100
Position (%) in list in decreasing order of density
0
0.35
0.7
1.05
1.4
1.75
2.1
2.45
2.8
egnar)0001..1(otdeppamytisnedfogoL
• real density (not inverse)
distribution
• hotspot classes 08: A (few
large items) through D (many large items)
• logic:
◦ only large places: A
◦ more places: AB
◦ ...
◦ all places: ABCD
08 M.Zhanikeev+1 "Popularity-Based Modeling of Flash Events in Synthetic Packet Traces" IEICE・CQ研 (2012)
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14. .
Results
0 50 100 150 200 250 300 350
Coverage rotation (angle)
0.45
0.6
0.75
0.9
1.05
1.2
1.35
1.5
1.65
1.8
Coveragedistance(log)
160
74 25
10
5 54552
2043
49
8
15
29
118
6
2
11
5
2 3
9
Fleetsize#100 Classes#A
0 50 100 150 200 250 300 350
Coverage rotation (angle)
0.3
0.45
0.6
0.75
0.9
1.05
1.2
1.35
1.5
1.65
1.8
Coveragedistance(log)
102 3011 6162
84 111
11814 109
32
17
935335
200 53
28
964 265553
4153
53
20
22
44
3115
12
15
21
9
6 22
4
Fleetsize#100 Classes#AB
0 50 100 150 200 250 300 350
Coverage rotation (angle)
0
0.2
0.4
0.6
0.8
1
1.2
1.4
1.6
1.8
Coveragedistance(log)
14
7640
116
26
621
23
7
22
101
33 84
14
2332 37
37
13
35
96
42
138
113
54 8379 5757
82
557
61
5
696318
255 59
21
10931 162850
4114
75
5
10
41
2441
22
15
39
23
8 2
4
Fleetsize#100 Classes#ABC
0 50 100 150 200 250 300 350
Coverage rotation (angle)
0
0.2
0.4
0.6
0.8
1
1.2
1.4
1.6
1.8
Coveragedistance(log)
13
6842
119
17
1913
41
30
21
61
34 20
73
1232 8
15
26
53
53
31
137
155
115 3314 6020
43
5728
65
20
1413719
231 29
9
11441 116836
3817
55
4
4
36
1721
11
7
21
7
9 7
16
Fleetsize#100 Classes#ABCD
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15. .
That’s all, thank you ...
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