Taming User-Generated
Content in Mobile Networks
via Drop Zones
Ionut Trestian
Supranamaya Ranjan
Aleksandar Kuzmanovic
Antonio Nucci
Northwestern University
Narus Inc.
http://networks.cs.northwestern.edu
http://www.narus.com
Powerful New Mobile Devices
The iPhone 4 has a 5 MP camera
The HTC Evo has a 8 MP camera
Ionut Trestian
Taming User-Generated Content in Mobile Networks
via Drop Zones
2
Online Social Networks
Social network websites
among the most popular
websites on the Internet
User desire to create virtual
records of their lives using
photos, videos, sounds
Ionut Trestian
Taming User-Generated Content in Mobile Networks
via Drop Zones
3
Current Cellular Networks Cannot Cope
AT&T officials warned that the Internet will “not
be able to cope with the increasing amounts of
video and user-generated content being
uploaded”
Most providers are changing billing plans to
address this problem
The current efforts conducted by some
providers are focused on “educating
customers about what represents a megabyte
of data and improving systems to give them
real-time information about their data usage”
Ionut Trestian
Taming User-Generated Content in Mobile Networks
via Drop Zones
4
Postponed Delivery – Drop Zones
Assume users can tolerate upload delays
(we will show later that this is indeed the case)
Ionut Trestian
Taming User-Generated Content in Mobile Networks
via Drop Zones
5
Drop Zones
Certain locations will have better
connectivity(e.g. 4G)
Client Side - Application running in the
background, users upload content, they are
given the option to delay
Network Side - Device that intercepts delayed
uploads and schedules them over the
backhaul link
Ionut Trestian
Taming User-Generated Content in Mobile Networks
via Drop Zones
6
Research Questions
Where to place Drop Zones such that they absorb the
most content possible?
What is the relationship between postponed
content delivery intervals users can tolerate and
needed infrastructure?
Ionut Trestian
Taming User-Generated Content in Mobile Networks
via Drop Zones
7
Outline
Technical details
Mobile user behavior
Algorithmic details
Evaluation
Further Implications
Ionut Trestian
Taming User-Generated Content in Mobile Networks
via Drop Zones
8
Trace Technical Details
Close to 2 million MMS images, videos etc uploaded by
1,959,037 clients across the United States
during a seven day interval
Ionut Trestian
Taming User-Generated Content in Mobile Networks
via Drop Zones
9
Trace Technical Details
Base
Station 1
1. Inter-session
2.
Intra-session movement
RADA Start
(contains BSID)
Base
Station 2
RADA Stop
Update
(contains BSID)
RADIUS
Server
Therefore we have a snapshot of user presence
across locations (base-stations)
Ionut Trestian
Taming User-Generated Content in Mobile Networks
via Drop Zones
10
Outline
Technical details
Mobile user behavior
Algorithmic details
Evaluation
Further Implications
Ionut Trestian
Taming User-Generated Content in Mobile Networks
via Drop Zones
11
Location Ranking
Comfort zone
3
All users spend most of their time in
their top 3 locations
Ionut Trestian
Taming User-Generated Content in Mobile Networks
via Drop Zones
12
Sending Probability vs. Location Rank
Most of the sending also happens
in their top 3 locations
Ionut Trestian
Taming User-Generated Content in Mobile Networks
via Drop Zones
13
Sent Content over Base-Stations
Certain base-stations popular
but not overly
Ionut Trestian
Taming User-Generated Content in Mobile Networks
via Drop Zones
14
Users Already Delay Uploads
40% of uploads at
least 10 hour old
Ionut Trestian
Taming User-Generated Content in Mobile Networks
via Drop Zones
15
Outline
Technical details
Mobile user behavior
Algorithmic details
Evaluation
Further Implications
Ionut Trestian
Taming User-Generated Content in Mobile Networks
via Drop Zones
16
Drop Zone Algorithmic Details
Placement problem, what base-stations to
collocate Drop Zones at so that we cover the
most content possible
This is an NP hard set covering problem
We adapt a greedy solution – in each step
select the remaining base station that can
cover the most content until all content is
covered
We compare our greedy solution with an ILP
we implemented in cplex
Ionut Trestian
Taming User-Generated Content in Mobile Networks
via Drop Zones
17
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Taming User-Generated
Mobile Networks
’07.
Ionut Trestian
via Drop Zones
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(7)
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xb
18
Outline
Technical details
Mobile user behavior
Algorithmic details
Evaluation
Further Implications
Ionut Trestian
Taming User-Generated Content in Mobile Networks
via Drop Zones
19
Greedy vs. Optimal
Our algorithm stays within
2% of Optimal over all time spans
Ionut Trestian
Taming User-Generated Content in Mobile Networks
via Drop Zones
20
Greedy vs. Simple Heuristic
Our algorithm compared to a
simple popularity heuristic
Ionut Trestian
Taming User-Generated Content in Mobile Networks
via Drop Zones
21
Required Infrastructure
Main metric, savings in infrastructure
Ionut Trestian
Taming User-Generated Content in Mobile Networks
via Drop Zones
22
Average Content Delay
Average delay experienced
a lot lower than set target
Ionut Trestian
Taming User-Generated Content in Mobile Networks
via Drop Zones
23
Average Distance to Drop Zone
Average distance actually grows as
more Drop Zones are added
Ionut Trestian
Taming User-Generated Content in Mobile Networks
via Drop Zones
24
Average Number of Pieces Batched
Batching content
leads to energy savings
Ionut Trestian
Taming User-Generated Content in Mobile Networks
via Drop Zones
25
Outline
Technical details
Mobile user behavior
Algorithmic details
Evaluation
Further Implications
Ionut Trestian
Taming User-Generated Content in Mobile Networks
via Drop Zones
26
Further Implications
Content size keeps increasing, how long until
the next upgrade?
What if we had higher coverage radio
technology?
Ionut Trestian
Taming User-Generated Content in Mobile Networks
via Drop Zones
27
Increase in Content Size
This gives 14 years under LTE
assuming content doubles each year
Ionut Trestian
Taming User-Generated Content in Mobile Networks
via Drop Zones
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Higher Coverage Radio
65% of content 2 km away !
Ionut Trestian
Taming User-Generated Content in Mobile Networks
via Drop Zones
29
Missed Opportunities
More opportunities with more
infrastructure !
Ionut Trestian
Taming User-Generated Content in Mobile Networks
via Drop Zones
30
Conclusions
A Drop Zone architecture reduces infrastructural
deployment requirements
Our approach can effectively tame the
exponentially increasing user-generated content
surge for the next 14 years, under the LTE
technology assumption
Slight increases in radio technology coverage
can bring substantial gains
Ionut Trestian
Taming User-Generated Content in Mobile Networks
via Drop Zones
31