Taming User-Generated Content in Mobile Networks
via Drop ZonesIonut TrestianSupranamaya RanjanAleksandar KuzmanovicAntonio Nucci
Northwestern UniversityNarus Inc.
http://networks.cs.northwestern.edu http://www.narus.com
Ionut TrestianTaming User-Generated Content in Mobile Networks
via Drop Zones
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The iPhone 4 has a 5 MP cameraThe HTC Evo has a 8 MP camera
Powerful New Mobile Devices
Ionut TrestianTaming User-Generated Content in Mobile Networks
via Drop Zones
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Social network websites among the most popular websites on the Internet
User desire to create virtual records of their lives using photos, videos, sounds
Online Social Networks
Ionut TrestianTaming User-Generated Content in Mobile Networks
via Drop Zones
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”
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Ionut TrestianTaming User-Generated Content in Mobile Networks
via Drop Zones
Postponed Delivery – Drop Zones
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Assume users can tolerate upload delays (we will show later that this is indeed the case)
Ionut TrestianTaming User-Generated Content in Mobile Networks
via Drop Zones
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
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Ionut TrestianTaming User-Generated Content in Mobile Networks
via Drop Zones
Research Questions
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Where to place Drop Zones such that they absorb the most content possible?
What is the relationship between postponedcontent delivery intervals users can tolerate and
needed infrastructure?
Ionut TrestianTaming User-Generated Content in Mobile Networks
via Drop Zones
Outline
Technical details
Mobile user behavior
Algorithmic details
Evaluation
Further Implications
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Ionut TrestianTaming User-Generated Content in Mobile Networks
via Drop Zones
Trace Technical Details
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Close to 2 million MMS images, videos etc uploaded by 1,959,037 clients across the United States
during a seven day interval
Ionut TrestianTaming User-Generated Content in Mobile Networks
via Drop Zones
Trace Technical Details
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1. Intra-session movement
RADA Start(contains BSID)
RADA Update(contains BSID)
2. Inter-session movement
RADA Stop(contains BSID)
RADIUSServer
BaseStation 1
BaseStation 2
Therefore we have a snapshot of user presence across locations (base-stations)
Ionut TrestianTaming User-Generated Content in Mobile Networks
via Drop Zones
Outline
Technical details
Mobile user behavior
Algorithmic details
Evaluation
Further Implications
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Ionut TrestianTaming User-Generated Content in Mobile Networks
via Drop Zones
Location Ranking
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All users spend most of their time in their top 3 locations
Comfort zone
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Ionut TrestianTaming User-Generated Content in Mobile Networks
via Drop Zones
Sending Probability vs. Location Rank
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Most of the sending also happens in their top 3 locations
Ionut TrestianTaming User-Generated Content in Mobile Networks
via Drop Zones
Sent Content over Base-Stations
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Certain base-stations popular but not overly
Ionut TrestianTaming User-Generated Content in Mobile Networks
via Drop Zones
Users Already Delay Uploads
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40% of uploads at least 10 hour old
Ionut TrestianTaming User-Generated Content in Mobile Networks
via Drop Zones
Outline
Technical details
Mobile user behavior
Algorithmic details
Evaluation
Further Implications
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Ionut TrestianTaming User-Generated Content in Mobile Networks
via Drop Zones
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
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Ionut TrestianTaming User-Generated Content in Mobile Networks
via Drop Zones
Drop Zone ILP Formulation
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Ionut TrestianTaming User-Generated Content in Mobile Networks
via Drop Zones
Outline
Technical details
Mobile user behavior
Algorithmic details
Evaluation
Further Implications
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Ionut TrestianTaming User-Generated Content in Mobile Networks
via Drop Zones
Greedy vs. Optimal
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Our algorithm stays within 2% of Optimal over all time spans
Ionut TrestianTaming User-Generated Content in Mobile Networks
via Drop Zones
Greedy vs. Simple Heuristic
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Our algorithm compared to a simple popularity heuristic
Ionut TrestianTaming User-Generated Content in Mobile Networks
via Drop Zones
Required Infrastructure
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Main metric, savings in infrastructure
Ionut TrestianTaming User-Generated Content in Mobile Networks
via Drop Zones
Average Content Delay
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Average delay experienced a lot lower than set target
Ionut TrestianTaming User-Generated Content in Mobile Networks
via Drop Zones
Average Distance to Drop Zone
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Average distance actually grows as more Drop Zones are added
Ionut TrestianTaming User-Generated Content in Mobile Networks
via Drop Zones
Average Number of Pieces Batched
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Batching content leads to energy savings
Ionut TrestianTaming User-Generated Content in Mobile Networks
via Drop Zones
Outline
Technical details
Mobile user behavior
Algorithmic details
Evaluation
Further Implications
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Ionut TrestianTaming User-Generated Content in Mobile Networks
via Drop Zones
Further Implications
Content size keeps increasing, how long until the next upgrade?
What if we had higher coverage radio technology?
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Ionut TrestianTaming User-Generated Content in Mobile Networks
via Drop Zones
Increase in Content Size
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This gives 14 years under LTE assuming content doubles each year
Ionut TrestianTaming User-Generated Content in Mobile Networks
via Drop Zones
Higher Coverage Radio
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65% of content 2 km away !
Ionut TrestianTaming User-Generated Content in Mobile Networks
via Drop Zones
Missed Opportunities
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More opportunities with more infrastructure !
Ionut TrestianTaming User-Generated Content in Mobile Networks
via Drop Zones
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
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