distribute what you can, centralize what you must! narseo vallina-rodriguez supervisor: jon...
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Distribute what you can, centralize what you must!Narseo Vallina-Rodriguez
Supervisor: Jon Crowcroft
Qualcomm – Cambridge22nd May 2013
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Motivation
The web is becoming mobile
Apps rely on multiple online/cloud services (mobile mashup): CDNs (Akamai) Cloud services (Amazon WS) Authentication APIs (Oauth) Assisting sensors (A-GPS) Advertisement (AdMob, Burstly, Millennial Media, …) Push notifications (Google’s GCM) NAT punching for P2P (Skype)
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Research question
How do mobile apps’ cloud dependency impact on cellular network and battery life of mobile handsets?
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2012-2013 outcome When Assistance becomes Dependence: characterizing the costs
and inefficiencies of A-GPS. Vallina-Rodriguez, Finamore, Grunenberger, Papagiannaki and Crowcroft. ACM SIGMOBILE MC2R (under review)
Breaking for Commercials: Characterizing Mobile Advertising. Vallina-Rodriguez, Finamore, Shah, Grunenberger, Haddadi, Papagiannaki and Crowcroft. In ACM Internet Measurement Conference 2012(IMC'12)
Energy Management Techniques in Modern Mobile Devices. Vallina-Rodriguez and Crowcroft. In IEEE Communications Tutorials and Surveys, 2012.
When David can help Goliath: the case for cellular augmentation of wired networks. Vallina-Rodriguez, Erramilli, Grunenberger, Gyarmati, Laoutaris, Stanojevic, Papagiannaki, In ACM HotNets'12
Signposts: End-to-End Networking in a World of Middleboxes. Aucinas, Chaudhry, Crowcroft, Probst Eide, Hand, Madhavapeddy, Moore, Mortier, Rotsos and Vallina-Rodriguez. In ACM SIGCOMM 2012. DEMO
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Take away: moving to the edge!
1. Mobile applications may abuse cellular networks: they cause network (signaling/channels/operational) and energy costs!
2. Fetching content in a centralized fashion is not the only way
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Distribute as much as you can!
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Flashlinq/LTE-direct
P2P wireless technology Perfect candidate for transparent communication in the edge!
Peer discovery (energy efficient) Expression-based discovery (service) Always-on background service with low duty-cycle Similar to powering up a paging channel every X seconds
Current prototype performance: Low-latency (<10 ms) Good throughput (~ 20 Mbps) Discovery (1~2 seconds)
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… but what can be distributed?
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1. Localized data
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Use case 1: Localized data
A large fraction of mobile data is local Weather Notifications Ads
Apps use cellular networks and push notifications to fetch this content High latency No delivery guarantees
[Cellular data network infrastructure characterization and implication on mobile content placement, Xu et al. SIGMETRICS’2011]
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NODE B
RNC SGSN GGSN
SERVER
(UK)
INTERNET
GoogleGCM (Ir)
Use case 1: AirportUse case 1: Airport notifications
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Use case 1: Airport notifications
TCP/IP Push notification model is broken for local data: Frequent RNC promotions (some caused by TCP
Heartbeats) Waste of energy, middleboxes/proxies memory and radio
channels (+200K users/day, a lot of signaling traffic!)
Traffic Pattern Heathrow App For Android (Flight Update)
EnergySignaling
Spectrum (HSPA)
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NODE B
RNC SGSN GGSN
SERVER
(UK)
INTERNET
Flashlinq
GoogleGCM (Ir)
Use case 1: AirportUse case 1: Airport notificationsPubSub modelLow latency
No net overheadEnergy efficientNo Middleboxes!
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2. Collaborative sensing
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Use case 2: Collaborative A-GPS
Assisting data (time, ephemeris, almanac, coarse location) downloaded from network: Reduces TTFF (usability) Temporal validity up to 2 weeks for ephemeris
Problem: use of cellular network may impair performance and increase energy costs!
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Use case 2: Collaborative A-GPS
2x current!
Control-planelatency
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Use case 2: Collaborative A-GPS
Collaboration between devices in a P2P fashion: Context-awareness (sense environment so do not turn on
AGPS indoors!) Share/pre-fetch assisting data (reduces latency to fetch
data)
Prototype for Nexus One: Pre-fetch and cache of assisting data Devices can detect if they’re indoors in less than 10
seconds Blackbox. Hard to inject assisting data on chipsets (A-
GPS is controlled by binary/proprietary files/drivers )
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3. Wired-wireless integration
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Use case 3: Wired-wireless integration
3G offloading to WiFi and femtocells: Reduce network traffic No real benefit for users (unless volume cap in data-plan)
Wired network can be constrained! Can cellular networks augment wired networks? Wired nets deployment is $$$ Cellular nets have good coverage
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20
Use case 3: Wired-wireless integration
2 Km2.8 Mbps
DSLAM
A
Google Maps
4.7 Mbps
Cellular network can provide more capacity than wired ones (DSL)
Spare capacity on cellular network Powerboost for video-
streaming apps
Use-and-release
Does NOT work everywhere anytime!
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Use case 3: Wired-wireless integration
2x downlink/5x uplink for most locations with 1 mobile device
Simulation: 50% of the videos have a speed up factor of 10x
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Conclusions
Current cloud-mobile model is not efficient Hyper-centralized: push notifications Lack of connectivity between handsets: missing
opportunities Cellular and wired networks are fully decoupled
Flashlinq/LTE-direct can bring a new mobile paradigm! Energy and network efficient Distributed Flexible
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Flashlinq limitations and extensions
Transparent security/authentication mechanisms Lessons to be learnt from the past: Bluetooth and WiFi-
direct failed! Source of DoS/Privacy/Energy attacks Global Signpost-ish naming (OpenSource, DNSSEC based)
Low-level radio details must be exposed to OS! Too much layering hides inefficiencies: e.g. A-GPS and 3G Cross-layer optimizations are key (e.g. iPhone vs. Android)
Incentives for operators? Reduce operational costs: better use of limited capacity Licensed frequency