Distribute what you can, centralize what you must!Narseo Vallina-Rodriguez

Supervisor: Jon Crowcroft

Qualcomm – Cambridge22nd May 2013

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)

Research question

How do mobile apps’ cloud dependency impact on cellular network and battery life of mobile handsets?

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

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

Distribute as much as you can!

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)

… but what can be distributed?

1. Localized data

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]

NODE B

RNC SGSN GGSN

SERVER

(UK)

INTERNET

GoogleGCM (Ir)

Use case 1: AirportUse case 1: Airport notifications

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)

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!

2. Collaborative sensing

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!

Use case 2: Collaborative A-GPS

2x current!

Control-planelatency

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 )

3. Wired-wireless integration

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

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!

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

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

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

Thank you for your attention!

http://www.cl.cam.ac.uk/~nv240nv240@cam.ac.uk