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Distribute what you can, centralize what you must! Narseo Vallina-Rodriguez Supervisor: Jon Crowcroft Qualcomm – Cambridge 22 nd May 2013.

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Presentation on theme: "Distribute what you can, centralize what you must! Narseo Vallina-Rodriguez Supervisor: Jon Crowcroft Qualcomm – Cambridge 22 nd May 2013."— Presentation transcript:

1 Distribute what you can, centralize what you must! Narseo Vallina-Rodriguez Supervisor: Jon Crowcroft Qualcomm – Cambridge 22 nd May 2013

2 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 (Googles GCM) NAT punching for P2P (Skype)

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

4 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, 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 DEMO

5 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

6 Distribute as much as you can!

7 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)

8 … but what can be distributed?

9 1. Localized data

10 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. SIGMETRICS2011]

11 Use case 1: AirportUse case 1: Airport notifications

12 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) Energy Signaling Spectrum (HSPA)

13 Use case 1: AirportUse case 1: Airport notifications

14 2. Collaborative sensing

15 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!

16 Use case 2: Collaborative A-GPS 2x current! Control-plane latency

17 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 theyre indoors in less than 10 seconds Blackbox. Hard to inject assisting data on chipsets (A-GPS is controlled by binary/proprietary files/drivers )

18 3. Wired-wireless integration

19 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 20 Use case 3: Wired-wireless integration 2 Km 2.8 Mbps A 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 !

21 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

22 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

23 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

24 Thank you for your attention!


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