The Role of Cloudlets in Mobile Computing

1© 2009-2010 M. Satyanarayanan Microsoft Networking Research Summit, Bellevue, WA, 2010-06-02

The Role of Cloudlets in Mobile Computing

Mahadev Satyanarayanan

School of Computer Science

Carnegie Mellon University


Based on same Spanish test set

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SystranSpanish

GoogleChinese

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CBMTSpanish

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SDLSpanish

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GoogleSpanish

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Human Scoring Range

Machine Translation Today


Face Recognition Today


What’s The Catch?

These are resource-intensive applications

• State-of-art performance and quality only with room full of servers

• How do we achieve this “in the wild”?(on resource-poor, energy-limited mobile hardware)

Obvious solution: leverage the cloud!

But your cloud may be far away

End-to-end latency matters for crisp interaction

• e.g., real-time two-way language translation on mobile devices

• e.g, augmented reality for cognitive assistance via “smart glasses”

and many other examples


Latency Hurts Even If Bandwidth Good(E.g. QuakeViz interactive benchmark on VNC thin client 100 Mbps)


Sample Internet2 RTTs (milliseconds)


Latency on 3G Networks“The wireless delay in the 3G network dominates the whole

network path delay, e.g., latency to the first pingable hop is around

200ms, which is close to the end-to-end Ping latency to landmark

servers distributed across the U.S.”

from “Anatomizing Application Performance Differences on

Smartphones”, to appear in MobiSys 2010 (Huang et al)


Solution: Create a Tiny Cloud Nearby

Low-latencyhigh-bandwidth1-hop wireless

network

Olympus Mobile Eye Trek

Wearable Computer

HandtalkWearable

Glove

Nokia N810Tablet

AndroidPhone

Coffee shopCloudlet

WAN todistant cloudon Internet

cloudlet = (compute cluster+ wireless access point+ wired Internet access+ no battery limitations)

““data center in a box”data center in a box”


Local Wireless Bandwidth

Original motivation for cloudlets was latency

But 1-hop wireless bandwidth to cloudlet also a win

• wireless LAN bw typically 100X wireless WAN bwe.g. 802.11n ≈ 400 Mbps but HSPDA ≈ 2 Mbps

• shipping large objects within interactive time boundse.g. captured images in an augmented reality system

4MB JPEG image takes 80 ms @ 400 Mbps, but 16 seconds @ 2 Mbps


Cloudlet vs. Cloud

CloudletCloudlet CloudCloud

State Only soft state Hard and soft state

Management Appliance model:

self-managed; little

professional attention

Utility model:professionally administered, 24x7 operator coverage

Environment “Data center in a box” at customer premises

Machine room with power conditioning and cooling

Ownership Decentralized ownership by local business

Centralized ownership by Amazon,Yahoo!, etc.

Network LAN latency and bandwidth

Internet latency and bandwidth

Sharing Few users at a time 100s to 1000s of users


Key Challenges

1. Trusting infrastructure

• tamper-resistant hardware (“first-world infrastructure”)

• portable device as root of trust (e.g TrustSniffer)

2. Finding the exactly right software on it

uniformity deployer value

specificity end-user valueinherent tension


Transient Customization

Deliver fully configured virtual machine (VM) to infrastructure

Problem: too large, too slow for transient use

Solution: assemble VM on the fly dynamic VM synthesis

• prefetch large, relatively static, widely-used piece (“base VM”)

• deliver small patch (“VM overlay”) just before use

• discard VM after use

VM overlay can come from

• mobile device over wireless link, or

• web site under control of mobile device (URL and decryption key)


Dynamic VM Synthesis

Mobile

Device

Cloudlet

Preload base VM

Discover & negotiateuse of cloudlet

private VM overlay (base + overlay) launch VM

Execute launch VM

Create VM residue

VM residue

Finish usedone

Depart Discard VM

Optional: cache VM overlay

Usecloudlet

user-drivendevice-VM

interactions


Typical Overlay Sizes(base VM = 8GB Ubuntu Linux)

Application Compressed VM Overlay Size (MB)

Uncompressed VM Overlay Size (MB)

Install Package Size (MB)

AbiWord 119.5 364.2 10.0

GIMP 141.0 404.7 16.0

Gnumeric 165.3 519.8 16.0

Kpresenter 149.4 426.8 9.1

PathFind 196.6 437.0 36.8

SnapFind 63.7 222.0 8.8

Null 5.9 24.8 0.0


VM Synthesis Time at 100Mbps(untuned proof-of-concept prototype)

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AbiWord GIMP Gnumeric Kpresenter PathFind SnapFind Null

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Resume VM

Apply VM overlay

Decompress VM overlay

Transfer floppy disk

Compress floppy disk

Transfer VM overlay

Largest standard deviation is 5.3% of mean

Nearly half the totalAll in the infrastructurePotentially optimizable


When Bandwidth Drops to 10Mbps

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AbiWord GIMP Gnumeric Kpresenter PathFind SnapFind Null

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e in

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Resume VM

Apply VM overlay

Decompress VM overlay

Transfer floppy disk

Compress floppy disk

Transfer VM overlay

Largest standard deviation is 3.4% of mean


Some Education is Needed

“In the discussion of the proposal, several members of the panel were skeptical about the argument about the need extremely low latencies for handheld devices.

In particular, handhelds are (historically) remarkably powerful computers capable of running user interfaces (the source of most latency sensitivity) locally.

The panel also felt that the case for "cloudlets" was not compelling in contrast to other distributed system architectures such as relying alarge-scale cloud based on conventional data centers and using a geographically distributed three-layer web service architecture.”


In Closing

(but keep the Swiss Army Knife handy for emergencies) Leverage the Cloud!Leverage the Cloud!

VM-based CLoudlets

Documents

The Role of Cloudlets in Mobile Computing