Cloudlet-Based Cyber-Foraging in Resource-Constrained Environments

© 2013 Carnegie Mellon University
Cloudlet-Based Cyber-
Foraging in Resource-
Constrained Environments
VU University Amsterdam
September 26, 2013
Grace A. Lewis (glewis@sei.cmu.edu)

2
Cloudlet-Based Cyber-Foraging in Resource-
Motivation
First responders and others operating in crisis and
hostile environments increasingly are making use
of handheld devices to help with tasks such as
speech and image recognition, natural language
processing, decision-making and mission planning
Challenges for mobile devices in resource-
constrained edge environments
•  Mobile devices offer less computational power than
conventional desktop or server computers
•  Computation-intensive tasks take a heavy toll on
battery power
•  Networks are often unreliable and bandwidth is
limited and inconsistent

3
Characteristics of Resource-Constrained
Environments
Wimpy edge nodes
•  Limited resources (CPU, battery and memory) on mobile nodes
Limited or no end-to-end network connectivity
•  Implicit assumption of WAN connectivity is not always valid
High cognitive load
•  Application latency and fidelity become important in situations of high stress
Bounded elasticity
•  Upper bound on number of consumers known in advance
Dynamic environment
•  Static deployment topologies cannot be assumed
•  Survivability is essential

4
Mobile Cloud Computing
Mobile Cloud Computing refers to the combination of mobile devices
and cloud computing in which cloud resources perform computing-
intensive tasks and store massive amounts of data
Work in this field is currently divided into three areas
1.  Extending access to cloud services to mobile devices
2.  Enabling mobile devices to work collaboratively as cloud resource
providers
3.  Augmenting execution of mobile applications using cloud resources
Cyber-foraging is part of the last area

5
Cyber-Foraging
Cyber-foraging* is the leverage of external resource-rich surrogates to
augment the capabilities of resource-limited devices
•  Increase computational capability
•  Conserve battery on a mobile device
•  Access remote or shared data
•  Provide better application fidelity
Two main forms of cyber-foraging
•  Code/Computation Offload
– Offload of expensive computation in order to extend battery life and
increase computational capability
•  Data Staging
– Improve data transfers between mobile computers and the cloud by
temporarily staging data in transit
* Satyanarayanan, Mahadev (2001). "Pervasive Computing: Vision and Challenges". IEEE Personal Communications (IEEE)

6
Challenges for Cyber-Foraging in Resource-
Most cyber-foraging solutions rely on
•  conventional Internet for connectivity to the cloud
•  strategies that tightly couple mobile clients with servers at deployment time
These solutions are not appropriate for resource-constrained
environments because they do not address the challenge of unreliable
networks and dynamic environments

7
Cyber-Foraging Questions
Where to offload?
•  Proximate (single-hop) or remote (multi-hop) servers?
When to offload?
•  With optimization in mind, when does it make sense to offload?
What to offload?
•  What is the granularity of the computation (or data) that is offloaded?
•  What is the payload?

8
Cyber-Foraging: Where to Offload?
Mobile
Enterprise Cloud
(Data Center)
Mobile Surrogate
Enterprise Cloud
(Data Center)
Synchronous network I/O, Multi-hop network
Synchronous
Network I/O
Asynchronous
Network I/O
tcloud
tsurrogate
Single-hop
network
tcloud
Assuming that tsurrogate is less than tcloud, nearby surrogates are a better
option from an energy consumption and latency perspective

9
Cyber-Foraging: When to Offload?
Never offload
It Depends: Size of this
area depends on
optimization algorithm
Always Offload
Offloading is beneficial
when large amounts of
computation (C) are
needed with relatively
small amounts of
communication (D)*
Goal of Optimization
•  Maximize a utility
function
•  Typically energy,
execution time, fidelity
or results
Computation (C)
Communication(D)
* Based on Karthik Kumar and Yung-Hsiang Lu. Cloud computing for mobile users. Computer, 99, 2010.

10
Cyber-Foraging: What to Offload?
Another aspect of what to offload is the actual payload
•  Computation is transferred from the mobile device to the surrogate at runtime,
or
•  Code already exists on the surrogate and is remotely invoked, in which case
the payload is simply the input parameters
Physical Machine
OS
Infrastructure
VM Image (VM Manager, e.g., KVM,
OpenStack)
Process/Application/Service (Application
Server)
Method/Thread (Language-Specific Virtual
Machine, e.g., JVM, CLR)
Surrogate
Mobile Code (Runtime Environment)
One aspect is granularity

11
Cloudlet-Based Cyber-Foraging
Discoverable, generic,
stateless servers located in
single-hop proximity of mobile
devices
Can operate in disconnected
mode — communication with
the central core is only
needed for provisioning
Virtual-machine based to
promote flexibility and mobility
Applications statically
partitioned into client and
server
•  Client runs on mobile device
•  Server runs on cloudlet
Enterprise
Cloud
Cloudlet Cloudlet Cloudlet
Single-‐Hop
Network
Multi-‐
or
Single-‐Hop
Network
Cloudlet

12
Reference
Architecture
for Cloudlet-
Based
Cyber-
Foraging
Cloudlet
HostMobile
Client
Legend
System

Boundary
Cloudlet-‐
Ready

Client
App

1
Custom
Runtime

Component
Cloudlet

Client
File
Read/
WriteCall
File
VM Manager
Guest
VM
1
Server
1
Cloudlet

Server
Discovery Service
Cloudlet
Metadata
Broadcast
3rd
Party
Runtime
Component
Server
Offload
Code
+
Metadata
Cloudlet-‐
Ready

Client
App

2
Cloudlet-‐
Ready

Client
App

n
...
...
Guest
VM
2
Server
2
Guest
VM
n
Server
n
...
Cloudlet

Metadata
Client

App
1

Metadata
Client

App
n

Metadata
Client

App
2

Metadata
Server
1

Offload

Code
Server
2

Offload

Code
Server
n

Offload

Code

13
Original Proposal for Cloudlet Provisioning: VM
Synthesis
Application overlay is transmitted to the cloudlet at runtime
Cloudlet applies application overlay to the Base VM and produces a
Complete VM
Start
Base
VM
Base VM
Disk Image
Install
Application
Complete
Memory
Snapshot
Suspend
VM
Save Disk
and
Memory
Snapshots
Complete
Disk
Snapshot
Obtain Base
VM from
Central Core
Start
Application
Base
Memory
Snapshot
Calculate Diff Between
Complete Snapshots and
Base Snapshots
VM Disk
Image
Overlay
Memory
Snapshot
Overlay
Application Overlay
Base
Disk
Snapshot

14
VM Synthesis
Process
1.  Mobile device
discovers cloudlet
2.  Mobile device sends
application overlay
(always offload
strategy)
3.  Cloudlet applies
overlay to base VM
4.  Cloudlet starts the
constructed VM and
informs client that
the application
server is ready for
execution
Cloudlet HostMobile Client
Legend
System
Boundary
Cloudlet-
Ready
Client
App 1
Custom Runtime
Component
Cloudlet
Client
Application
Overlay n
File Read/
WriteCall
File
VM Manager
Guest VM 1
Server 1
Cloudlet
Server
Discovery Service
Cloudlet Server IP Address/Port
Broadcast
Base VM
Image
3rd
Party
Runtime
Component
Application
Overlay 2
Application
Overlay 1
Application Overlay
Cloudlet-
Ready
Client
App 2
Cloudlet-
Ready
Client
App n
...
...
Guest VM 2
Server 2
Guest VM n
Server n
...

15
Problems with VM Synthesis in Resource-
VM overlays are very large
•  Large payloads incur large energy costs
•  Limited bandwidth can make application ready time unreasonable
Payload
NULL OBJECT SPEECH FACE
Linux (MB)
Windows
(MB)
Linux (MB)
Linux
(MB)
Windows
(MB)
Windows
(MB)
Compressed Disk
Overlay
0.1 0.4 42.8 104.8 113.7 33.5
Compressed Disk
+ Memory
Overlays
21.2 4.2 144.5 226.8 425.7 141.5
Question: Is it possible to maintain the flexibility and mobility of a VM-
based strategy but reduce payload size?

16
Cloudlet Provisioning using Application
Virtualization
Emulates OS functionality for an application
Runtime component intercepts all system calls from an application and
redirects these to resources inside the virtualized application
Application itself is unmodified and unaware that it is interacting with
virtual OS services
Sample Tools
•  CDE (short for Code, Data and Environment)
– Application virtualizer for Linux
– Virtualizes applications by monitoring their execution
•  Cameyo
– Application virtualizer for Windows
– Virtualized applications by monitoring the installation process

17
Application
Virtualization
Process
Mobile
Device
Application
1

Package
Cloudlet
Host
VM
Hypervisor
Guest
VM
– OS
1
Cloudlet
Server
Application
1
Server
Application
i Server
Guest
VM
– OS
n
Discovery
Application
1
Client
Application
1

Metadata
HTTP
Server
Cloudlet
Server
Application
j
Server
Application
m
Server
Discovery
HTTP
Server
Cloudlet
ClientDiscovery
Application
i
Client
Application
j
Client
Application
m
Client
Application
i
Package
Application
i

Metadata
Application
j

Package
Application
j

Metadata
Application
m

Package
Application
m

Metadata
Application
Package
Application
Metadata
Application
Package
Application
Metadata
IP
Address
:
Port
Cloudlet
Properties
Legend
System
Boundary Custom
Runtime
Component
3rd
Party
Runtime
Component
File Blocking
Call Non-‐Blocking
Call File
Read HTTP Multicast
1.  Mobile device
discovers cloudlet
application package
and metadata
3.  Cloudlet deploys
application package
inside matching
guest VM
4.  Cloudlet informs
client that the
application server is
ready for execution

18
VM Synthesis vs. Application Virtualization
Cyber-
Foraging
Strategy
Transmitted
Package
NULL OBJECT SPEECH FACE
Linux (MB)
Windows
(MB)
Linux (MB)
Linux
(MB)
Windows
(MB)
Windows
(MB)
Application
Virtualization
Compressed
Virtualized
Application
1.1 0.9 28.5 67.7 65.4 13.1
VM Synthesis
Compressed Disk
Overlay
0.1 0.4 42.8 104.8 113.7 33.5
Compressed Disk +
Memory Overlays
21.2 4.2 144.5 226.8 425.7 141.5
Experiments show that energy consumption is proportional to file size
Even though application virtualization creates payloads of smaller size, it is still
large for resource-constrained environments
Exploring two alternative options
•  Cloudlet Push
•  On-Demand VM Provisioning

19
Cloudlet Push
Opposite approach to traditional cyber-foraging and cloudlet
provisioning
•  Pushes client application from the cloudlet to the mobile device

20
Cloudlet Push
(PROTOTYPE)
Legend
System

Boundary
Client
App

1
Custom
Runtime

Component
Cloudlet

Client
File
Read/
WriteCall
File
VM Manager
Guest
VM
1
Server
1
Cloudlet

Server
Discovery Service
Cloudlet
Metadata
Broadcast
3rd
Party
Runtime
Component
Client
App
Client
App

2
Client
App

n
...
Guest
VM
2
Guest
VM
n
Server
n
...
Cloudlet

Metadata
Client

Metadata

Client

App
Server
2
Client
Metadata
Cloudlet
HostCloudlet
HostMobile
ClientMobile
Client
1.  Mobile device
discovers cloudlet
(and available
applications)
client metadata and
selected app
3.  Cloudlet sends
client app
4.  Mobile device
installs and starts
client app

21
On-Demand Provisioning
Leverages commercial cloud provisioning tools such as Puppet or
Vagrant to “compose” VMs on demand to match the requirements of the
mobile application client
•  What is transferred from the mobile device to the cloudlet is a provisioning
script
Composition could be
•  Instantiating a pre-configured VM from a VM image repository that contains
the full server component
•  Instantiating a pre-configured base VM and adding components
•  Putting together a VM from a set of basic components

22
On-Demand VM
Provisioning
(WORK IN PROGRESS)
1.  Mobile device discovers
cloudlet
provisioning script to
cloudlet
3.  Cloudlet runs VM
provisioning script and
starts VM
4.  Cloudlet informs client
that the application
server is ready for
execution
Cloudlet
HostMobile
Client
Legend
System

Boundary
Cloudlet-‐
Ready

Client
App

1
Custom
Runtime

Component
Cloudlet

Client
File
Read/
WriteCall
File
VM Manager
Guest
VM
1
Server
1
Cloudlet

Server
Discovery Service
Cloudlet
Metadata
Broadcast
3rd

Party

Runtime

Component
Provisioning
Script
Cloudlet-‐
Ready

Client
App

2
Cloudlet-‐
Ready

Client
App

n
...
...
Guest
VM
2
Server
2
Guest
VM
n
Server
n
...
Cloudlet

Metadata
Server
1

Provisioning

Script
Server
n

Provisioning

Script
Server
2

Provisioning

Script
VM
Image

Repository
Database

23
Comparison of Cloudlet Provisioning Strategies
VM Synthesis Application
Virtualization
Cloudlet Push On-Demand VM
Provisioning
Cloudlet Contents
(plus Cloudlet
Server)
Exact Base VM(s) VM(s) compatible
with client app(s)
•  Paired VM
(server code)
•  Client app(s)
•  VM provisioning
software
•  Server
components
Mobile Device
Contents
•  Cloudlet client
•  Application
overlay
•  Client app
•  Cloudlet client
•  Virtualized server
code
•  Client app
•  Cloudlet client •  Cloudlet client
•  VM provisioning
script(s)
•  Client app
Advantages Guarantees replica
of pre-configured
surrogate
Portability across
OS distribution
boundaries
Supports most
client nodes at
runtime
Small data
transfer
Constraints Exact Base VM —
limits distribution
and patches
All dependencies
must be captured
at packaging time
Cloudlet has a
client app version
matching mobile
client OS version
Cloudlet has all
required VM
components
Distribution to
Mobile Devices
Deployment Deployment Runtime Deployment
Runtime Transfer
Cost
Depends on
overlay size
Medium Low Very low

24
Current Work: Architecture Strategies for
Cyber-Foraging in Resource-Constrained
Environments
Research Question
What are the strategies/patterns/tactics — expressed as architecture
decisions and promoted quality attributes — that would provide
architecture alternatives for cyber-foraging that adapt to unreliable
networks and dynamic environments while conserving battery power

25
Related Work 1
Work in cyber-foraging dates back to 2001 when the term was coined
•  Most proposed solutions for cyber-foraging come from electrical and
computer engineering with very little emphasis on software engineering or
software architecture
•  Most solutions favor one quality attribute (typically battery consumption or
latency) with very little consideration of architecture tradeoffs
•  Many solutions assume that code can execute on both the mobile device and
the surrogate, which is highly unlikely for the complex algorithms used by
edge applications
•  Many solution tightly couple mobile clients with surrogates at deployment time

26
Related Work 2
Representative Cyber-
Foraging Solutions
Quality Attributes
Basic Tradeoff Space Extended Tradeoff Space
Energy
Execution
Time
Fidelityof
Results
Network
Capabilities
Survivability
Resiliency
Security
Flexibility
Spectra [Flinn 2002] X X X
Chroma [Balan 2003] X X X
Surrogates [Goyal 2004] X X
Slingshot [Su 2005] X X X X
Cloudlets [Satyanarayanan 2009] X X
MAUI [Cuervo 2010] X X X X
Scavenger [Kristensen 2010] X X
CloneCloud [Chun 2011] X X X
Odessa [Ra 2011] X X

27
Goal
Identify architecture strategies that address a much broader range of
quality attributes that are critical in resource-constrained environments,
e.g.
•  Survivability — fitness/readiness, awareness, anticipation, speed
(responsiveness), agility (e.g., flexibility/ maneuver), and evolvability*
•  Resiliency — robustness (e.g., redundancy), diversity, active defense, rapid
reconstitution*
* Source: Air Force Cyber Vision 2025. July 2012.

28
Contact Information
Grace A. Lewis
Advanced Mobile Systems (AMS) Initiative
Software Engineering Institute
4500 Fifth Avenue
Pittsburgh, PA 15213-2612
USA
Phone: +1 412-268-5851
Email: glewis@sei.cmu.edu
WWW: http://www.sei.cmu.edu/staff/glewis/

29
Selected Cyber-Foraging References
[Balan 2003] Rajesh K. Balan, Mahadev Satyanarayanan, So Young Park, and Tadashi Okoshi. Tactics-based remote
execution for mobile computing. In Proceedings of the 1st International Conference on Mobile Systems, Applications and
Services, pages 273–286, San Francisco, CA, May 2003.
[Chun 2011] Byung-Gon Chun, Sunghwan Ihm, Petros Maniatis, Mayur Naik, and Ashwin Patti. CloneCloud: Elastic
execution between mobile device and cloud. In Proceedings of the European Conference on Computer Systems,
Salzburg, Austria, April 2011
[Cuervo 2010] Eduardo Cuervo, Aruna Balasubramanian, Dae ki Cho, Alec Wolman, Stefan Saroiu, Ranveer Chandra,
and Paramvir Bahl. MAUI: Making smartphones last longer with code offload. In Proceedings of the 8th International
Conference on Mobile Systems, Applications and Services, pages 49–62, San Francisco, CA, June 2010.
[Flinn 2002] Jason Flinn, SoYoung Park, and Mahadev Satyanarayanan. Balancing Performance, Energy, and Quality in
Pervasive Computing. In Proceedings of the 22nd International Conference on. Distributed Computing Systems, Vienna,
Austria, July 2002.
[Flinn 2012] Jason Flinn. Cyber Foraging: Bridging Mobile and Cloud Computing. Synthesis Lectures on Mobile and
Pervasive Computing. Vol. 7, No. 2, pp. 1-103. 2012.
[Goyal 2004] Sachin Goyal and John Carter. A lightweight secure cyber foraging infrastructure for resource-constrained
devices. In Proceedings of the 6th IEEE Workshop on Mobile Computing Systems and Applications, Lake Windermere,
England, December 2004.
[Kristensen 2010] Mads Daro Kristensen. Scavenger: Transparent deployment of efficient cyber foraging applications. In
IEEE International Conference on Pervasive Computing and Communications (PerCom), pages 217–226, San Diego,
CA, March 2010.
[Ra 2011] Moo-Ryong Ra, Anmol Sheth, Lily Mummert, Padmanabhan Pillai, DavidWetherall, and Ramesh Govidan.
Odessa: Enabling interactive perception applications on mobile devices. In Proceedings of the 9th International
Conference on Mobile Systems, Applications and Services, Washington, DC, June 2011.
[Satyanarayanan 2009] Mahadev Satyanarayanan, Paramvir Bahl, Ramón Cáceres, and Nigel Davies. The case for VM-
based cloudlets in mobile computing. IEEE Pervasive Computing, 8(4):14–23,October–December 2009.
[Su 2005] Ya-Yunn Su and Jason Flinn. Slingshot: Deploying stateful services in wireless hotspots. In Proceedings of the
3rd International Conference on Mobile Systems, Applications and Services, pages 79–92, Seattle, WA, June 2005.

30
Our Publications
Refereed
•  Lewis, Grace; Simanta, Soumya; Novakouski, Marc; Cahill, Gene; Boleng, Jeff; Morris,
Edwin; and Root, James. Architecture Patterns for Mobile Systems in Resource-
Constrained Environments. 32nd Annual Military Communications Conference (MilCom
2013). Novermber, 2013.
•  Simanta, Soumya; Lewis, Grace; Morris, Ed; Ha, Kiryong; and Satyanarayanan,
Mahadev. A Reference Architecture for Mobile Code Offload in Hostile Environments.
Proceedings of the 4th International Conference on Mobile Computing, Applications
and Services (MobiCASE 2012). October 2012.
•  Simanta, Soumya; Lewis, Grace; Morris, Ed; Ha, Kiryong; and Satyanarayanan,
Mahadev. A Reference Architecture for Mobile Code Offload in Hostile Environments.
Proceedings of the Joint 10th Working IEEE/IFIP Conference on Software Architecture
& 6th European Conference on Software Architecture (WICSA/ECSA 2012). August
2012.
Other
•  S. Simanta, G. Lewis, E. Morris, K. Ha, and M. Satyanarayanan, "Cloud Computing at
the Tactical Edge," Software Engineering Institute, Carnegie Mellon University,
Pittsburgh, Pennsylvania, Technical Note CMU/SEI-2012-TN-015, 2012. http://
www.sei.cmu.edu/library/abstracts/reports/12tn015.cfm

31
Copyright 2013 Carnegie Mellon University
This material is based upon work funded and supported by the Department of Defense
under Contract No. FA8721-05-C-0003 with Carnegie Mellon University for the operation
of the Software Engineering Institute, a federally funded research and development center.
Any opinions, findings and conclusions or recommendations expressed in this material are
those of the author(s) and do not necessarily reflect the views of the United States
Department of Defense.
NO WARRANTY. THIS CARNEGIE MELLON UNIVERSITY AND SOFTWARE
ENGINEERING INSTITUTE MATERIAL IS FURNISHED ON AN “AS-IS” BASIS.
CARNEGIE MELLON UNIVERSITY MAKES NO WARRANTIES OF ANY KIND, EITHER
EXPRESSED OR IMPLIED, AS TO ANY MATTER INCLUDING, BUT NOT LIMITED TO,
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