applications offloading in mobile cloud computing...
TRANSCRIPT
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Applications Offloading in Mobile
Cloud Computing Environment
Amal ELLOUZE, Ph.D. Candidate
Prof. Maurice GAGNAIRE
29 November 2013
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Motivation
CPU / Battery Limitations of
mobile terminals
Mobile Cloud Computing
(MCC)
Mobile Application Offloading
(MAO)
MCC “ a new paradigm for mobile applications whereby the data processing and storage are moved from the
mobile device to powerful and centralized computing platforms located in clouds” Aepona [1]
[1] White Paper, “Mobile Cloud Computing Solution Brief,” AEPONA, November 2010.
GreenDays@Lille Slide 2
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Infrastructure Deployment
CO
MME/UPE
BBU Farm
Application
Server
Farm
RRH
WDM-PON-based Mobile Backhaul
GreenDays@Lille Slide 3
RRH
RRH
RRH
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MAO
MAO Mobile Applications Offloading is a decision algorithm that
enables to offload judiciously certain applications under I/O
energy consumption constraints
Slide 4 GreenDays@Lille
Today: Microsoft : MAUI decides at Runtime what methods should be
remotely executed
Intel : CloneCloud clone the execution environment
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Considered Applications
A single M located at the foot of the pole
supporting the antenna
A single active user was considered in the
cell
Six main applications were considered to
evaluate the decision algorithm
M
GreenDays@Lille Slide 5
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Assumptions
LTE Environment
Samsung Galaxy S2 at a speed of 1.2 GHz.
Tx / Rx Capacity=4 Mbit/s.
The server on which is activated a new VM for each
application offloading is equipped with a X86 CPU
operating 4 times faster than the CPU of the Mobile
Terminal.
GreenDays@Lille Slide 6
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MAO Algorithm
Start Input Execution_Time App
No offload
Offload
Reject
Execution_Time
App > Critical Delay
Energy Efficiency
T_Tot (sejourn, tr) <
Critical Delay
Update Energy=>
Energy Efficiency
D1
D2
D3
D4
GreenDays@Lille Slide 7
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Rejection Causes
74%
26%
Network Conditions
Server load
GreenDays@Lille Slide 8
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Actions
We offload the code of an eligible job with its input
associated data onto a remote server
Once this job has been computed, we download its result
back to the mobile terminal
Evaluation Metrics: Battery lifetime and Rejection Ratio
GreenDays@Lille Slide 9
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Results
0%
10%
20%
30%
40%
50%
60%
70%
0,01 0,02 0,03 0,04 0,05 0,1 0,5 1 1,1
Battery lifetime % Taux de rejets %
λ=Application/seconde
Taux de rejets
Battery lifetime
GreenDays@Lille Slide 10
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Results
of Battery energy gain over an offered load of 0.1
applications per second
GreenDays@Lille Slide 11
63%
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Conclusion
MAO enables to decide under which conditions it is worth to offload an application from a mobile terminal to a remote VM located in the mobile backhaul
This operation may drive to a gain in available energy on the mobile terminal up to 60%
Future Works
• The PMs on which are activated the applications are not systematically located at the BS’s site but higher in the mobile backhaul infrastructure
• Ideally, the VM farms should be co-located with the BBU farms
• A cross-optimization tool for that purpose.
GreenDays@Lille Slide 12
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Thank you
GreenDays@Lille Slide 13