icacon 2015 -0.7em9cm0.3pt mobile application offloading
TRANSCRIPT
ICACON 2015
Mobile Application Offloading: An Opportunitytowards Mobile Cloud Computing
A. Ellouze, M. Gagnaire
May 22, 2015
Outline
ResearchMotivationOffloading decision modelDecomposition of energy consumptionState of charge of the batteryMobile Application Offloading Algorithm (MAO)Numerical SimulationFuture Work
A. Ellouze, M. Gagnaire ICACON 2015 – Institut Mines-Télécom 2 / 16
Research Motivation
MotivationI An offloading strategy for mobile applications;I Infrastructure deployment – cross optimization tool between Radio
resources disponibility and VMs allocation;
A. Ellouze, M. Gagnaire ICACON 2015 – Institut Mines-Télécom 3 / 16
Research Offloading decision model
Mobile Processor Job Modeling
Figure: Processor Sharing Model
A. Ellouze, M. Gagnaire ICACON 2015 – Institut Mines-Télécom 4 / 16
Research Offloading decision model
Offloading Decision Model
Concept of critical delay:
I Expected excution delay – Dexpected(j) given N(j),ta(j), CM
I Ideal execution delay – D(j)
I Preferred waiting delay (in relation with QoE) – d(j)
I Critical delay – D∗(j) = D(j) + d(j)
A new application is eventually offloaded if:
Dexpected (j) > D∗(j) (1)
A. Ellouze, M. Gagnaire ICACON 2015 – Institut Mines-Télécom 5 / 16
Research Decomposition of energy consumption
Decomposition of energy consumption
I If job j is processed on the mobile terminal, the minimum energyconsumption EM
min(j) is given by:
EMmin(j) = Pactive
M × DMmin(j) (2)
I If this same job is processed on the server, the energy ES(j) consumedby the mobile terminal for this offload is given by:
ES(j) = Etr (j) + EMidle,p(j) + EM
idle,w (j) (3)
Etr (j) = P × V (j)B
(4)
where,P(Ptr );Ptr = min(Pmax ,P0 + 10 × log10(M) + PL) (5)
EMidle,p(j) =
N(j)CS
× P idleM (6)
EMidle,w (j) =
ρ× N(j)CS
2 × (1 − ρ)× P idle
M (7)
A. Ellouze, M. Gagnaire ICACON 2015 – Institut Mines-Télécom 6 / 16
Research State of charge of the battery
State of charge of the battery
I 20% as a threshold to offload applications meeting the requirements.
I SoC = 1 − αA
αf , where, αA is the accumulated capacity during the timeperiod [ts, te] at the discharge current rate I and αf is the full capacity.
Figure: Battery model
11J. C. Zhang, S. Ci and H. Sharif, "An Enhanced Circuit-Based Model for Single-CellBattery," IEEE Applied Power Electronic
Conference and Exposition (APEC), February 21-25, 2010, Palm Springs, pp. 672-675.
A. Ellouze, M. Gagnaire ICACON 2015 – Institut Mines-Télécom 7 / 16
Research Mobile Application Offloading Algorithm (MAO)
Algorithm Flowchart
Main contributions:I QoE Satisfaction;I Network conditions considered;I User Position within the Cell
considered;I CPU considered;I State of Charge of the battery
considered;
Figure: MAO Flowchart.
A. Ellouze, M. Gagnaire ICACON 2015 – Institut Mines-Télécom 8 / 16
Research Mobile Application Offloading Algorithm (MAO)
Applications - Benchmark
Range of applications:I Chess game: processing inherent to the execution of one move on the
chess-board;I Speech recognition: conversion of an analog speech to a text and vice
versa;I Virus scanning: a program able to detect the presence of virus, and if
possible, to kill it;
Table: Applications parameters.
Application CPU Interactivity d(j) inseconds
D(j)∗inseconds
Chess game High High 0.2 7.329Speech recognition Low High 1 1.75Virus Scanning High Low 10 25.671
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Research Numerical Simulation
Simulation parametersTable: Simulation parameters.
Parameter ValueCellular layout 1 Single hexagonal cellCell radius 500 mPath loss model PL = A+30× log10(
dd0 )+Xf +Xh+σ
Channel fading Typical urbanCarrier frequency 2GHzSystem Bandwidth 5MHz (25RBs)Thermal Noise per RB −121.45 dBmBit rate of the mobile 600Kbps < B < 16MbpsTraffic Control messages, data trafficNumber of UE 1Number of application activation 100Inter-arrival in seconds λ−1 2, 15, 30Simulation duration 3 hours
22we assume that an application server is located at the antenna’s site and the three applications softwares are installed on the remote
server.
A. Ellouze, M. Gagnaire ICACON 2015 – Institut Mines-Télécom 10 / 16
Research Numerical Simulation
Equally mixed applications
Variable loads Variable CPU Speed
15 20 25 30 35 40 45 50 55 600
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inter−arrival of applications (in seconds)
Ene
rgyG
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& R
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tionR
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Energy Savings and Rejection Ratio under variable loads (Scenario Mix)
Energy GainRejection Ratio
0 5 10 15 20 25 300
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F (CPU Server Speed per CPU Mobile Speed)
Ene
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& R
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Performance Evaluation With Different Computational Resources
Energy GainRejection Ratio
X axis: Inter-arrival in seconds X axis: F (Computational ratio)Y axis: Energy Gain and Rejection Ratio Y axis: Energy Gain and Rejection Ratio
Conclusion:I When inter-arrivals gets greater, offloading applications is less beneficial.I Having more computational resouces provides avenues for more gains
to be achieved in terms of energy savings.
A. Ellouze, M. Gagnaire ICACON 2015 – Institut Mines-Télécom 11 / 16
Research Summary
Summary
I Developed Offloading decision model;
I Designed offloading algorithm tweaking on energy efficiency andQoE(MAO);
I Used realistic applications to simulate;
I Evaluated model through simulated results;
A. Ellouze, M. Gagnaire ICACON 2015 – Institut Mines-Télécom 12 / 16
Research Future Work
Perspectives
I Recovery effect of the battery to take into account;
I Overhead virtualization and architectures’s compatiblity to include;
I Cross optimzation tool between radio resources and VM’s placement;
A. Ellouze, M. Gagnaire ICACON 2015 – Institut Mines-Télécom 13 / 16
Bibliography
Bibliography
Dusza B, Ide C, Cheng L, Wietfeld C. " An accurate measurement-based power consumptionmodel for LTE uplink transmissions ", In Proc. IEEE INFOCOM (Poster), Turin, Italy, 2013.
X. Ma, Y. Cui, L. Wang and I. Stojmenovic "Energy Optimization for Mobile Terminals viaComputation Offloading", 2012 2nd IEEE International Conference on Parallel Distributed andGrid Computing (PDGC), 2012, pp. 236-241.
J. C. Zhang, S. Ci and H. Sharif, "An Enhanced Circuit-Based Model for Single-CellBattery,"IEEE Applied Power Electronic Conference and Exposition (APEC), February 21-25, 2010,Palm Springs, pp. 672-675.
Dusza, B., Ide, C., Cheng, L. and Wietfeld, C. (2013), CoPoMo: a context-aware powerconsumption model for LTE user equipment. Trans Emerging Tel Tech, 24: 615-632.
UE radio transmission and reception, January 2012. 3GPP TS 36.101, V 9.10.0.
E. Lagerspetz and S. Tarkoma, "Mobile search and the cloud: The benefits of offloading," inNinth Annual IEEE International Conference on Pervasive Computing and Communications,PerCom 2011, 21-25 March 2011, Seattle, WA, USA, Workshop Proceedings. IEEE, 2011,pp. 117-122.
John L. Henning, SPEC CPU2006 benchmark descriptions, SIGARCH Comput. Archit.News34,September 2006. Architecture for LTE Mobile Terminals", IEEE Conference, 2012.
A. Ellouze, M. Gagnaire ICACON 2015 – Institut Mines-Télécom 14 / 16
ICACON 2015
Mobile Application Offloading: An Opportunitytowards Mobile Cloud Computing
A. Ellouze, M. Gagnaire
May 22, 2015
The End Related Work
Related Work
I E. Cuervo, A. Balasubramanian, D.-k. Cho, A. Wolman, S. Saroiu, R. Chandra, and P. Bahl,"Maui: making smartphones last longer with code offload," in Proceedings of the 8thinternational conference on Mobile systems, applications, and services"
I B.-G. Cn, S. Ihm, P. Maniatis, M. Naik, and A. Patti, "Clonecloud: elastic execution betweenmobile device and cloud." in EuroSys, C. M. Kirsch and G. Heiser, Eds. ACM, 2011, pp.301-314.
I Shiraz, M. Gani, A. Khokhar, R.H. Buyya, R., "A Review on Distributed Application ProcessingFrameworks in Smart Mobile Devices for Mobile Cloud Computing," Communications Surveysand Tutorials, IEEE , vol.15, no.3, pp.1294,1313, Third Quarter 2013
A. Ellouze, M. Gagnaire ICACON 2015 – Institut Mines-Télécom 16 / 16