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HeteroPar 2013
Optimization of a Cloud Resource Management Problem from a Consumer Perspective
Rafaelli de C. Coutinho, Lucia M. A. Drummond andYuri Frota
Fluminense Federal University – UFF Brazil
Sponsorship:
Outline
Motivation
Definition and Formulation
GRASP
Results and Conclusions
Outline
oMotivation
oProblem Definition and Mathematical
Formulation
oGRASP for Resource Selection in Cloud
Environments
oPreliminary Results and Conclusion
Outline
Outline
Motivation
Definition and Formulation
GRASP
Results and Conclusions
Motivation
Cloud Computing
a large-scale distributed computing paradigm in which computing
resources are available to consumers via Internet.
Motivation
Outline
Motivation
Definition and Formulation
GRASP
Results and Conclusions
Motivation
Cloud Computing
a large-scale distributed computing paradigm in which computing
resources are available to consumers via Internet.
It delivers infrastructure, platform and software as services by signing service-level agreements (SLAs) with consumers.
Motivation
Outline
Motivation
Definition and Formulation
GRASP
Results and Conclusions
Motivation The provider should offer resource-economic services.
New pricing models based on the pay-as-you-go policy are necessary to address the highly variable demand for cloud resources.
Motivation
Outline
Motivation
Definition and Formulation
GRASP
Results and Conclusions
Motivation The provider should offer resource-economic services.
New pricing models based on the pay-as-you-go policy are necessary to address the highly variable demand for cloud resources.
For example, cloud service consumers might have an SLA with a cloud service provider concerning how much bandwidth, CPU, and memory the consumer can use at any given time throughout the day.
Motivation
Outline
Motivation
Definition and Formulation
GRASP
Results and Conclusions
Motivation Application schedulers have different policies that vary according to the objective function.
Independently of the objective function, resource allocation problems in clouds are NP-hard problems.
Motivation
Outline
Motivation
Definition and Formulation
GRASP
Results and Conclusions
Motivation
Cloud computing becomes more widespread
andComputing resources grow
More researches have been conducted on
Resource Allocation Problem in Clouds.
Motivation
Outline
Motivation
Definition and Formulation
GRASP
Results and Conclusions
Definition and FormulationA resource management problem that aims to reduce the payment cost and the execution time of the user application is defined.
An integer programming formulation and a heuristic based on Greedy Randomized Adaptive Search Procedure are proposed.
Definition and Formulation
Outline
Motivation
Definition and Formulation
GRASP
Results and Conclusions
Definition Problem Infrastructure-as-a-Service (Iaas) model:
• cloud consumers request computing resources as processing power, disk storage, memory and architecture type, for a period of time and pays only what he/she uses.
• Cloud providers have a wide variety of virtual machines.
• Cloud consumers have to decide which packages should purchase in order to minimize a specific objective as execution time or payment cost.
Definition and Formulation
Outline
Motivation
Definition and Formulation
GRASP
Results and Conclusions
Definition Problem Infrastructure-as-a-Service (Iaas) model:
• cloud consumers request computing resources as processing power, disk storage, memory and architecture type, for a period of time and pays only what he/she uses.
Cloud providers have a wide variety of package types.
• Cloud consumers have to decide which packages should purchase in order to minimize a specific objective as execution time or payment cost.
Definition and Formulation
Outline
Motivation
Definition and Formulation
GRASP
Results and Conclusions
Definition Problem Infrastructure-as-a-Service (Iaas) model:
• cloud consumers request computing resources as processing power, disk storage, memory and architecture type, for a period of time and pays only what he/she uses.
Cloud providers have a wide variety of package types.
Cloud consumers have to decide which packages should purchase in order to minimize a specific objective as execution time or payment cost.
Definition and Formulation
Outline
Motivation
Definition and Formulation
GRASP
Results and Conclusions
Modeling the problem … Let be the set of packages types offered by a cloud
provider during a set of time periods.
Definition and Formulation
Package
Package
Package
Outline
Motivation
Definition and Formulation
GRASP
Results and Conclusions
Modeling the problem … Let be the set of packages types offered by a cloud
provider during a set of time periods.
Each package type has: • cost• computing resources:
• disk storage • memory capacity • processing power ofGflop per period of time
Definition and Formulation
Package
Package
Package
𝑐𝑝𝑑𝑝𝑚𝑝
Package
𝑔𝑝
Outline
Motivation
Definition and Formulation
GRASP
Results and Conclusions
Modeling the problem … The set of consumer requirements is defined by:• maximum cost • maximum time • disk storage • memory capacity • processing demand of Gflop.
Definition and Formulation
, ,
Cloud Provider
Outline
Motivation
Definition and Formulation
GRASP
Results and Conclusions
Modeling the problem … The set of consumer requirements is defined by:• maximum cost • maximum time • disk storage • memory capacity • processing demand of Gflop.
Let , the maximum limit of packages that can be purchased for each consumer in each period of time.
Definition and Formulation
, ,
Cloud Provider
Outline
Motivation
Definition and Formulation
GRASP
Results and Conclusions
Modeling the problem … Let , a binary variable for each , and such that if and only if packageof type is purchased at time ; otherwise
Let , the variable that defines the last time period that a package was purchased by the consumer.
Definition and Formulation
Outline
Motivation
Definition and Formulation
GRASP
Results and Conclusions
The Mathematical Formulation CC-IP
Subject to:1. The paid costs do not exceed the maximum recommended cost. Definition and
Formulation
Outline
Motivation
Definition and Formulation
GRASP
Results and Conclusions
The Mathematical Formulation CC-IP
Subject to:2. The storage and memory capacity should be sufficient large to meet the requirements in each period of time.
Definition and Formulation
Outline
Motivation
Definition and Formulation
GRASP
Results and Conclusions
The Mathematical Formulation CC-IP
Subject to:3. The processing power is at least large enough to satisfy the total demand.
4. The number of selected packages does not exceed the cloud providers limit.
Definition and Formulation
Outline
Motivation
Definition and Formulation
GRASP
Results and Conclusions
The Mathematical Formulation CC-IP
Subject to:5. Guarantee the correct interpretation of variable
6. There will be no gaps of time in feasible solutions.
Definition and Formulation
Outline
Motivation
Definition and Formulation
GRASP
Results and Conclusions
The Mathematical Formulation CC-IP
Subject to:7. An order between the packages should be established and the symmetry should be eliminate.
8. The binary and integrality requirements of the variables.
Definition and Formulation
Outline
Motivation
Definition and Formulation
GRASP
Results and Conclusions
GRASP for Resource Selection in Cloud Exact procedures have often proved incapable of finding solutions as they are extremely time-consuming. • Heuristics and metaheuristics provide sub-
optimal solutions in a reasonable time.
GRASP
Outline
Motivation
Definition and Formulation
GRASP
Results and Conclusions
GRASP for Resource Selection in Cloud Exact procedures have often proved incapable of finding solutions as they are extremely time-consuming. • Heuristics and metaheuristics provide sub-
optimal solutions in a reasonable time.
A Greedy Randomized Adaptive Search Procedure (GRASP) is proposed. GRASP
Outline
Motivation
Definition and Formulation
GRASP
Results and Conclusions
GRASP for Resource Selection in Cloud Exact procedures have often proved incapable of finding solutions as they are extremely time-consuming. • Heuristics and metaheuristics provide sub-
optimal solutions in a reasonable time.
A Greedy Randomized Adaptive Search Procedure (GRASP) is proposed.
The proposed heuristic GraspCC is composed of two phases: • a construction phase coCC• a local search phase lsCC
GRASP
Outline
Motivation
Definition and Formulation
GRASP
Results and Conclusions
GraspCCAdittional Definitions• A solution as a set of 3-tuples representing that package of type was purchased on period .
• Let be the family of all possible solutions.
• Let be the last period that a package was selected.
GRASP
Outline
Motivation
Definition and Formulation
GRASP
Results and Conclusions
GraspCCAdittional Definitions• Define a cost function which will measure the quality of the solution:
GRASP
Outline
Motivation
Definition and Formulation
GRASP
Results and Conclusions
Construction Phase - coCCInitialization• is defined, as the set of packages such that its elements appears in descending order of cost and processing power.
Meeting Disk and Memory RequirementsChoose a package among the first packages to be added to the first period of time while the solution does not satisfy the disk and memory requirements.
Meeting Processing RequirementsThe chosen packages are replicated in future periods until the processing demand is satisfied.
GRASP
Outline
Motivation
Definition and Formulation
GRASP
Results and Conclusions
Local Search Phase - lsCCInitialization• The neighborhood is defined as the family of all solutions obtained by exchanging tuples in with another tuples not in .
• lsCC starts with the solution provided by the construction phase.
Improving solution• It iteratively replaces the current solution by that with minimum cost functionwithin its neighborhood.
Termination• The local search halts when no better solution is found in the neighborhood of the current solution.
GRASP
Outline
Motivation
Definition and Formulation
GRASP
Results and Conclusions
GraspCC
GraspCC consists to perform the coCC following by the lsCC until the maximum number of iterations without improvement in the best solution found is satisfied.
GRASP
Outline
Motivation
Definition and Formulation
GRASP
Results and Conclusions
Preliminary Results Implemented in:
• C • CPLEX 12.4, for mathematical formulation.
Executed on a computer with processor Intel Core i7 3.4Hz and 12Gb of RAM under Linux (Ubuntu 12.04) operating system.
Tested over a set of instances constructed from the requirements of real applications combined with the sets of virtual machine packages available in commercial clouds.
Results and Conclusions
Outline
Motivation
Definition and Formulation
GRASP
Results and Conclusions
Preliminary Results• These instances use requirements of five real applications:• an algorithm for the Quadratic Assignment Problem
that can be solved by a branch-and-bound algorithm;• three applications related to manipulation of biologic
sequences: RAXML, ModelGenerator and Segemehl;• a typical analysis user job for the CMS experiment
running at the LHC/CERN grid.
• They use packages of two commercial clouds:• Amazon EC2, with package groups of high
performance computing (HPC) clusters • Google Cloud Platform, with packages from the
Google Compute Engine
Results and Conclusions
Outline
Motivation
Definition and Formulation
GRASP
Results and Conclusions
Preliminary Results Accomplished experiments:
1. An evaluation of the CC-IP mathematical formulation
2. An evaluation of the GraspCC heuristic
Results and Conclusions
Outline
Motivation
Definition and Formulation
GRASP
Results and Conclusions
Preliminary Results Accomplished experiments:
1. An evaluation of the CC-IP mathematical formulation
2. An evaluation of the GraspCC heuristic
Results and Conclusions
For all experiments, these values for and were considered:
The other used values were: and , equal to the maximum number of packages offered by each cloud provider and .
Outline
Motivation
Definition and Formulation
GRASP
Results and Conclusions
Preliminary Results Accomplished experiments:
1. An evaluation of the CC-IP mathematical formulation
2. An evaluation of the GraspCC heuristic
Results and Conclusions
The objectives of the cost function were normalized due to their distinct range values. - They share the same minimum and maximum values (0 and 1).
- The payment cost was divided by the most expensive package cost times the maximum time informed by the cloud consumer.
- The execution time was divided by the maximum time informed by the cloud consumer.
Outline
Motivation
Definition and Formulation
GRASP
Results and Conclusions
Preliminary Results
Analyzing the different goals in the proposed cost function:(i) the cloud consumer is only concerned with
payment cost ( and )(ii) he only prioritizes the execution time ( and
)
Results and Conclusions
Outline
Motivation
Definition and Formulation
GRASP
Results and Conclusions
Preliminary Results
Analyzing the different goals in the proposed cost function:(i) the cloud consumer is only concerned with
payment cost ( and )(ii) he only prioritizes the execution time ( and
)
Results and Conclusions
For example, nug24-cbb with packages of Amazon(i) 3 time units for execution time and $46.20 for payment cost. Packages set: 8 packages of type 2 (ii) 2 time units for execution time and $84.00 for payment cost. Packages set: 20 packages of type 2
Outline
Motivation
Definition and Formulation
GRASP
Results and Conclusions
Preliminary ResultsComparison of the GraspCC with the CC-IP
Instances
GraspCC CC-IP
Function
cost
Solution value
TotalTime
Gap (%)
Function
cost
Solution Value
Total Time
Time valu
e
Payment
Time Value
Payment
nug22-sbb_am
12 0.0456 1 4.5 0.01 0.0000 0.0456 1 4.5 0.59
nug28-sbb_am
72 0.0128 1 40.8 0.07 0.0000 0.0128 1 40.8 27.23
nug22-cbb_am
12 0.0519 1 11.8 0.03 0.0000 0.0519 1 11.8 0.77
nug28-cbb_am
72 0.0123 1 36.9 0.07 0.0000 0.0123 1 36.9 21.20
nug30-cbb_am
84 0.2652 23 1034.7 3.63 0.0000 0.2652 23 1034.7 118.42
segemehl_am
4 0.1688 1 16.8 0.07 0.0000 0.1688 1 16.8 0.26
cms-1500_am
24 0.1625 4 410.4 0.53 0.0000 0.1625 4 410.4 32.83
nug22-sbb_go
12 0.0497 1 4.9 5.36 0.0066 0.0497 1 4.9 77.72
nug28-sbb_go
72 0.0655 6 87.4 133.66 0.0000 0.0655 6 87.435278.
98nug22-cbb_go
12 0.1137 2 18.6 17.97 0.0000 0.1137 2 18.6 246.79
nug28-cbb_go
72 0.0541 5 70.7 60.00 0.0859 0.0552 5 70.686400.
00nug30-cbb_go
84 0.8502 81 1573.22987.7
90.0000 0.8502 81 1573.2
5085.60
segemehl_go4 0.5038 3 26.2 52.40 0.0000 0.5038 3 26.2 23.52
cms-1500_go24 0.4796 13 573.5 53.27 0.0000 0.4797 13 573.986400.
00
Results and Conclusions
Outline
Motivation
Definition and Formulation
GRASP
Results and Conclusions
Preliminary ResultsComparison of the GraspCC with the CC-IP
Results and Conclusions
Instances
GraspCC CC-IP
Function
cost
Solution value
TotalTime
Gap (%)
Function
cost
Solution Value
Total Time
Time valu
e
Payment
Time Value
Payment
nug22-sbb_am
12 0.0456 1 4.5 0.01 0.0000 0.0456 1 4.5 0.59
nug28-sbb_am
72 0.0128 1 40.8 0.07 0.0000 0.0128 1 40.8 27.23
nug22-cbb_am
12 0.0519 1 11.8 0.03 0.0000 0.0519 1 11.8 0.77
nug28-cbb_am
72 0.0123 1 36.9 0.07 0.0000 0.0123 1 36.9 21.20
nug30-cbb_am
84 0.2652 23 1034.7 3.63 0.0000 0.2652 23 1034.7 118.42
segemehl_am
4 0.1688 1 16.8 0.07 0.0000 0.1688 1 16.8 0.26
cms-1500_am
24 0.1625 4 410.4 0.53 0.0000 0.1625 4 410.4 32.83
nug22-sbb_go
12 0.0497 1 4.9 5.36 0.0066 0.0497 1 4.9 77.72
nug28-sbb_go
72 0.0655 6 87.4 133.66 0.0000 0.0655 6 87.435278.
98nug22-cbb_go
12 0.1137 2 18.6 17.97 0.0000 0.1137 2 18.6 246.79
nug28-cbb_go
72 0.0541 5 70.7 60.00 0.0859 0.0552 5 70.686400.
00nug30-cbb_go
84 0.8502 81 1573.22987.7
90.0000 0.8502 81 1573.2
5085.60
segemehl_go4 0.5038 3 26.2 52.40 0.0000 0.5038 3 26.2 23.52
cms-1500_go24 0.4796 13 573.5 53.27 0.0000 0.4797 13 573.986400.
00
Outline
Motivation
Definition and Formulation
GRASP
Results and Conclusions
Preliminary ResultsComparison of the GraspCC with the CC-IP
Results and Conclusions
Instances
GraspCC CC-IP
Function
cost
Solution value
TotalTime
Gap (%)
Function
cost
Solution Value
Total Time
Time valu
e
Payment
Time Value
Payment
nug22-sbb_am
12 0.0456 1 4.5 0.01 0.0000 0.0456 1 4.5 0.59
nug28-sbb_am
72 0.0128 1 40.8 0.07 0.0000 0.0128 1 40.8 27.23
nug22-cbb_am
12 0.0519 1 11.8 0.03 0.0000 0.0519 1 11.8 0.77
nug28-cbb_am
72 0.0123 1 36.9 0.07 0.0000 0.0123 1 36.9 21.20
nug30-cbb_am
84 0.2652 23 1034.7 3.63 0.0000 0.2652 23 1034.7 118.42
segemehl_am
4 0.1688 1 16.8 0.07 0.0000 0.1688 1 16.8 0.26
cms-1500_am
24 0.1625 4 410.4 0.53 0.0000 0.1625 4 410.4 32.83
nug22-sbb_go
12 0.0497 1 4.9 5.36 0.0066 0.0497 1 4.9 77.72
nug28-sbb_go
72 0.0655 6 87.4 133.66 0.0000 0.0655 6 87.435278.
98nug22-cbb_go
12 0.1137 2 18.6 17.97 0.0000 0.1137 2 18.6 246.79
nug28-cbb_go
72 0.0541 5 70.7 60.00 0.0859 0.0552 5 70.686400.
00nug30-cbb_go
84 0.8502 81 1573.22987.7
90.0000 0.8502 81 1573.2
5085.60
segemehl_go4 0.5038 3 26.2 52.40 0.0000 0.5038 3 26.2 23.52
cms-1500_go24 0.4796 13 573.5 53.27 0.0000 0.4797 13 573.986400.
00
Outline
Motivation
Definition and Formulation
GRASP
Results and Conclusions
Preliminary ResultsComparison of the GraspCC with the CC-IP
Results and Conclusions
Instances
GraspCC CC-IP
Function
cost
Solution value
TotalTime
Gap (%)
Function
cost
Solution Value
Total Time
Time valu
e
Payment
Time Value
Payment
nug22-sbb_am
12 0.0456 1 4.5 0.01 0.0000 0.0456 1 4.5 0.59
nug28-sbb_am
72 0.0128 1 40.8 0.07 0.0000 0.0128 1 40.8 27.23
nug22-cbb_am
12 0.0519 1 11.8 0.03 0.0000 0.0519 1 11.8 0.77
nug28-cbb_am
72 0.0123 1 36.9 0.07 0.0000 0.0123 1 36.9 21.20
nug30-cbb_am
84 0.2652 23 1034.7 3.63 0.0000 0.2652 23 1034.7 118.42
segemehl_am
4 0.1688 1 16.8 0.07 0.0000 0.1688 1 16.8 0.26
cms-1500_am
24 0.1625 4 410.4 0.53 0.0000 0.1625 4 410.4 32.83
nug22-sbb_go
12 0.0497 1 4.9 5.36 0.0066 0.0497 1 4.9 77.72
nug28-sbb_go
72 0.0655 6 87.4 133.66 0.0000 0.0655 6 87.435278.
98nug22-cbb_go
12 0.1137 2 18.6 17.97 0.0000 0.1137 2 18.6 246.79
nug28-cbb_go
72 0.0541 5 70.7 60.00 0.0859 0.0552 5 70.686400.
00nug30-cbb_go
84 0.8502 81 1573.22987.7
90.0000 0.8502 81 1573.2
5085.60
segemehl_go4 0.5038 3 26.2 52.40 0.0000 0.5038 3 26.2 23.52
cms-1500_go24 0.4796 13 573.5 53.27 0.0000 0.4797 13 573.986400.
00
Outline
Motivation
Definition and Formulation
GRASP
Results and Conclusions
Preliminary ResultsComparison of the GraspCC with the CC-IP
Results and Conclusions
Instances
GraspCC CC-IP
Function
cost
Solution value
TotalTime
Gap (%)
Function
cost
Solution Value
Total Time
Time valu
e
Payment
Time Value
Payment
nug22-sbb_am
12 0.0456 1 4.5 0.01 0.0000 0.0456 1 4.5 0.59
nug28-sbb_am
72 0.0128 1 40.8 0.07 0.0000 0.0128 1 40.8 27.23
nug22-cbb_am
12 0.0519 1 11.8 0.03 0.0000 0.0519 1 11.8 0.77
nug28-cbb_am
72 0.0123 1 36.9 0.07 0.0000 0.0123 1 36.9 21.20
nug30-cbb_am
84 0.2652 23 1034.7 3.63 0.0000 0.2652 23 1034.7 118.42
segemehl_am
4 0.1688 1 16.8 0.07 0.0000 0.1688 1 16.8 0.26
cms-1500_am
24 0.1625 4 410.4 0.53 0.0000 0.1625 4 410.4 32.83
nug22-sbb_go
12 0.0497 1 4.9 5.36 0.0066 0.0497 1 4.9 77.72
nug28-sbb_go
72 0.0655 6 87.4 133.66 0.0000 0.0655 6 87.435278.
98nug22-cbb_go
12 0.1137 2 18.6 17.97 0.0000 0.1137 2 18.6 246.79
nug28-cbb_go
72 0.0541 5 70.7 60.00 0.0859 0.0552 5 70.686400.
00nug30-cbb_go
84 0.8502 81 1573.22987.7
90.0000 0.8502 81 1573.2
5085.60
segemehl_go4 0.5038 3 26.2 52.40 0.0000 0.5038 3 26.2 23.52
cms-1500_go24 0.4796 13 573.5 53.27 0.0000 0.4797 13 573.986400.
00
Outline
Motivation
Definition and Formulation
GRASP
Results and Conclusions
Preliminary ResultsComparison of the GraspCC with the CC-IP
Results and Conclusions
Instances
GraspCC CC-IP
Function
cost
Solution value
TotalTime
Gap (%)
Function
cost
Solution Value
Total Time
Time valu
e
Payment
Time Value
Payment
nug22-sbb_am
12 0.0456 1 4.5 0.01 0.0000 0.0456 1 4.5 0.59
nug28-sbb_am
72 0.0128 1 40.8 0.07 0.0000 0.0128 1 40.8 27.23
nug22-cbb_am
12 0.0519 1 11.8 0.03 0.0000 0.0519 1 11.8 0.77
nug28-cbb_am
72 0.0123 1 36.9 0.07 0.0000 0.0123 1 36.9 21.20
nug30-cbb_am
84 0.2652 23 1034.7 3.63 0.0000 0.2652 23 1034.7 118.42
segemehl_am
4 0.1688 1 16.8 0.07 0.0000 0.1688 1 16.8 0.26
cms-1500_am
24 0.1625 4 410.4 0.53 0.0000 0.1625 4 410.4 32.83
nug22-sbb_go
12 0.0497 1 4.9 5.36 0.0066 0.0497 1 4.9 77.72
nug28-sbb_go
72 0.0655 6 87.4 133.66 0.0000 0.0655 6 87.435278.
98nug22-cbb_go
12 0.1137 2 18.6 17.97 0.0000 0.1137 2 18.6 246.79
nug28-cbb_go
72 0.0541 5 70.7 60.00 0.0859 0.0552 5 70.686400.
00nug30-cbb_go
84 0.8502 81 1573.22987.7
90.0000 0.8502 81 1573.2
5085.60
segemehl_go4 0.5038 3 26.2 52.40 0.0000 0.5038 3 26.2 23.52
cms-1500_go24 0.4796 13 573.5 53.27 0.0000 0.4797 13 573.986400.
00
Outline
Motivation
Definition and Formulation
GRASP
Results and Conclusions
Instances
GraspCC CC-IP
Function
cost
Solution value
TotalTime
Gap (%)
Function
cost
Solution Value
Total Time
Time valu
e
Payment
Time Value
Payment
nug22-sbb_am
12 0.0456 1 4.5 0.01 0.0000 0.0456 1 4.5 0.59
nug28-sbb_am
72 0.0128 1 40.8 0.07 0.0000 0.0128 1 40.8 27.23
nug22-cbb_am
12 0.0519 1 11.8 0.03 0.0000 0.0519 1 11.8 0.77
nug28-cbb_am
72 0.0123 1 36.9 0.07 0.0000 0.0123 1 36.9 21.20
nug30-cbb_am
84 0.2652 23 1034.7 3.63 0.0000 0.2652 23 1034.7 118.42
segemehl_am
4 0.1688 1 16.8 0.07 0.0000 0.1688 1 16.8 0.26
cms-1500_am
24 0.1625 4 410.4 0.53 0.0000 0.1625 4 410.4 32.83
nug22-sbb_go
12 0.0497 1 4.9 5.36 0.0066 0.0497 1 4.9 77.72
nug28-sbb_go
72 0.0655 6 87.4 133.66 0.0000 0.0655 6 87.435278.
98nug22-cbb_go
12 0.1137 2 18.6 17.97 0.0000 0.1137 2 18.6 246.79
nug28-cbb_go
72 0.0541 5 70.7 60.00 0.0859 0.0552 5 70.686400.
00nug30-cbb_go
84 0.8502 81 1573.22987.7
90.0000 0.8502 81 1573.2
5085.60
segemehl_go4 0.5038 3 26.2 52.40 0.0000 0.5038 3 26.2 23.52
cms-1500_go24 0.4796 13 573.5 53.27 0.0000 0.4797 13 573.986400.
00
Preliminary ResultsComparison of the GraspCC with the CC-IP
Results and Conclusions
GraspCC presented an outstanding improvement of the execution time, in
average 99% less than the execution time of CC-IP.
HeteroPar 2013
Optimization of a Cloud Resource Management Problem from a Consumer Perspective
Rafaelli de C. Coutinho, Lucia M. A. Drummond andYuri Frota
Fluminense Federal University – UFF Brazil
Sponsorship:
Outline
Motivation
Definition and Formulation
GRASP
Results and Conclusions
Local Search Phase - lsCC
GRASP