Using Free Cloud Storage Services For DistributedEvolutionary Algorithms

Maribel García-Arenas,

Juan-J. Merelo,

Antonio M. Mora,

Pedro Castillo

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Outline

Idea and how to test it

Dropbox features

Putting in practice with Evolutionary Computation

File-individuals

Island Algorithm

Goals

Problems

Results

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IDEA

What do you know about cloud storage services?

Why not use them for computing?How can we use all our computers to

make a multicomputer?Desktop computerPortable computerHome computerAny other computers...

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How to test the ideaLook for some free storage

services and test them: What are their features and what is the availability for storing, sharing and synchronizing information

After that, We have selected Dropbox

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Dropbox TM features

It is free up to a certain level of use (measured in traffic and usage)

It is popular, so many people use it, and we may found many volunteers for computation

It monitors the local filesystem and uploads information asynchronously

It looks like a local directory

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Putting in practice with Evolutionary Computation

What do we need to build Evolutionary Distributed Algorithms?Exchange individuals among populations:

Phenotype and Genotype

We can exchange this information using files. So the name of the file represents the phenotype and genotype and all connected PCs share it with Dropbox

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Let's go

File distribution via Dropbox It synchronizes the file-individuals with

other computersEach computer evolves an islandDropbox folder contains a pool of

individuals and each computer adds and gets file-individuals from it

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Let's go (II)

Each computer connected or synchronized by Dropbox is part of a multi-computer

Each Island-computer evolves a population of individuals and exchanges with the pool file-individuals when the migration process must be done

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File-individuals

How to include phenotype and genotype into a fileAs the contents of the file? It is not a good

idea because we have to open and close files and Dropbox has to synchonize them.

Into the filesystem attributes? Dropbox is working on that and we will be testing in the future

Into the filename? It is our approach

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File-individuals (II)

The filename problemHow many gens can we include into the

name?We have to code the genotype into base 32Ex: 00000 → 0, 00001-> 1, 01010->A ...

111111->V

The filename includes: Fitness, genotypeBase32codification and the id of the computer which generates the individual

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Island AlgorithmCreates and evaluates the initial population

Until to reach a number of evaluations into the multi-computer

Breed the population

Evaluate

Generational replacement with 1-elitism

After a fixed number of generations, Immigrate (gets one file-individual from the pool and incorporates it to the population)

After a fixed number of generations, Migrate (adds the best or a random file-individual to the pool)

Adds the best individual to the pool

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Control of the number of evaluations

Each computer creates a file whose name is the number of evaluations performed and its identification (random initial seed)

Each computer looks for this kind of file within the Dropbox folder and adds the total of evaluations.

When the sum of this evaluations is greater than the fixed minimum, the evolution of this island ends.

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Goals

What do we want to test?We want test if we save time when use the

multi-computer for computing a fixed number of evaluations.

How can we test it?Making a distributed evolutionary algorithm

based on pool and testing that the time for reaching the fixed evaluations decreases when you add new nodes to our multi-computer linked by Dropbox.

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Problems: MMDP

Multimodal Deceptive Problem

It is composed of k (k=80) subproblems of 6 bits each one called s

i for i=0 to 79.

Depending of the number of ones s

i takes the values

detailed into the table

Fitness individual=∑i=1

k fitness si

ones fitness

0 or 6 1

5 or 1 0

2 or 4 0,360384

3 0,640576

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Problems: TRAP

It is defined for the unitation function (number of ones in a binary string) using the following function.

For our problem, the trap is defined for l=4, a=3, b=4 and z = 3

With 30 traps

into the genome

trap u x=az z−u x , if u x zbl−z ux−z , otherwise{

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ParametersWe use as multi-computer one, two or four

heterogeneous computers so we use one, two, three or four island

Population size: 1000 individuals

Selection: Tournament

Crossover: uniform

Mutation: bit-flit

Replacement: Generational with 1-elitism

Stop criteria: minimum number of evaluations for the multi-computer

WiFi with WPA/Enterprise encryption.

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Results for MMDP

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Results for TRAP

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Conclusions

The Dropbox File-storage and sharing system, can be used as a migration device for distributed evolutionary computation experiments without needing to acquire or set up complicated cloud or grid infrastructure.

With this approach everyone can use a multicomputer running an evolutionary algorithm with a good scaling behavior.

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Others results for MMDP

100 200 400

0

20

40

60

80

100

120

Success Rate

124

Migration frecuency

Per

cent

age

1 2 4

0

50000

100000

150000

200000

250000

300000

Time to find the solution

MMDP Problem

100200400

Islands

Tim

e(m

ilise

cond

s)

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Questions