Computer Science Evolutionary Computation Genetic Algorithms Memetic Algorithms Ephemeral Computing

1. A Study of the Performance of Self-✭ Memetic
Algorithms on Heterogeneous Ephemeral Environments
Rafael Nogueras & Carlos Cotta
Dpto Lenguajes y Ciencias de la Computación, Universidad de Málaga
PPSN 2016
Edinburgh, Scotland
EphemeC
H
TIN2014-56494-C4-1-
P
Use of parallel and distributed models of EAs to improve solution quality and reduce computational times.
The island model spatially organizes populations into partially isolated panmictic demes.
Two emergent computational environments: P2P networks and desktop grids.They are dynamic and unstable.
Churn: the combined effect of multiple computing nodes leaving and entering the system along time.
Scale-free topology (Barabási-Albert model)
Platforms with many nodes
Instability
FaultTolerance
Self-Rewiring: Node failures disrupt the
network and limit the flow of information ⇒
Dynamic Rewiring: when the number of
neighbors of an island is below a threshold
additional neighbors are searched.
Self-Sampling: Prevent randomness when an
island increases its size ⇒ EDAs to estimate
the population of each island to be enlarged
generating new individuals by sampling.
Each node i has a certain computing power, iN+ but the overall computational power of the network is the same in all cases Wii.
Four different scenarios regarding the distribution of power of all nodes:
 Uniform: the overall computing power is distributed among nodes.
 Random: each coefficient i can have a uniformly random value in {1,…,Wn+1}, subject to Wii.
 Binomial: coefficients can take values in {1,…,Wn+1} and the probability of a certain value  is p()C(Wn, 1)qw-1(1-q)  n-w+1, with q1/n.
 Power Law: coefficients are grouped in r levels, where r{0,…,rmax} with rmax=log2n1.
• Resilience to deal with the
fluctuating computational landscape
because of volatility and
heterogeneity.
• Self-✭ properties are an effective
solution.
• Self-scaling and self-healing are
robust under different
configurations
FutureWork
Extend the range of scenarios
considered in terms of heterogeneity
and volatility.
The algorithm adjust the search strategy
during runtime.
Memetic Computing: memes representing
problem solving strategies are explicitly
represented and evolved.
We use the model of J. Smith, whereby memes
are variable-length pattern rewriting rules
attached to genotypes and evolving alongside
them.
The algorithm changes its structure in response
to variations in the problem or environment.
Islands dynamically change their size in the
presence of churn:
• If a neighboring island goes down, an island
increases its size
• Active islands exchange individuals in order
to balance their sizes (self-balancing)