Name
Abstract | ||
|---|---|---|
Particle Swarm Optimization is a parallel algorithm that spawns particles across a search space searching for an optimized solution. Though inherently parallel, they have distinct synchronizations points which stumbles attempts to create completely distributed versions of it. in this paper, we attempt to create a completely distributed peer-peer particle swarm optimization in a cluster of heterogeneous nodes. Since, the original algorithm requires explicit synchronization points we modified the algorithm in multiple ways to support a peer-peer system of nodes. We also modify certain aspect of the basic PSO algorithm and show how certain numerical problems can take advantage of the same thereby yielding fast convergence. |
Year | DOI | Venue |
|---|---|---|
2012 | 10.1109/ICGEC.2012.27 | ICGEC |
Keywords | Field | DocType |
parallel algorithms,particle swarm optimisation,search problems,PSO algorithm,explicit synchronization points,parallel algorithm,peer-peer particle swarm optimization,search space,distributed,fault tolerance,load balance,particle swarm optimization,peer-peer,strategic niching,strategic skip | Convergence (routing),Particle swarm optimization,Mathematical optimization,Synchronization,Parallel algorithm,Computer science,Load balancing (computing),Multi-swarm optimization,Fault tolerance,Particle swarm optimizer | Conference |
ISSN | Citations | PageRank |
1949-4653 | 1 | 0.40 |
References | Authors | |
10 | 2 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Hrishikesh Dewan | 1 | 13 | 3.72 |
| V. Susheela Devi | 2 | 47 | 9.21 |