Multi-objective evolutionary algorithms for unstructured P2P topologies reconfiguration
Resumen: Nowadays one of the main usages of the Internet is content generation, sharing and access. One of the approaches used to support these activities is the P2P model. In content distribution systems using this model, instead of having servers to distribute the contents, nodes are selforganized to do it. Each node is a potential server and a client and this characteristic makes those systems naturally scalable and fault tolerant. The nodes of a P2P system establish logical connections between them and those connections define an overlay network (called P2P network). There are two main classes of P2P networks: structured and unstructured. In the first class a specific geometry for the topology is predefined and the logical connections between nodes are determined by this geometry. In the second class, in which we are interested, there are no specific rules to define the neighborhood of a newcomer. The goal of these protocols is to preserve the connectivity. In this project we are interested in the exploration of distributed control, local information multiobjective evolutionary algorithms as a strategy to perform periodic reconfiguration of unstructured P2P topologies.
- The design and implementation of an effective and efficient multi-objective evolutionary algorithm to perform the reconfiguration of an unstructured P2P topology
- Identify and understand the different distributed control, local information multi-objective evolutionary algorithms proposed to perform the reconfiguration of an unstructured P2P topology
- Design a distributed control, local information multi-objective evolutionary algorithm to perform reconfiguration in unstructured P2P topologies
- Evaluate the proposed algorithm
- Assess the relative importance of the different objectives used in the reconfiguration of an unstructured topology
Última actualización: June 3, 2016 at 0:20 am