On the Impact of Path Redundancy Awareness in Evolutionary P2P Networking

Abstract

A P2P system is composed by autonomous nodes interconnected to share resources. The interconnections between the nodes define the P2P topology that is traversed to lookup resources. As nodes are autonomous, they are free to decide when to arrive and leave and what resources to share and download. To cope with this dynamism, the Evolutionary P2P Networking approach performs a periodical P2P topology reconfiguration applying evolutionary computation and using the amount of successful lookups as the evaluation function that drives the process. We extended this approach to also consider, as a part of the evaluation function, the creation of redundant paths in the topology and, additionally, we introduced elitism to improve the evolutionary process. In this work we present an extensive evaluation of both approaches. The results show that our approach scales better and produces more connected topologies. The improved connectivity ensures a higher rate of successful lookups under static and dynamic scenarios.

Parallel Evolutionary Peer-to-Peer Networking in Realistic Environments

“…So, we here describe researches on optimization of P2P network topologies by computational intelligence techniques. First, except our previous studies [4][5][6], there is only one study on the evolutionary P2P networking technique (EP2P) [12]. This study dealt with not the parallel evolutionary P2P networking technique (P-EP2P) but EP2P in which only one node group exists and proposed two methods for maintaining diversity of network topologies as a population of the evolutionary algorithm.…”

“…The first method proposed in [12] is to devise a fitness function to maintain network topologies that include various links between nodes in a population. The method introduces an index that measures degree of overlap of links between network topologies, which was named "repetition factor," and if multiple network topologies providing the same search success rate exist, the method preferentially takes network topologies with lower degree of the link overlap.…”