Paper Info
Title
Parallel Evolutionary P2P Networking for Realizing Adaptive Large-Scale Networks
Abstract
The present paper proposes a parallel evolutionary P2P networking technique (P-EP2P) that applies an evolutionary networking technique (EP2P) in parallel to small networks into which an entire P2P network is divided. EP2P dynamically and adaptively optimizes several P2P network topologies, in which all of the nodes are included at the same time, in an evolutionary manner. However, EP2P has a scalability problem that load is more concentrated in a particular node as the number of nodes increases. The aim of P-EP2P is to first balance load among the nodes to maintain the function of the entire network and then bring adaptability even to a large-scale P2P network. Simulation results reveal that P-EP2P is capable of balancing load among the nodes, but degrades search reliability as the number of the small networks increases, which indicates that there is a trade-off relationship between the load balancing and the search reliability. The results suggest that to enhance the search reliability, the small networks should exchange information among them to maintain consistency of the network topologies, though that causes additional load to the nodes.
Year
DOI
Venue
2011
10.1109/SAINT.2011.98
Applications and the Internet
Keywords
Field
DocType
parallel evolutionary,load balancing,additional load,p2p networking,nodes increase,p2p network topology,p2p network,network topology,balance load,small network,entire network,search reliability,realizing adaptive large-scale networks,load balance,resource allocation,evolutionary algorithm,topology,adaptability,reliability,evolutionary computation,couplings
Network Load Balancing Services,Evolutionary algorithm,Computer science,Load balancing (computing),Computer network,Evolutionary computation,Active networking,Network topology,Resource allocation,Distributed computing,Scalability
Conference
ISBN
Citations 
PageRank 
978-0-7695-4423-6
2
0.39
References 
Authors
8
2
Name
Order
Citations
PageRank
Kei Ohnishi13917.71
Yuji Oie237868.37