  Information dissemination is a fundamental and frequently occurring problem
in large, dynamic, distributed systems. In order to solve this, there has been
an increased interest in creating efficient overlay networks that can maintain
decentralized peer-to-peer networks. Within these overlay networks nodes take
the patterns of small world networks, whose connections are based on proximity.
These small-world systems can be incredibly useful in the dissemination and
lookup of information within an internet network. The data can be efficiently
transferred and routing with minimal information loss through forward error
correct (FEC) and the User Datagram Protocol (UDP). We propose a networking
scheme that incorporates geographic location in chord for the organization of
peers within each node's partitioned key space. When we combine this with a
proximity-based neighborhood set {based on the small world structure} we can
mimic the efficient of solutions designed to solve traditional small-world
problems, with the additional benefit of resilience and fault-tolerance.
Furthermore, the routing and address book can be updated based on the
neighborhood requirements. The flexibility of our proposed schemes enables a
variety of swarm models, and agents. This enables our network to as an
underlying networking model that can be applied to file-sharing, streaming, and
synchronization of networks.

Networking and Internet Architecture;Neural and Evolutionary Computing