[e2e] on detecting social nets and using them for optimising dtn forwarding algorithms

Jon Crowcroft Jon.Crowcroft at cl.cam.ac.uk
Thu May 10 02:19:13 PDT 2007

the following technical report
is available for your perusal. Due to circumstances beyond
our control, we won't be talking about it in Kyoto
unless you want to chat in the baths or temples...

Bubble Rap: Forwarding in small world DTNs in ever decreasing circles

In this paper we seek to improve understanding of the structure of human mobility, and to use this in the
design of forwarding algorithms for Delay Tolerant Networks for the dissemination of data amongst mobile users.

Cooperation binds but also divides human society into communities. Members of the same community interact with
each other preferentially. There is structure in human society. Within society and its communities, individuals
have varying popularity. Some people are more popular and interact with more people than others; we may call
them hubs. Popularity ranking is one facet of the population. In many physical networks, some nodes are more
highly connected to each other than to the rest of the network. The set of such nodes are usually called
clusters, communities, cohesive groups or modules. There is structure to social networking. Different metrics
can be used such as information flow, Freeman betweenness, closeness and inference power, but for all of them,
each node in the network can be assigned a global centrality value.

What can be inferred about individual popularity, and the structure of human society from measurements within a
network? How can the local and global characteristics of the network be used practically for information
dissemination? We present and evaluate a sequence of designs for forwarding algorithms for Pocket Switched
Networks, culminating in Bubble, which exploit increasing levels of information about mobility and interaction. 

with apologies to magritte,
ceci n'est pas un sigcomm papier

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