Workshop on Online Social
December 7, 2007.
matters: Using Social Network Analysis to Improve Network and Mechanism
Buchegger (DT-labs, Berlin)
Network nodes may experience large disparities in utility according
to their location in the network topology. These disparities become more
problematic in resource-constrained self-organized networks, such as mobile
ad-hoc, peer-to-peer, wireless mesh, or sensor networks, than they have been
in traditional infrastructure-based networks. The impact of node location has
so far received relatively little attention, e.g. it is common practice to
assume the random-waypoint mobility model in mobile ad-hoc networks, implying
that over time node location will be evenly distributed. We are interested in
the effect of location on node utility when this assumption is removed.
Applying insights from social network analysis, we introduce
centrality metrics and quantify the effect of location and several network
topologies. As a concrete application of the general problem, we investigate
how incentives for cooperation (such as payment or reputation systems for
traffic relay in mobile ad-hoc networks) exacerbate or alleviate node utility
disparities due to location. We show
that location matters and that without location awareness, such incentive
schemes can be unfair.
We propose the use of centrality metrics, combine them with metrics
from economics, and discuss their impact on the following networking research
areas: mobility models, strategic node behavior (location changes), placement
of access points in wireless mesh networks, topology control of overlay
networks, location-aware incentives for cooperation, and evaluation of
fairness of networking protocols.