  With social networking sites providing increasingly richer context,
User-Centric Service (UCS) creation is expected to explode following a similar
success path to User-Generated Content. One of the major challenges in this
emerging highly user-centric networking paradigm is how to make these exploding
in numbers yet, individually, of vanishing demand services available in a
cost-effective manner. Of prime importance to the latter (and focus of this
paper) is the determination of the optimal location for hosting a UCS. Taking
into account the particular characteristics of UCS, we formulate the problem as
a facility location problem and devise a distributed and highly scalable
heuristic solution to it.
  Key to the proposed approach is the introduction of a novel metric drawing on
Complex Network Analysis. Given a current location of UCS, this metric helps to
a) identify a small subgraph of nodes with high capacity to act as service
demand concentrators; b) project on them a reduced yet accurate view of the
global demand distribution that preserves the key attraction forces on UCS;
and, ultimately, c) pave the service migration path towards its optimal
location in the network. The proposed iterative UCS migration algorithm, called
cDSMA, is extensively evaluated over synthetic and real-world network
topologies. Our results show that cDSMA achieves high accuracy, fast
convergence, remarkable insensitivity to the size and diameter of the network
and resilience to inaccurate estimates of demands for UCS across the network.
It is also shown to clearly outperform local-search heuristics for service
migration that constrain the subgraph to the immediate neighbourhood of the
node currently hosting UCS.
