  We consider a \emph{Social Group} of networked nodes, seeking a "universe" of
segments for maximization of their utility. Each node has a subset of the
universe, and access to an expensive link for downloading data. Nodes can also
acquire the universe by exchanging copies of segments among themselves, at low
cost, using inter-node links. While exchanges over inter-node links ensure
minimum or negligible cost, some nodes in the group try to exploit the system.
We term such nodes as `non-reciprocating nodes' and prohibit such behavior by
proposing the "Give-and-Take" criterion, where exchange is allowed iff each
participating node has segments unavailable with the other. Following this
criterion for inter-node links, each node wants to maximize its utility, which
depends on the node's segment set available with the node. Link activation
among nodes requires mutual consent of participating nodes. Each node tries to
find a pairing partner by preferentially exploring nodes for link formation and
unpaired nodes choose to download a segment using the expensive link with
segment aggressive probability. We present various linear complexity
decentralized algorithms based on \emph{Stable Roommates Problem} that can be
used by nodes (as per their behavioral nature) for choosing the best strategy
based on available information. Then, we present decentralized randomized
algorithm that performs close to optimal for large number of nodes. We define
\emph{Price of Choices} for benchmarking performance for social groups
(consisting of non-aggressive nodes only). We evaluate performances of various
algorithms and characterize the behavioral regime that will yield best results
for node and social group, spending the minimal on expensive link. We consider
social group consisting of non-aggressive nodes and benchmark performances of
proposed algorithms with the optimal.
