  In this paper we investigate a new computing paradigm, called SocialCloud, in
which computing nodes are governed by social ties driven from a bootstrapping
trust-possessing social graph. We investigate how this paradigm differs from
existing computing paradigms, such as grid computing and the conventional cloud
computing paradigms. We show that incentives to adopt this paradigm are
intuitive and natural, and security and trust guarantees provided by it are
solid. We propose metrics for measuring the utility and advantage of this
computing paradigm, and using real-world social graphs and structures of social
traces; we investigate the potential of this paradigm for ordinary users. We
study several design options and trade-offs, such as scheduling algorithms,
centralization, and straggler handling, and show how they affect the utility of
the paradigm. Interestingly, we conclude that whereas graphs known in the
literature for high trust properties do not serve distributed trusted computing
algorithms, such as Sybil defenses---for their weak algorithmic properties,
such graphs are good candidates for our paradigm for their self-load-balancing
features.
