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1) Availability of Computational Resources
In the case of traditional cloud computing, availability on demand is essential for many cloud customers. Social Cloud Computing doesn't provide this availability guarantee because in a P2P environment, peers are usually those using only mobile devices and they may enter or leave the P2P network at any time. The only relatively successful use cases as of recent years are those which do not require real time results, only computation power for a small subset or module of a larger algorithm or data set.
2) Trust and Security
Unlike large scale data centers and company brand image, people may be less likely to trust peers vs. a large company like Google or Amazon. Running some sort of computation with sensitive information would then need to be encrypted properly and the overhead of that encryption may render the usefulness of the product minimal. When resources are distributed in small pieces to many people for computations, inherent trust must be placed in the client, regardless of the encryption that may be promised to the client.
3) Reliability
Similar to availability, reliability of computations must be consistent and uniform. If computations offloaded to the client are continuously interreupted, some mechanism for detecting this much be in place such that the client may know the computation is tainted or needs to be completely re-run.
==See also==
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