Abstract
Data intensive parallel applications are harder to protect against transient software and hardware failures compared to traditional parallel applications. Due to the need for distributed data replication, the CAP Conjecture and Theorem define the ultimate limits for data intensive application's reliability, availability and overall scalability. This paper examines the two assumptions in the proof of CAP Theorem and proposes a statistic multiplexing paradigm for eliminating the reliability, availability and scalability limits of data intensive parallel applications.
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