Performance modelling and comparisons of global shared buffer management policies in a cluster environment

Clustering multiple computing nodes has become increasingly popular for reasons of capacity, availability and cost. One approach to clustering is the data sharing approach where a number of loosely coupled nodes share a common database. In this environment, a global shared buffer can be introduced to alleviate the multisystem invalidation effect either as a disk cache or shared intermediate memory. We develop an analytic model to evaluate different shared buffer management policies (SBMPs) which differ in their choice of data granules to be put into the shared buffer. The methodology analyzes all policies using a uniform framework by decomposing the input stream to the shared buffer into multiple (three) component streams based on their effects on the dependency between the private and shared buffer contents. This approach simplifies the problem of analyzing different SBMPs into 1) estimating the rate of each component stream, and 2) evaluating the impact of dependency on each type of component stream and hence the shared buffer hit probability. A detailed simulation model is also developed to validate the analytic model. We also illustrate how the analytic buffer model can be integrated with other system submodels to examine trade-offs between the SBMPs and to estimate optimal shared buffer allocations from a cost-performance point of view