By Bryen J.

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These throughputs then characterize the aggregate server. Exact aggregation is possible when the overall queueing network model is product-form, such that a subnetwork can be substituted by an aggregate server. , the maximum number of transactions that can be activated in the computer system is limited. Examples of applying aggregation in queueing networks appear in [ThNa81],[Lave83],[LZGS84]. Hierarchical analytic solutions typically consist of a lower level closed queueing network model, which is analyzed to obtain the throughput characteristic of the aggregate server which replaces the queueing network.

A careful validation requires experimentation with a larger set of input parameters, as weil as the validation of lower level performance measures. , [RyTh90a]. This is because validation may be carried out in a bottom-up manner, to ensure that errors at lower levels do not propagate to higher levels (refer to Figures 4 and 6 in [RyTh90a]). Assuming that it is known from simulation results that the effect of deadlocks on the performance of the standard locking system is negligibly small [ThRy91],[Thom93b], then the analysis should take into account only the mean transaction blocking time, which equals the product of the mean number of lock requests per transaction, the probability of lock conflict (Pe), and the mean waiting time per lock conflict (W).

11) [ThRy91]. 51X + 1)P - IX = O. 12) It is stated in [TayY90] that "As yet, there are no proposed measures for the resource requirements of a given concurrency control algorithm". Note that IX is a single measure, which determines the level of lock contention for standard locking. Two different systems will have the same lock contention level as long as they have the same value for IX. 1 that the value of IX for fixed size transactions is one sixth of the IX for transactions with a geometric transaction size distribution and the same mean size.