A stochastic evaluation model for database organizations in data retrieval systems
Experimental work in the valuation of large scale data retrieval systems has been scarce due to its difficulty and prohibitive cost. This paper discusses a simulation model of a data retrieval system which has the effect of significantly reducing the cost of experimentation and enabling research never attempted before. The model is designed to estimate the retrieval workload of alternative data retrieval systems. These data retrieval systems can be organized under several database organizations, including inverted list, threaded list, and cellular list organizations and hybrid combinations of these systems. Effectiveness of the methodology is demonstrated by using the model to study the effect of database organizations in data retrieval systems. In particular, the impact of query complexity is analyzed.