A Novel Adaptive Cuckoo Search for Optimal Query Plan Generation

Algorithm 2

Input: A collection of RDF files containing subject, predicate and objects

     RDF query

     Number of Generations

Output: Optimal query plan

Step  1. Randomly generate initial population of query plans.

Step  2. Evaluate the cost of each plan based on the cardinality as given in the cost model.

Step  3. Sort the query plans based on fitness value and find the median of fitesses. Let be the median (threshold) value.

      Based on value of set the value of

Step  4. Select a random egg from sorted population using levy flight.

Step  5. Compare the cost of with and replace with if cost() < cost().

Step  5. Abandon a fraction of worst query plans based on the value of .

Step  6. Keep the best query plans.

Step  7. Rank the current solutions and find the current best. Rank the fittest solution as the best and the less fit solution

      as the worst.

Step  8. Pass the best query plans to next generation.