1. An Evolutionary Bluetooth Scatternet Formation Protocol Students: Mirko Gilioli Elallali Mohammed

2. Introduction 802.11 based ad hoc network Bluetooth

3. Scatternet formation algorithm Introduction to genetic algorithm Start : n candidate solutions ( strings of 0s and 1s). Start : n candidate solutions ( strings of 0s and 1s). Fitness : f(x) ? Fitness : f(x) ? New population New population  Selection : 2 parents ( based on f(x) ).  Crossover & Mutation : may cross over the parents →offspring. →offspring.  Accepting: Reject or accept the new population.  Replace: Replace old with new population.  Test : Test problem criterium.

4. Genetic scatternet formation algorithm (1) Phase 1: Role determination Start : Groups ( Masters, slaves & bridges). Start : Groups ( Masters, slaves & bridges). Fitness : Min_masters, Max_slaves, Ok bridges. Fitness : Min_masters, Max_slaves, Ok bridges. New population New population  Selection: two parent groups ( from half the population).  Crossover → new childreen.  Mutation : Childreen mutated, placed in new population.

5. Genetic scatternet formation algorithm (2) Phase 2: Connection establishment

6. Number of Piconets and Number of bridges vs. Number of nodes

7. Execution Time and Number of Generation vs. Number of nodes

8. Conclusions If the number of nodes is increased beyond a threshold value (40 nodes), the performance degrades significantly. However, when the population size is increased, this allows to find a best solution quickly.