Fuzzy logic examples in network applications.

1. Fuzzy Logic and Adaptive Sampling Edwin Hernandez HCS - Lab

3. Membership functions Triangular T() and trapezoidal Trap() All parameters are represented as T(), Trap() or Impulse()

4. FLC membership functions  deltaV (NC)=T(NC:0, D1, 0)  deltaV (CS)=T(CS:D1, D2,D3)  deltaV (CL)=T(CL:D2, D3, D4)  deltaV (CM)=T(CM:D3, D4, D5)  deltaV (CH)=T(CH:D4, D5, D6) NC: No change CS: Change-Slightly CL: Change-Low CM: Change-Medium CH: Change-High DeltaV (Change of Value)

5. Membership functions  deltaT (Low)=Trap(Low:1, T1, T2)  deltaT (med-low)=T(med-low:T1, T2,T3)  deltaT (medium)=T(medium:T2, T3, T4)  deltaT (med-high)=T(med-high:T3, T4, T5)  deltaT (high)=Trap(high:T4, T5, Tmax) deltaT Timming

6. Membership Functions  output (DH)=Trap(Low:-O1, -O2, -O3)  output (DM)=T(DM:-O2, O3,0)  output (NC)=T(NC:-O3, 0, O4)  output (IM)=T(IM:0, O3, O4)  output (IH)=Trap(IH:O4, O5, O6) Output Inc/dec timmers DH: decrease high DM: decrease medium NC: No change IM: Increase more IH: Increase High

11. MAX-MIN method

12. MAX-DOT Pseudo-code float Output[]; Value[] = GetMembership(inputV, DeltaV[]); // returns a value for Value_chLow, Value_nochange, etc Timming[] = GetMembership(inputT, DeltaT[]); // returns a value for Timming_low, Timming_High, etc For each rule if rule[I] applies then // depending on the Rule Timming/Value applies // and are used in the array Output[] = MAX(Value[I]*Timming[I], Output[]); end; return Defuzzify(Output[])

13. Other Applications ATM Admission control and congestion control

14. FLC:ATM Switcher [1]

15. FLC : Rules and Membership functions

16. FLC: Rules for the Fuzzy Congestion Controller

17. FLC: Defuzzification Rules 1, 2, 4,5,6 apply for IM Tsukamoto’s defuzzification method