Optimization of Transmission Signal Power through Observation of Congestion in VANets Using the Fuzzy Logic Approach: A Case Study in Highway and Urban Layout

Algorithm 7

Classification of the local congestion level.

// Fuzzy inference system

// Initial setting

updateNeighbors ← getNeighborhood ();

currentSpeed ← getSpeed ();

(5) currentDensity ← getDensity (updateNeighbors);

(6)

(7) // Fuzzification

(8) // Input variables

(9) fzSpeed ←fuzzification (currentSpeed);

(10) fzDensity←fuzzification (currentDensity);

(11)

(12) // In: membership functions

(13) foreach membershipFuncIn[i] ∈ getRuleWith (↩

    fzSpeed, fzDensity) do

(14)

(15)   // Fuzzy inference engine with set of rules

(16)   membershipFuncOut[i] ←fuzzyInference (↩

    membershipFuncIn[i]);

(17) done

(18)

(19) // Out: membership functions

(20) foreach fzOut[i] ∈ membershipFuncOut () do

(21)

(22)   // Defuzzification with Eq. (2)

(23)   FzTraffic ← defuzzification (fzOut[i]);

(24) done

(25)

(26)

(27)   if  ( fzTraffic <= 0.28) then

(28)   congestion ← setFreeLevel (fzTraffic);

(29)

(30)  else if  (fzTraffic <= 0.54) then

(31)   congestion ← setWeakLevel (fzTraffic);

(32)

(33) else if  (fzTraffic <= 0.8) then

(34)   congestion ← setModerateLevel (fzTraffic);

(35)

(36)  else

(37)   congestion ← setSevereLevel (fzTraffic);

(38)

(39) end

(40)

(41) return (congestion);