Method to get object based on probability distribution
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Hi
I need to implement a network protocol slot selection mechanism as described in this research paper( Sift: A MAC Protocol for Event-Driven Wireless Sensor Networks ) where each slot from 1 to Cw like (1 to 10 when Cw=10) has increasing geometric non uniform probability distribution. Alpha is b/w 0.7 and 0.8, r is slot number from 1 to 10.
The probability mass function Pr has values greater than 1 and it equals as shown in figure
I have to now write a function that should give me a slot from (1 to 10), when called, each time but as slots from 1 to 10 has increasing probability of selection then one would expect that 10 would be given more preference then 1 and the function must give values according to probability of each slot from 1 to 10. So how could i write this logic?
Is fitting in any one distribution like exponential necessary? . Even after determining that if this fits in exponential distribution with mu 'x' how can i let my function choose (randomly) slot with biasing to higher number of slots then starting ones?
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