servidor windows costo $ 100,000 hasta $ 200,000 actualizacion de software $ 275,000 a $ 500,000. capacitacion $9,000 a $10,000
Windows min $384000 max $710,000 estimado 435,000
servidor linux costo $ 80,000 hasta $ 210,000. actualizacion de software $ 250,000 a $ 525,000. capacitacion $ 8,000 a $ 17,500
Linux min 338000 max 752500 estimado 410000
get_montecarloest <- function(vmin,vmax,vest){
mn <- (vmin + 4*vest + vmax)/6
s <- abs((vmax - vmin)/6)
valmontecarlo <- rnorm(1, mean=mn, sd=s)
return(valmontecarlo)
}
get_sim<-function(x,vmin,vmax,vest){
times <- get_montecarloest(vmin,vmax,vest)
return (times)
}
hacemos test de la funcion de montecarlo
get_montecarloest(384000,710000,410000)
aplicamos la funcion para windows y linux con 10000 iteraciones
simulacion<-10000
sim_win<-sapply(1:simulacion, get_sim,vmin=384000,vmax=710000,vest=435000)
sim_lin<-sapply(1:simulacion, get_sim,vmin=338000,vmax=752500,vest=410000)
print(paste("windows: ",mean(sim_win)," Linux:", mean(sim_lin)))
[1] "windows: 471830.746806248 Linux: 455568.007223083"
La mejor opcion es linux
LS0tDQp0aXRsZTogIlNpbXVsYWNpb24gbW9udGVjYXJsbyINCm91dHB1dDogaHRtbF9ub3RlYm9vaw0KLS0tDQpzZXJ2aWRvciB3aW5kb3dzIGNvc3RvICQgMTAwLDAwMCBoYXN0YSAkIDIwMCwwMDANCmFjdHVhbGl6YWNpb24gZGUgc29mdHdhcmUgICQgMjc1LDAwMCBhICQgNTAwLDAwMC4gDQpjYXBhY2l0YWNpb24gJDksMDAwIGEgJDEwLDAwMA0KDQoNCg0KV2luZG93cyBtaW4gJDM4NDAwMCBtYXggJDcxMCwwMDAgZXN0aW1hZG8gIDQzNSwwMDAgDQoNCnNlcnZpZG9yIGxpbnV4ICBjb3N0byAkICA4MCwwMDAgaGFzdGEgJCAgMjEwLDAwMC4NCmFjdHVhbGl6YWNpb24gZGUgc29mdHdhcmUgICQgMjUwLDAwMCBhICQgNTI1LDAwMC4gDQpjYXBhY2l0YWNpb24gJCA4LDAwMCBhICQgMTcsNTAwIA0KDQpMaW51eCBtaW4gMzM4MDAwICBtYXggNzUyNTAwIGVzdGltYWRvIDQxMDAwMA0KDQoNCmBgYHtyfQ0KZ2V0X21vbnRlY2FybG9lc3QgPC0gZnVuY3Rpb24odm1pbix2bWF4LHZlc3Qpew0KICAgIG1uIDwtICh2bWluICsgNCp2ZXN0ICsgdm1heCkvNg0KICBzIDwtIGFicygodm1heCAtIHZtaW4pLzYpDQogIA0KICB2YWxtb250ZWNhcmxvIDwtIHJub3JtKDEsIG1lYW49bW4sIHNkPXMpDQogIA0KICByZXR1cm4odmFsbW9udGVjYXJsbykNCn0NCg0KZ2V0X3NpbTwtZnVuY3Rpb24oeCx2bWluLHZtYXgsdmVzdCl7DQogICAgDQogICAgdGltZXMgPC0gZ2V0X21vbnRlY2FybG9lc3Qodm1pbix2bWF4LHZlc3QpDQogICAgcmV0dXJuICh0aW1lcykNCn0NCmBgYA0KaGFjZW1vcyB0ZXN0IGRlIGxhIGZ1bmNpb24gZGUgbW9udGVjYXJsbw0KDQpgYGB7cn18DQpnZXRfbW9udGVjYXJsb2VzdCgzODQwMDAsNzEwMDAwLDQxMDAwMCkNCmBgYA0KYXBsaWNhbW9zIGxhIGZ1bmNpb24gcGFyYSB3aW5kb3dzIHkgbGludXggY29uIDEwMDAwIGl0ZXJhY2lvbmVzDQpgYGB7cn0NCnNpbXVsYWNpb248LTEwMDAwDQpzaW1fd2luPC1zYXBwbHkoMTpzaW11bGFjaW9uLCBnZXRfc2ltLHZtaW49Mzg0MDAwLHZtYXg9NzEwMDAwLHZlc3Q9NDM1MDAwKQ0Kc2ltX2xpbjwtc2FwcGx5KDE6c2ltdWxhY2lvbiwgZ2V0X3NpbSx2bWluPTMzODAwMCx2bWF4PTc1MjUwMCx2ZXN0PTQxMDAwMCkNCnByaW50KHBhc3RlKCJ3aW5kb3dzOiAiLG1lYW4oc2ltX3dpbiksIiBMaW51eDoiLCBtZWFuKHNpbV9saW4pKSkNCmBgYA0KTGEgbWVqb3Igb3BjaW9uIGVzIGxpbnV4DQoNCg0K