cache_replc_lru.m

clear solver AvgTable;
 
model = Network('model');
 
n = 5; % number of items
m = 2; % cache capacity
 
delay = Delay(model, 'Delay');
cacheNode = Cache(model, 'Cache', n, m, ReplacementStrategy.LRU);
 
jobClass = ClosedClass(model, 'JobClass', 1, delay, 0);
hitClass = ClosedClass(model, 'HitClass', 0, delay, 0);
missClass = ClosedClass(model, 'MissClass', 0, delay, 0);
 
delay.setService(jobClass, Exp(1));
 
pAccess = DiscreteSampler((1/n)*ones(1,n));  % uniform item references
cacheNode.setRead(jobClass, pAccess);
 
cacheNode.setHitClass(jobClass, hitClass);
cacheNode.setMissClass(jobClass, missClass);
 
P = model.initRoutingMatrix;
 
P{jobClass, jobClass}(delay, cacheNode) =  1.0;
P{hitClass, jobClass}(cacheNode, delay) =  1.0;
P{missClass, jobClass}(cacheNode, delay) =  1.0;
 
model.link(P);
 
solver{1} = CTMC(model,'keep',false);
AvgTable{1} = solver{1}.getAvgNodeTable; AvgTable{1}
 
model.reset;
solver{2} = SSA(model,'samples',1e4,'verbose',true,'method','serial','seed',23000);
AvgTable{2} = solver{2}.getAvgNodeTable; AvgTable{2}
 
solver{3} = MVA(model);
AvgTable{3} = solver{3}.getAvgNodeTable; AvgTable{3}