This paper proposes a distributed model termed as Tower-like Master-Slave Model (TMSM) for the artificial immune systems.Based on TMSM

a distributed immune memory clonal selection algorithm (DIMCSA) is put forward for solving numerical optimization problem.Using the theorem of Markov chain

we have proved the convergence of DIMCSA.In order to get away from the influence of network conditions and get a veracious estimation on the DIMCSA’ efficiency

Multi-thread simulative parallel computing system (MSPCS) is designed here and a novel performing index in which the searching time and network communication time are considered respectively is also proposed for distributed stochastic searching approaches.Experimental results indicate that DIMCSA can achieve better solutions with less computing and fewer communications

and it is capable of solving massive and complicated optimization problems.