Future Manufacturing Systems by T. Aized

By T. Aized

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The drawback of this strategy is that it can create a lot of messages among the nodes. Moreover, both strategies take into consideration neither the communication among the processes, nor the migration costs. 3. MigBSP: Process Rescheduling Model A BSP application is divided in one or more supersteps, each one containing both computation and communication phases followed by a barrier synchronization. Since the barrier always wait for the slowest process, MigBSP’s final objective is to adjust the processes’ location in order to reduce the supersteps’ times.

Starved and blocked machine states when Mi-1 is faster than Mi+1 (51) Discrete event models for flexible manufacturing cells 31 In a dual situation to case A, we get the parts until the next event, for Bi-1 (Ciufudean & Filote, 2010): 1   T1,i 1  T2i   i 1 Ni-1 = 1 + lnt  1 1     i 1  i 1      (52) From relation (48) and (52) we notice that the number of parts until the next event depends on the service rate of each part. We may say that the buffer dimensions can be calculated in such a manner as to avoid the failed state of machines, considering that the time to calculate the number of parts until next event is set to T21 = P02 in relation (48) and, respectively, to T1,i-1 = P02 in relation (52); where P02 is given by relation (42).

Comp(i, j) = Pcomp (i ) . CTPk+α−1 (i ) . ISetk+α−1 ( j) (3) Equation 3 shows the function to calculate the Computation metric for process i to Set j. The value of the equation is high if the BSP process presents stability on its executed instructions, has a large computation time and an efficient Set is involved. However, Comp(i, j) is close to 0 if the process is unstable and/or it finishes its computation phase quickly. The model aims to migrate a delayed BSP process that presents a good behavior (amount of instructions that performs is regular) on the resource which belongs currently, because it can follow this actuation in another resource.

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