Runtime balancing effect in distributed simulation model

Abstract

The paper deals with study of the load distribution effect between computing nodes for simulation run-time of a distributed computer network model. Two main types of balancing are considered: computational load balancing and reduction of transmitted amounts of data. Simulation was performed on one computer, and distribution was carried out between the cores of one processor. Simulation experiments showed that the lack of balance in the amounts of data, transferred between parts of a distributed model, leads to decrease of the simulation speed by several times due to overhead charges for data transmission between logical processes because of MPI usage. Model run-time changing at uneven distribution of computational load depends to a large extent on the load, which is created by the applications running on the simulated network nodes. It is shown that a balanced model is performed much faster than unbalanced version even when using applications that do not require significant computing resources. Simulation time reduction can be achieved by model separation in such manner as to reduce amounts of data transferred between its parts and reduce variability of loads generated by applications in different logical processes.