Masanori Hirano

Dependence of load imbalance on data allocation among distributed processing modules in an advanced intelligent network

This paper considers advanced IN systems in which the data for each customer are allocated in a distributed way among multiple processor modules. A method is presented in which the traffic imbalance for customer data is represented. Based on such a representation, a method to evaluate the load imbalance among the processor modules, as well as a method to estimate its upper limit, are presented. Using the presented method, even if customer data composed of number conversion and screening information, and with a large traffic imbalance factor of several thousand to several tens of thousands, are allocated at random to the processor modules, the load imbalance can be reduced to 10 to 20% at the present level of processor performance and number of dynamic steps in the transaction. It is shown that dynamic load balancing can be achieved for this kind of imbalance by combining the processing that can be executed independently of the customer data, such as directory retrieval, which appears in ordinary distributed processing.