A new congestion control algorithm for improving the performance of a broadcast-based multiprocessor architecture

Congestion occurring in the input queues of broadcast-based multiprocessor architectures can severely limit their overall performance. The existing congestion control algorithms estimate congestion based on a node’s output channel parameters such as the number of free virtual channels or the number of packets waiting at the channel queue. In this paper, we have proposed a new congestion control algorithm to prevent congestion on broadcast-based multiprocessor architectures with multiple input queues. Our algorithm performs congestion control at the packet level and takes into account the next input queue number which will be accessed by the processor, which form the fundamental differences between our algorithm and the algorithms based on the idea of virtual channel congestion control. The performance of the algorithm is evaluated by OPNET Modeler with various synthetic traffic patterns on a 64-node Simultaneous Optical Multiprocessor Exchange Bus (SOME-Bus) architecture employing the message passing protocol. Performance measures such as average input waiting time, average network response time and average processor utilization have been collected before and after applying the algorithm. The results show that the proposed algorithm is able to decrease the average input waiting time by 13.99% to 20.39%, average network response time by 8.76% to 20.36% and increase average processor utilization by 1.92% to 6.63%. The performance of the algorithm is compared with that of the other congestion control algorithms and it is observed that our algorithm performs better under all traffic patterns. Also, theoretical analysis of the proposed method is carried out by using queuing networks.

Research highlights
► A new congestion control algorithm for broadcast-based multiprocessor architectures with multiple input queues.
► The algorithm reduces the average input waiting time by 13.99% to 20.39%.
► The algorithm reduces the average network response time by 8.76% to 20.36%.
► The algorithm increases the average processor utilization by 1.92% to 6.63%.