Design of High Performance, Scalable Content-based Publish-Subscribe System using MPI-CUDA Approach
DOI:
https://doi.org/10.26438/ijcse/v5i8.110115Keywords:
Matching Latency, MPI-CUDA, High performance, parallel event processingAbstract
Today Publish-subscribe model is used as communication backbone for various application domains such as IoT, Social networking, Intrusion detection system and Financial trading. Content-based flavor of Pub-Sub system enables routing of information from producers to consumers based on contents of the query or depends on subscriptions entered by the user. In this model, information is disseminated from producers to consumers through a network of brokers. The significant challenge in content-based Pub-Sub system lies in an efficient matching of an event against a large number of subscribers on a single message broker. To provide high throughput service guarantee to the subscriber of Pub-Sub system we propose a novel hybrid model for parallel event processing using MPI-CUDA approach. This approach combines message passing interface (MPI) and CUDA, a parallel computing platform and programming model, invented by NVIDIA. Results are compared with CCM (Cuda Content Matching Algorithm), a high performance, and parallel content matching algorithm. Approximately 1.77X speedup is observed in matching latency. This approach is suitable for use in event processing of large data intensive applications where the rate of arrival of the event is high.
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