WSEAS Transactions on Systems
Print ISSN: 1109-2777, E-ISSN: 2224-2678
Volume 24, 2025
Optimization of SQS Configurations for Efficient Batch Data Processing
Authors: , ,
Abstract: The evolution of distributed computing in cloud environments raises the question of finding new
approaches to processing large amounts of data. The speed of data arrival and the need to make decisions in
real-time adds to the higher complexity. AWS Simple Queue Service (SQS) is one of the popular tools for
organizing asynchronous message processing in distributed systems in many scenarios. Relying on SQS with
its default settings does not always work well, especially when we are dealing with heavy data processing. That
is why figuring out the best setup for each specific task is a key challenge. Objective. This study aims to
determine the queue setup so that a distributed system can efficiently handle processing 500,000 records while
generating many PDF documents. We want to find the sweet spot in queue configuration that keeps the system
running smoothly and effectively under heavy workloads. Method. The research evaluates the performance of
the developed system for the mass generation of PDF documents under various load conditions using classical
queuing theory models and their extensions. To assess the impact of different combinations of SQS parameters,
key performance indicators such as response time, average queue length, and utilization rate are calculated
using mathematical concepts. A PDF document generation software that directly interacts with SQS is
developed using Python and AWS SDK Boto3. Results. The key factors affecting system performance are the
batch size and time of message visibility in the queue. The results showed that proper configurations
significantly increase throughput without loss of reliability. Empirical results confirm theoretical expectations
and contribute to the selection of optimal parameters. Conclusions. The obtained research results enable us to
provide practical recommendations for the selection of important parameters for SQS, such as throughput,
delay, cost, and reliability, for performing high-load operations in serverless computing.
Search Articles
Keywords: serverless, cloud computing, queueing theory, batch processing, high-load systems, performance
optimization
Pages: 36-43
DOI: 10.37394/23202.2025.24.4