Revolutionizing Supply Chain Management: Real-time Data Processing and Concurrency

Author:

Shukla Suwarna,Singh Prabhneet

Abstract

In the contemporary business landscape, effective supply chain management (SCM) is paramount for organizations seeking to thrive amidst evolving market dynamics and heightened customer expectations. This research paper presents a pioneering approach to SCM that harnesses cutting-edge technologies, namely Kafka and Akka, to revolutionize data integration and decision-making processes. By leveraging Kafka as a robust distributed event streaming platform and Akka as a versatile toolkit for developing concurrent and distributed applications, our system facilitates seamless communication and coordination across diverse nodes within the supply chain network. This paper elucidates the intricacies of the proposed architecture, detailing the implementation methodology and performance evaluation metrics. Through a comprehensive examination, we demonstrate how our solution enhances supply chain visibility, fosters operational agility, and enables real-time responsiveness to market fluctuations and customer demands. Moreover, practical use cases exemplify the transformative impact of our approach on inventory management optimization, order fulfillment efficiency, and logistics optimization. Furthermore, we delve into the challenges encountered during implementation and deployment, offering insights into potential mitigative strategies. Finally, we outline avenues for future research, exploring emerging trends and opportunities in the realm of SCM empowered by Kafka and Akka technologies.

Publisher

International Journal of Innovative Science and Research Technology

Reference55 articles.

1. K. Peddireddy, ”Streamlining Enterprise Data Processing, Reporting and Realtime Alerting using Apache Kafka,” 2023 11th International Symposium on Digital Forensics and Security (ISDFS), Chattanooga, TN, USA, 2023, pp. 1-4, doi: 10.1109/ISDFS58141.2023.10131800. keywords: Industries;Fault tolerance; Filtering;Scalability;Fault tolerant systems ;Refining; Organizations;Data Engineering; Kafka; Machine learning Data reporting;Data alerting;Efficiency;Accuracy;Time reduction;Cost reduction,

2. P. Le Noac’h, A. Costan and L. Bouge, ”A performance evaluation´ of Apache Kafka in support of big data streaming applications,” 2017 IEEE International Conference on Big Data (Big Data), Boston, MA, USA, 2017, pp. 4803-4806, doi: 10.1109/Big Data.2017.8258548. keywords: Throughput; Big Data;Real-time systems; Benchmark testing; Measurement; Internet of Things; Sparks;Stream computing;Apache Kafka;Big Data,

3. A. Sayar, S¸. Arslan, T. C¸akar, S. Ertugrul and A. Akc¸ay, ”High-˘ Performance Real-Time Data Processing: Managing Data Using Debezium, Postgres, Kafka, and Redis,” 2023 Innovations in Intelligent Systems and Applications Conference (ASYU), Sivas, Turkiye, 2023, pp. 1-4, doi: 10.1109/ASYU58738.2023.10296737. keywords: Technological innovation;Relational databases;Data processing;Real-time systems;Intelligent systems;Monitoring;Kafka;Debezium;Redis;EventDriven,

4. Y. Drohobytskiy, V. Brevus and Y. Skorenkyy,”Spark Structured Streaming: Customizing Kafka Stream Processing,” 2020 IEEE Third International Conference on Data Stream Mining Processing (DSMP), Lviv, Ukraine, 2020, pp. 296299, doi: 10.1109/DSMP47368.2020.9204304. keywords: Sparks;Task analysis;Monitoring;Data mining;Conferences;Realtime systems;Containers;Distributed systems;Stream processing;Kafka streams;Spark v 2.3.2;HDFS file granulation,

5. Bill Bejeck, Kafka Streams in Action: Real-time apps and microservices with the Kafka Streams API , Manning, 2018.

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