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◇ Charles Sturt University Research Output (CRO)2026-08-01· Computer science

<i>LEISA</i>:A scalable microservice-based system for efficient livestock data sharing

Habib, Mahir, Kabir, Muhammad Ashad; id_orcid 0000-0002-6798-6535, Zheng, Lihong; id_orcid 0000-0001-5728-4356

原始摘要(英文原文)· Original abstract
The livestock sector’s fragmented data landscape hampers timely, interoperable decision-making across producers, processors, and service providers. We present the Livestock Event Information Sharing Architecture (LEISA), a cloud-based microservices system that enables real-time, standardised exchange of livestock event data while preserving producer control. Unlike prior approaches, LEISA elevates two first-class primitives: (i) producer-controlled, event-level routing via a queue-mapping service and (ii) schema-driven validation at ingress to enforce data quality and interoperability. A decoupled, asynchronous consumption model tolerates heterogeneous systems and connectivity conditions. We derive functional and non-functional requirements, describe a reference implementation using RESTful APIs with a message broker, and evaluate five core services for throughput, latency, scalability, and resilience. Representative use cases (e.g., tracking and veterinary events) illustrate applicability. Results indicate that LEISA achieves reliable, seamless data sharing while maintaining producer autonomy. We also outline database design considerations (indexing, partitioning), discuss portability across deployment environments, and state limitations with directions for future work (e.g., broader service coverage and multi-cloud experiments).
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