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Sepideh Masoudi

Publications and source records attributed to Sepideh Masoudi.

6 recordsLinked to original sources

Enabling Reuse for Data-Sharing Pipelines in Federated Environments

Data mesh architectures enable decentralized data sharing through domain-owned data products, but supporting diverse consumers in federated settings often requires customized data-sharing pipelines. As the number of consumers grows, this leads to a proliferation of pipelines, increasing design and maintenance complexity. We observe that such pipelines frequently exhibit substantial structural overlap. In this paper, we argue that reuse should serve as a guiding principle to address this challenge. We define reuse in data-sharing pipelines as the systematic use of existing data assets and transformation logic across pipelines, and identify reuse opportunities at both design time and runtime. We analyze the associated challenges and outline a reuse-oriented design approach, supported by a reference architecture. A preliminary evaluation demonstrates the potential of reuse to reduce redundancy and improve manageability, providing a pathway toward more scalable and sustainable federated data sharing.

cs.DC

Artifact for A Non-Intrusive Framework for Deferred Integration of Cloud Patterns in Energy-Efficient Data-Sharing Pipelines

As data mesh architectures grow, organizations increasingly build consumer-specific data-sharing pipelines from modular, cloud-based transformation services. While reusable transformation services can improve cost and energy efficiency, applying traditional cloud design patterns can reduce reusability of services in different pipelines. We present a Kubernetes-based tool that enables non-intrusive, deferred application of design patterns without modifying services code. The tool automates pattern injection and collects energy metrics, supporting energy-aware decisions while preserving reusability of transformation services in various pipeline structures.

cs.DC

A Non-Intrusive Framework for Deferred Integration of Cloud Patterns in Energy-Efficient Data-Sharing Pipelines

As data mesh architectures gain traction in federated environments, organizations are increasingly building consumer-specific data-sharing pipelines using modular, cloud-native transformation services. Prior work has shown that structuring these pipelines with reusable transformation stages enhances both scalability and energy efficiency. However, integrating traditional cloud design patterns into such pipelines poses a challenge: predefining and embedding patterns can compromise modularity, reduce reusability, and conflict with the pipelines dynamic, consumer-driven nature. To address this, we introduce a Kubernetes-based tool that enables the deferred and non-intrusive application of selected cloud design patterns without requiring changes to service source code. The tool supports automated pattern injection and collects energy consumption metrics, allowing developers to make energy-aware decisions while preserving the flexible, composable structure of reusable data-sharing pipelines.

cs.DC

Energy Profiling of Data-Sharing Pipelines: Modeling, Estimation, and Reuse Strategies

Data-sharing pipelines involve a series of stages that apply policy-based data transformations to enable secure and effective data exchange among organizations. Although numerous tools and platforms exist to manage governance and enforcement in these pipelines, energy efficiency in data exchange has received limited attention. This paper introduces a novel method to model and estimate the energy consumption of different execution configurations in data-sharing pipelines. Additionally, this method identifies reuse potential in shared stages across pipelines that hold the key to reducing energy in large data-sharing federations. We validate this method through simulation experiments, revealing promising potential for cross-organizational pipeline optimization and laying a foundation for energy-conscious execution strategies.

cs.DB

PRE-Share Data: Assistance Tool for Resource-aware Designing of Data-sharing Pipelines

Data is a valuable asset, and sharing it as a product across organizations is key to building comprehensive and useful insights in fields such as science and industry. Before sharing, data often requires transformation to comply with governance policies and meet the requirements of recipient organizations. By leveraging pipelines, these transformations can be modeled as chains of processes; however, designing such pipelines while ensuring their efficiency is complex. In this paper, we present a tool that supports the design of pipelines by identifying opportunities for reusing transformation processes across different pipelines and suggesting designs and configurations based on these opportunities. This tool also generates reports on the resource consumption of pipeline processes, enabling the estimation of potential resource savings achievable through reuse-based designs. It could serve as a foundation for more efficient and resource-conscious data transformation pipeline design and be used as a component in self-service data platforms.

cs.SI

Advocate -- Trustworthy Evidence in Cloud Systems

The rapid evolution of cloud-native applications, characterized by dynamic, interconnected services, presents significant challenges for maintaining trustworthy and auditable systems, especially in sensitive contexts, such as finance or healthcare. Traditional methods of verification and certification are often inadequate due to the fast-past and dynamic development practices common in cloud computing. This paper introduces Advocate, a novel agent-based system designed to generate verifiable evidence of cloud-native application operations. By integrating with existing infrastructure tools, such as Kubernetes and distributed tracing systems, Advocate captures, authenticates, and stores evidence trails in a tamper-resistant manner. This approach not only supports the auditing process but also allows for privacy-preserving evidence aggregation. Advocate's extensible architecture facilitates its deployment in diverse environments, enabling the verification and adherence to policies and enhance trust in cloud services.

cs.DC