Distributed stream processing frameworks are designed to perform continuous computation on possibly unbounded data streams whose rates can change over time. Devising solutions to make such systems elastically scale is a fundamental goal to achieve desired performance and cut costs caused by resource over-provisioning. These systems can be scaled along two dimensions: the operator parallelism and the number of resources. In this paper, we show how these two dimensions, as two symbiotic entities, are independent but must mutually interact for the global benefit of the system. On the basis of this observation, we propose a fine-grained model for estimating the resource utilization of a stream processing application that enables the independent scaling of operators and resources. A simple, yet effective, combined management of the two dimensions allows us to propose ELYSIUM, a novel elastic scaling approach that provides efficient resource utilization. We implemented the proposed approach within Apache Storm and tested it by running two real-world applications with different input load curves. The outcomes backup our claims showing that the proposed symbiotic management outperforms elastic scaling strategies where operators and resources are jointly scaled.

Traceability plays a critical role in ensuring the quality, safety, and transparency of supply chains, where transportation stakeholders are fundamental to the efficient movement of goods. However, the diversity of actors involved poses significant challenges to achieving these goals. Each organization typically operates its own information system, tailored to manage internal data, but often lacks the ability to communicate effectively with external systems. Moreover, when data exchange between different systems is required, it becomes critical to maintain full control over the shared data and to manage access rights precisely. In this work, we propose the concept of interoperable traceability. We present a model that enables the seamless integration of data from sensors, IoT devices, data management platforms, and distributed ledger technologies (DLT) within a newly designed data space architecture. We also demonstrate a practical implementation of this concept by applying it to real-world scenarios in the agri-food sector, with direct implications for transportation systems and all stakeholders in a supply chain. Our demonstrator supports the secure exchange of traceability data between existing systems, providing stakeholders with a novel approach to managing and auditing data with increased transparency and efficiency.