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OPTIMised video content delivery chains leveraging data analysis over joint multI-accesS edge computing and 5G radio network infrasTructures

Periodic Reporting for period 2 - OPTIMIST (OPTIMised video content delivery chains leveraging data analysis over joint multI-accesS edge computing and 5G radio network infrasTructures)

Période du rapport: 2023-05-01 au 2025-04-30

The OPTIMIST programme set the ambitious aim to develop a modular end-to-end service platform tailored to the optimized delivery of personalised video content in 5G mobile networks, providing one of the first world-wide implementations of MEC-enabled service provisioning in 5G networks that is fully compatible with the emerging ETSI/3GPP reference architectures. To achieve this, the OPTIMIST service platform designed and implemented different Multi-access Edge Computing (MEC) services, which were until recently studied in an isolated fashion in the literature, (e.g. edge network caching exploiting edge storage resources, video transcoding and data-driven content popularity prediction exploiting edge processing resources, optimized video content placement and delivery exploiting the new 5G radio capabilities), in the form of virtual network functions (VNFs) that are instantiated and optimized on-the-fly to construct a video service chain that is designed to meet the personalized requirements of 5G mobile video consumers. To formalize the integration of MEC capabilities into the operation of 5G mobile networks, the OPTIMIST service platform is fully aligned with the existing and forthcoming standardization activities in the areas of MEC and 5G networks (ETSI MEC and 3GPP); thus, maximizing the impact of the project in the long-term both in terms of academic results (new methodological tools and algorithmic innovations) and market products (deliver specific products / services that will enhance the portfolio of industrial partners). To this end, OPTIMIST leveraged state-of-the-art (SotA) technologies in MEC-empowered service provisioning, data-driven service control and automation, QoE-driven dynamic adaptive video streaming over HTTP (DASH), GPS-free localization and machine learning (ML) for wireless communications. To fulfil the ambitious objectives, OPTIMIST pursued inter-disciplinary and cross-sectoral research that goes beyond current SotA in the following areas: i) MEC/RAN integration and NFV in 5G networks, ii) MEC-empowered service provisioning for stateful video services, iii) QoE-driven service optimization and DASH and iv) data-driven automation and control of 5G MEC services.
The OPTIMIST project has successfully developed and integrated a modular, ETSI-compliant MEC (Multi-access Edge Computing) platform, targeting optimized video content delivery over 5G infrastructures. Key results include advanced QoE-driven data analytics modules, dynamic DASH video adaptation, and a fully containerized MEC architecture featuring orchestrators, application managers, and edge platforms. The project demonstrated the integration and experimental validation of analytics and QoE prediction tools, revealing robust improvements in adaptive video streaming performance across varied network conditions. Meanwhile, it consolidated these developments into an end-to-end MEC service platform, deploying and evaluating the full lifecycle of MEC applications. The system was tested using comprehensive load and integration testing frameworks, including Kubernetes-OpenStack hybrid environments, with tangible enhancements in latency, throughput, and resource allocation across the MEC components.

The project's exploitation strategy focuses on advancing MEC-aware multimedia services in telecom and cloud-edge markets. The OPTIMIST software stack is built with open standards and modular components to enable adoption by mobile operators, infrastructure providers, and application developers. Source code repositories, documented deployment workflows, and containerized modules ensure the replicability and extendibility of the platform. Dissemination efforts include the release of open-source repositories (e.g. GitHub), extensive technical documentation, and public deliverables, which offer a blueprint for future research and integration. Through these combined efforts, OPTIMIST paves the way for next-generation edge computing services, while actively fostering uptake by the research community and industrial stakeholders.
The OPTIMIST project has advanced the state of the art by integrating cutting-edge QoE-aware adaptive streaming and MEC orchestration into a cohesive, ETSI-compliant edge computing framework. Unlike existing fragmented approaches, OPTIMIST introduced an end-to-end, standards-aligned platform capable of jointly optimizing video delivery, resource allocation, and service orchestration in real time. The project’s innovative combination of data-driven analytics, predictive caching strategies, and smart DASH adaptation algorithms significantly enhances user-perceived quality under dynamic 5G network conditions. Moreover, the integration of tools like Temporal workflow engines, Keycloak-secured API gateways, and Kubernetes-based VIM plugins within an open, interoperable architecture reflects a novel approach to managing the complexity of MEC application lifecycles at scale.

The results of OPTIMIST have the potential to yield strong socio-economic impacts. Improved video delivery quality and resource efficiency directly benefit telecom operators and end-users by reducing infrastructure costs, energy consumption, and network congestion. These advancements also support a more inclusive digital society by enabling better service delivery in underserved or bandwidth-constrained regions. On a broader societal level, the platform’s openness and modularity empower SMEs, researchers, and developers to build upon the OPTIMIST stack, fostering innovation and accelerating the adoption of edge-based services in education, health, emergency response, and entertainment sectors. The project also contributes to European digital sovereignty by promoting interoperable, standards-based solutions that reduce dependence on proprietary cloud and content delivery systems.
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