Intelligent Service Orchestration in Edge Cloud Networks

Zeydan, Engin; Mangues‐Bafalluy, Josep; Türk, Yekta

doi:10.1109/mnet.101.2100214

Cited by 10 publications

(5 citation statements)

References 11 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…In the adaptive provisioning process, reconfiguration has been studied to improve orchestration decisions. Several techniques have been proposed [27], [32], [47], [48], with the most common being reinforcement learning (RL) [44], [50], [51]. Distributed behavioral learning and inference techniques that can support decentralization across the Edge Cloud while preserving the privacy of the raw training data, such as Federated Learning and Decentralized Learning, have also been considered [46], [52].…”

Section: Context-awareness and Decentralized Learningmentioning

confidence: 99%

A Framework for Cognitive, Decentralized Container Orchestration

Sofia,

Salomon,

Ferlin-Reiter

et al. 2024

IEEE Access

View full text Add to dashboard Cite

This perspective paper introduces a novel framework for container orchestration called CODECO. The CODECO orchestration framework relies on a data-network-computing approach to define the best infrastructure that can support the operation of next-generation Internet applications across a mobile, heterogeneous Edge-Cloud continuum. The selection of such an infrastructure is aligned with target performance profiles defined by the user, such as resilience or greenness. CODECO proposes to rely on decentralized Artificial Intelligence approaches in an attempt to provide the most suitable infrastructure to an application deployment, considering infrastructural challenges, such as intermittent connectivity and node failure. This paper explains the current CODECO framework and provides insight into operational use-cases where CODECO is being deployed, as relevant examples of application for such a framework. Recent developments in the creation of the open-source CODECO framework are described and explained, allowing the use of the framework by the research community. The paper then provides a thorough analysis of CODECO's features in comparison with existing orchestration frameworks, explaining the benefits introduced with this dynamic orchestration approach.INDEX TERMS Edge-Cloud; Orchestration; Kubernetes; AI/ML; heterogeneous networks; data observability.

show abstract

Section: Context-awareness and Decentralized Learningmentioning

confidence: 99%

A Framework for Cognitive, Decentralized Container Orchestration

Sofia,

Salomon,

Ferlin-Reiter

et al. 2024

IEEE Access

View full text Add to dashboard Cite

show abstract

“…Another crucial enabler for 6G networks is the programmability of the network to be able to configure and adapt to more than ever changing traffics and characteristics of 6G services [78]. With the new use cases of 6G and their more stringent performance requirements for certain types of traffic, it is also critical that transport and services are orchestrated jointly [79].…”

Section: ) Management and Orchestrationmentioning

confidence: 99%

Design Methodology for 6G End-to-End System: Hexa-X-II Perspective

Kerboeuf,

Porambage,

Jain

et al. 2024

IEEE Open J. Commun. Soc.

View full text Add to dashboard Cite

As the fifth generation (5G) mobile communication systems are commercially deployed, they bring new services, enhance user experiences, and offer various opportunities to different industries. Despite its advancements, 5G encounters several challenges. To tackle these issues, global industrial, academic, and standards organizations are actively researching on sixth generation (6G) wireless communication systems. 6G networks are envisioned as a transformative shift in the interactions between the physical, digital, and human realms, paving the way for a pervasive human-centered cyber-physical world. 6G is positioned to be a platform that offers communication and beyond communication services considering both performance and value centric technological development approaches. In this paper, we present the way forward towards the design of 6G end-to-end (E2E) system as a consolidated view of leading industry stakeholders and academia in the European level 6G flagship project Hexa-X-II. We discuss the key challenges with 5G and how 6G is expected to tackle those by introducing new technological innovations and supporting novel use case requirements. We provide a comprehensive methodology for the design of a 6G E2E system including ten principles, a blueprint, and a structured design process. The architecture design principles prioritize environmental sustainability, digital inclusiveness, and trustworthiness, considering their impact on the 6G E2E system. The blueprint is described corresponding to the infrastructure, network centric application, and application layers, as well as the pervasive functionalities and the relevant technological innovations. Following the design principles and the system blueprint, the design process is demonstrated as two-way approaches (i.e., 1) key performance and value indicators based design process. 2) top-down versus bottomup alignment process) through the lens of a collaborative robot use case. Through this use case, a special attention is given to the technological enablers that cover management and orchestration functionalities and their 6G enhancement to go beyond the limitations characterizing the previous network generation. In addition, virtual modelling aspects related to digital twining and simulations for 6G E2E system design are also discussed. INDEX TERMS 6G, end-to-end, platform, system, blueprint, network architecture, design process, use case, key value indicators, key performance indicators, collaborative robots.

show abstract

“…On the other hand, centralized approaches have recently gained attention because they can more easily leverage on Machine Learning (ML) techniques. In [22] a ML platform is developed for effective management of both computational and networking resources in a 5G mobile environment, where data are collected from both the Kubernetes orchestrator and the SDN controller.…”

Section: Background and Related Workmentioning

confidence: 99%

Enabling P4 Network Telemetry in Edge Micro Data Centers With Kubernetes Orchestration

et al. 2023

View full text Add to dashboard Cite

Integrating computation resources with networking technologies is an hot research topic targeting the optimization of containers deployment on a set of host machines interconnected by a network infrastructure. Particularly, next generation edge nodes will offer significant advantages leveraging on integrated computation resources and networking awareness, enabling configurable, granular and monitorable quality of service to different micro-services, applications and tenants, especially in terms of bounded endto-end latency. In this regard, SDN is a key technology enabling network telemetry and traffic switching with the granularity of the single traffic flow. However, currently available solutions are based on legacy SDN techniques, not enabling the matching of tunneled traffic, and thus require a tricky integration inside the hosts where containers are deployed. This work considers Kubernetes clusters deployed on next generation edge micro data center platforms and proposes an innovative SDN solution exploiting the P4 technology to gain visibility inside tunnelled traffic exchanged among pods. This way, the integration is achieved at the control plane level through the communication between Kubernetes and the SDN controller. The proposed solution is experimentally validated including a comprehensive framework enabling effective traffic switching and in-band telemetry at pod level. The major paper contributions consist in the design and the development of: (i) the networking applications at SDN control plane level; (ii) the P4 switch pipeline at the data plane level; (iii) the monitoring system used to collect, aggregate and elaborate the telemetry data.

show abstract

Intelligent Service Orchestration in Edge Cloud Networks

Cited by 10 publications

References 11 publications

A Framework for Cognitive, Decentralized Container Orchestration

A Framework for Cognitive, Decentralized Container Orchestration

Design Methodology for 6G End-to-End System: Hexa-X-II Perspective

Enabling P4 Network Telemetry in Edge Micro Data Centers With Kubernetes Orchestration

Contact Info

Product

Resources

About