Edge Computing and Cloud Management Advancements

The field of edge computing and cloud management is witnessing significant advancements, driven by the need for efficient, scalable, and secure data processing and deployment. Researchers are exploring innovative approaches to integrate quantum computing capabilities into classical edge computing servers, enabling sustainable multi-user computation offloading and optimizing resource management. Another key area of focus is the development of hybrid cloud management planes, which aim to simplify the management of big data applications across multiple cloud environments. Noteworthy papers in this area include: Hybrid Reinforcement Learning-based Sustainable Multi-User Computation Offloading for Mobile Edge-Quantum Computing, which proposes a pioneering paradigm for mobile edge quantum computing. KubeFence: Security Hardening of the Kubernetes Attack Surface, which introduces a novel solution for security hardening of the Kubernetes attack surface. FlowUnits: Extending Dataflow for the Edge-to-Cloud Computing Continuum, which presents a novel programming and deployment model for edge-to-cloud computing environments.

Sources

Hybrid Reinforcement Learning-based Sustainable Multi-User Computation Offloading for Mobile Edge-Quantum Computing

A Hybrid Cloud Management Plane for Data Processing Pipelines

Container-level Energy Observability in Kubernetes Clusters

Kubernetes in the Cloud vs. Bare Metal: A Comparative Study of Network Costs

KubeFence: Security Hardening of the Kubernetes Attack Surface

FlowUnits: Extending Dataflow for the Edge-to-Cloud Computing Continuum

Comparative Analysis of POX and RYU SDN Controllers in Scalable Networks

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