Towards Orchestration of Cloud-Edge Architectures with Kubernetes

Böhm, Sebastian; Wirtz, Guido

doi:10.1007/978-3-031-06371-8_14

Cited by 13 publications

(7 citation statements)

References 42 publications

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“…Relevant edge orchestration architectures have a primary focus on the organization and scheduling of tasks across both cloud and edge nodes [51,52]. These approaches offer advantages such as resource optimization, but the creation of efficient orchestration strategies can be a complex task.…”

Section: Edge-offloading Architecturesmentioning

confidence: 99%

“…These approaches offer advantages such as resource optimization, but the creation of efficient orchestration strategies can be a complex task. Böhm et al define an architecture based on a container registry that contains the images of applications and is used to design the nodes within the cloud infrastructure [51]. The autonomic controller distributes responsibilities to various nodes.…”

Section: Edge-offloading Architecturesmentioning

confidence: 99%

See 1 more Smart Citation

Edge Offloading in Smart Grid

Arcas,

Cioara,

Anghel

et al. 2024

Smart Cities

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The management of decentralized energy resources and smart grids needs novel data-driven low-latency applications and services to improve resilience and responsiveness and ensure closer to real-time control. However, the large-scale integration of Internet of Things (IoT) devices has led to the generation of significant amounts of data at the edge of the grid, posing challenges for the traditional cloud-based smart-grid architectures to meet the stringent latency and response time requirements of emerging applications. In this paper, we delve into the energy grid and computational distribution architectures, including edge–fog–cloud models, computational orchestration, and smart-grid frameworks to support the design and offloading of grid applications across the computational continuum. Key factors influencing the offloading process, such as network performance, data and Artificial Intelligence (AI) processes, computational requirements, application-specific factors, and energy efficiency, are analyzed considering the smart-grid operational requirements. We conduct a comprehensive overview of the current research landscape to support decision-making regarding offloading strategies from cloud to fog or edge. The focus is on metaheuristics for identifying near-optimal solutions and reinforcement learning for adaptively optimizing the process. A macro perspective on determining when and what to offload in the smart grid is provided for the next-generation AI applications, offering an overview of the features and trade-offs for selecting between federated learning and edge AI solutions. Finally, the work contributes to a comprehensive understanding of edge offloading in smart grids, providing a Strengths, Weaknesses, Opportunities, and Threats (SWOT) analysis to support cost–benefit analysis in decision-making regarding offloading strategies.

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Section: Edge-offloading Architecturesmentioning

confidence: 99%

Section: Edge-offloading Architecturesmentioning

confidence: 99%

Edge Offloading in Smart Grid

Arcas,

Cioara,

Anghel

et al. 2024

Smart Cities

View full text Add to dashboard Cite

show abstract

“…In Ref. [96], Böhm and Wirtz discuss the opportunities and the difficulties of managing distributed computing resources as they investigate the orchestration of cloud-edge systems using Kubernetes. The creation of scalable and robust smart city infrastructures depends heavily on this study.…”

Section: Literature Reviewmentioning

confidence: 99%

A Novel Authentication Scheme Based on Verifiable Credentials Using Digital Identity in the Context of Web 3.0

Nita,

Mihailescu

2024

Electronics

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This paper explores the concept of digital identity in the evolving landscape of Web 3.0, focusing on the development and implications of a novel authentication scheme using verifiable credentials. The background sets the stage by placing digital identity within the broad context of Web 3.0′s decentralized, blockchain-based internet, highlighting the transition from earlier web paradigms. The methods section outlines the theoretical framework and technologies employed, such as blockchain, smart contracts, and cryptographic algorithms. The results summarize the main findings, including the proposed authentication scheme’s ability to enhance user control, security, and privacy in digital interactions. Finally, the conclusions discuss the broader implications of this scheme for future online transactions and digital identity management, emphasizing the shift towards self-sovereignty and reduced reliance on centralized authorities.

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“…In case of a redundant deployment, either with multiple master nodes or a unique etcd cluster, the data will be replicated across all instances. The api is exposed [58] as REST API and allows the interaction with the system components in the cluster. The Horizontal Pod Autoscaler (HPA), omitted in Figure 4, dynamically scales in and scales out the number of pods based on metrics like CPU and memory utilization.…”

Section: Kubernetes As Container Platformmentioning

confidence: 99%

“…Comparison of Resource-Awareness and Architectural Capabilities in Different Kubernetes Implementations for Cloud-Edge Architectures[58] …”

mentioning

confidence: 99%

Cloud-Edge Orchestration for Smart Cities: A Review of Kubernetes-based Orchestration Architectures

Böhm

Wirtz

2022

EAI Endorsed Trans Smart Cities

Self Cite

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Edge computing offers computational resources near data-generating devices to enable low-latency access. Especially for smart city contexts, edge computing becomes inevitable for providing real-time services, like air quality monitoring systems. Kubernetes, a popular container orchestration platform, is often used to efficiently manage containerized applications in smart cities. Although it misses essential requirements of edge computing, like network-related metrics for scheduling decisions, it is still considered. This paper analyzes custom cloud-edge architectures implemented with Kubernetes. Specifically, we analyze how essential requirements of edge orchestration in smart cities are solved. Also, shortcomings are identified in these architectures based on the fundamental requirements of edge orchestration. We conduct a literature review to obtain the general requirements of edge computing and edge orchestration for our analysis. We map these requirements to the capabilities of Kubernetes-based cloud-edge architectures to assess their level of achievement. Issues like using network-related metrics and the missing topology-awareness of networks are partially solved. However, requirements like real-time resource utilization, fault-tolerance, and the placement of container registries are in the early stages. We conclude that Kubernetes is an eligible candidate for cloudedge orchestration. When the formerly mentioned issues are solved, Kubernetes can successfully contribute latency-critical, large-scale, and multi-tenant application deployments for smart cities.

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Towards Orchestration of Cloud-Edge Architectures with Kubernetes

Cited by 13 publications

References 42 publications

Edge Offloading in Smart Grid

Edge Offloading in Smart Grid

A Novel Authentication Scheme Based on Verifiable Credentials Using Digital Identity in the Context of Web 3.0

Cloud-Edge Orchestration for Smart Cities: A Review of Kubernetes-based Orchestration Architectures

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