Towards Edge Computing as a Service: Dynamic Formation of the Micro Data-Centers

Simić, Miloš; Prokić, Ivan; Dedeić, Jovana; Sladić, Goran; Milosavljević, Branko

doi:10.1109/access.2021.3104475

Cited by 12 publications

(24 citation statements)

References 55 publications

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“…Namespaces are designed to span AWS Regions, so containment remains consistent even if a person signs in to a different AWS Region [28]. This marks a significant improvement over the Kubernetes mechanism and its ability to tie and operate multiple clusters [29] to the same namespace, which is more challenging to set up and manage through a single control plane.…”

Section: A Namespaces Applicability In Cloud Computingmentioning

confidence: 99%

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A Hierarchical Namespace Approach for Multi-Tenancy in Distributed Clouds

Simić,

Dedeić,

Stojkov

et al. 2024

IEEE Access

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The micro cloud model offers cloud behavior at the edge of the network. It allows dynamic organization of the resources, closer to the users and the data. One of the crucial problems to solve is to design a proper cloud model at the edge of the network and offer cloud services that support multi-tenancy. This cloud property is a governing mechanism to lower cloud costs. It is essential for the scalability of both public and private clouds due to the utilization of shared resources and the logical separation of tenants. This paper presents the model for the creation of virtual clouds (vClouds) on physical infrastructure using a hierarchy of namespaces, with proper organization and redistribution of resources such as CPU, RAM, and storage, while preserving logical isolation between vClouds, thus creating a multi-tenant system. The presented model guarantees accurate resource redistribution through graph transformations to model operations, while the proposed protocols ensure correctness by employing multiparty session types for modeling. We extend the secure computing mode to establish an isolated system, allowing sandboxing rules for every namespace and creating hierarchies of security profiles. This advancement enables our model to inherit parent security profiles fully, extend them by adding child-specific elements, or redefine and create entirely new ones. Furthermore, the users can switch context, meaning they can change vCloud or the namespace they operate on.INDEX TERMS Cloud computing, distributed systems, edge computing, formal specifications, infrastructure as software, platform, namespaces, isolation, multi-tenancy.• We enable users to switch between contexts, meaning they can change vCloud or the namespace they operate on.These advancements rely on our following technical contributions:• Protocol definitions for namespace manipulation:This study defines protocols for performing crucial operations, such as creating, updating, and deleting namespaces within virtual clouds, leveraging the power of rules for graph transformations over namespaces. These protocols provide a standardized framework for managing and manipulating namespaces effectively.

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Section: A Namespaces Applicability In Cloud Computingmentioning

confidence: 99%

“…In contrast, edge computing models lack dynamic geographical organization, well-defined native applications, and a clear separation of concerns (SoC) [29]. These issues collectively hinder the provision of EC models as a service.…”

Section: A Paradigm Of Distributed Edge Computingmentioning

confidence: 99%

A Hierarchical Namespace Approach for Multi-Tenancy in Distributed Clouds

Simić,

Dedeić,

Stojkov

et al. 2024

IEEE Access

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“…Based on the previously defined health-check protocol, list, mutate, query operations, and formal models defined in [19], we have implemented a proof of concept solution able to dynamically form disposable micro clouds, abstracting infrastructure to the level of software in laboratory conditions.…”

Section: Proof Of Conceptmentioning

confidence: 99%

“…The proposed model could exist as a stand-alone solution, integrated into existing tools (e.g., orchestrator engines), or be an integral element of every cloud provider infrastructure and offered as a service [19].…”

mentioning

confidence: 99%

Infrastructure as Software in Micro Clouds at the Edge

Simić

Sladić

Zarić

et al. 2021

Sensors

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Edge computing offers cloud services closer to data sources and end-users, making the foundation for novel applications. The infrastructure deployment is taking off, bringing new challenges: how to use geo-distribution properly, or harness the advantages of having resources at a specific location? New real-time applications require multi-tier infrastructure, preferably doing data preprocessing locally, but using the cloud for heavy workloads. We present a model, able to organize geo-distributed nodes into micro clouds dynamically, allowing resource reorganization to best serve population needs. Such elasticity is achieved by relying on cloud organization principles, adapted for a different environment. The desired state is specified descriptively, and the system handles the rest. As such, infrastructure is abstracted to the software level, thus enabling “infrastructure as software” at the edge. We argue about blending the proposed model into existing tools, allowing cloud providers to offer future micro clouds as a service.

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“…Edge computing is a paradigm that brings computation and data storage closer to the source of data generation (Hamdan et al, 2020). Unlike traditional cloud computing, where data is processed in centralized data centers, edge computing utilizes decentralized infrastructure, placing computing resources closer to the data source, often at the edge of the network (Simić et al, 2021). This proximity enables faster data processing and reduced latency, making it ideal for applications that require real-time responsiveness (Shumba et al, 2022).…”

Section: Introductionmentioning

confidence: 99%

Reviewing the Transformational Impact of Edge Computing on Real-Time Data Processing and Analytics

Oluwole Temidayo Modupe,

Aanuoluwapo Ayodeji Otitoola,

Oluwatayo Jacob Oladapo

et al. 2024

Comput. sci. IT res. j.

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Edge computing has emerged as a pivotal paradigm shift in the realm of data processing and analytics, revolutionizing the way organizations handle real-time data. This review presents a comprehensive review of the transformational impact of edge computing on real-time data processing and analytics. Firstly, the review delves into the fundamental concepts of edge computing, elucidating its architectural framework and highlighting its distinct advantages over traditional cloud-centric approaches. By distributing computational resources closer to data sources, edge computing mitigates latency issues and enhances responsiveness, thereby enabling real-time data processing at the edge. Furthermore, this review explores how edge computing facilitates the seamless integration of analytics capabilities into edge devices, empowering organizations to derive actionable insights at the source of data generation. Leveraging advanced analytics algorithms, such as machine learning and artificial intelligence, edge computing enables autonomous decision-making and predictive analytics in real time, fostering innovation across diverse industry verticals. Moreover, the review examines the transformative implications of edge computing on various sectors, including healthcare, manufacturing, transportation, and smart cities. By enabling localized data processing and analytics, edge computing enhances operational efficiency, ensures data privacy and security, and unlocks new opportunities for business optimization and value creation. This review underscores the profound impact of edge computing on real-time data processing and analytics, revolutionizing the way organizations harness data to drive informed decision-making and gain competitive advantage in today's dynamic business landscape. As edge computing continues to evolve, its transformative potential is poised to redefine the future of data-driven innovation and digital transformation. Keywords: Edge, Computing, Analytics, Data, Impact, Review.

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Towards Edge Computing as a Service: Dynamic Formation of the Micro Data-Centers

Cited by 12 publications

References 55 publications

A Hierarchical Namespace Approach for Multi-Tenancy in Distributed Clouds

A Hierarchical Namespace Approach for Multi-Tenancy in Distributed Clouds

Infrastructure as Software in Micro Clouds at the Edge

Reviewing the Transformational Impact of Edge Computing on Real-Time Data Processing and Analytics

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