2016
DOI: 10.1002/nem.1944
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Seamless integration of cloud and fog networks

Abstract: Summary A way to merge cloud computing infrastructures with traditional or legacy network deployments, leveraging the best in both worlds and enabling a logically centralized control. A solution is proposed to extend existing cloud computing software stacks so they are able to manage networks outside the cloud computing infrastructure, the fog, by extending the internal, virtualized network segments. This is useful in a variety of use cases such as incremental legacy to cloud network migration, hybrid virtual/… Show more

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Cited by 5 publications
(5 citation statements)
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References 14 publications
(12 reference statements)
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“…The primary challenges in a multi-cloud environment is providing users with seamless and secure access to resources across various platforms [21]. Traditional authentication methods may fall short in meeting the demands of diverse cloud ecosystems, necessitating innovative solutions.…”
Section: Challenges In User Authentication and Solutionsmentioning
confidence: 99%
“…The primary challenges in a multi-cloud environment is providing users with seamless and secure access to resources across various platforms [21]. Traditional authentication methods may fall short in meeting the demands of diverse cloud ecosystems, necessitating innovative solutions.…”
Section: Challenges In User Authentication and Solutionsmentioning
confidence: 99%
“…In this case, some close mobile devices will be selected as ad hoc relay nodes and connect the affected user devices to unreachable MEC servers. Cardoso et al in [62] proposed the vertical collaboration approach that coordinates mobile devices, physical edge servers, and remote cloud centers for performance optimization. They extended the current edge computing software stack to allow efficient collaboration and orchestration.…”
Section: ) Multiple Edge Servers' Collaborationmentioning
confidence: 99%
“…Algorithm 1 implements the distance-based heuristic using a function that evaluates a given service component allocation, checks for its feasibility, and returns a score value representing the summation of DC components. Furthermore, to balance the importance of each DC component and the priority of service components, the distance-based heuristic relies on both the ω rd , ω io , ω crios weights defined in (14) and on the service priority weights FSP defined in (9). Finally, let us note that this heuristic is a revised version of the preliminary approach presented in Poltronieri et al, 24 which we enhanced to provide more performance and accuracy.…”
Section: A Distance-based Heuristic For Service Fabric Managementmentioning
confidence: 99%
“…In fact, fog computing solutions are responsible to deliver low-latency applications at the edge of the network with improvements due to the proximity of users and devices. 9 However, managing such applications means dealing with a significant number of users with heterogeneous interests, a large number of devices, and applications with different Quality-of-Service (QoS) and Quality-of-Experience (QoE) requirements. 10 Scientific literature often addressed fog computing resource management as an optimization problem, considering many different optimization criteria, including deadline matching, 11 energy consumption (green computing), 12 job duration, 13 or tail latency minimization.…”
Section: Introductionmentioning
confidence: 99%