Cited by 69IoT and Edge/Fog ComputingCloud Computing and Resource ManagementSoftware-Defined Networks and 5G

Cloudlet network design optimization

Ceselli, Alberto, Premoli, Marco, Secci, Stefano·2015·2015 IFIP Networking Conference (IFIP Networking)

Abstract

Major interest is currently given to the integration of clusters of virtualization servers, also referred to as `cloudlets', into the access network to allow higher performance and reliability in the access to mobile cloud services. We tackle the cloudlet network design problem for mobile access networks. The model is such that virtual machines are associated with mobile users and are allocated to cloudlets. Designing a cloudlet network implies first determining where to install cloudlet facilities among the available sites, then assigning sets of access points such as base-stations to cloudlets, while supporting virtual machine migrations and taking into account partial user mobility information, as well as the satisfaction of service-level agreements. We present link-path formulations supported by heuristics to compute solutions in reasonable time. We qualify the advantage in considering mobility for both users and virtual machines as up to 40% less cloudlet facilities to install and 40% less virtual machine migrations to execute. We compare two migration modes, bulk and live migration, as a function of mobile cloud service requirements, determining that a high preference should be given to bulk migrations for delay-stringent services such as augmented reality support, while for applications with less stringent delay requirements, live migration appears as largely preferable.

Integrity signals

Registry

Crossref · 10.1109/ifipnetworking.2015.7145315

Cites

1 of 1 references verified0 citation errors · 0 not checkable

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Each is checked against this paper’s own text: does it say what the citing paper says it does?

  • An optimized cloudlet network demonstrated advantages in traffic volume and reduction of latency.

    “While these authors did not explicitly compare MEC and Cloud performance parameters, the results demonstrated advantages in an optimized “cloudlet network” in terms of traffic volume and reduction of latency [144].”

    From Edge AI: A survey (2023) · cites this paper as [144]

  • The problem addressed in the simulated cloudlet network study was more related to MEC and/or micro data centers than to cloudlets because so many devices were included in the network.

    “The results suggest, however, that the problem addressed in that study was more related to MEC and/or mDCs than to cloudlets because so many devices were included in the network.”

    From Edge AI: A survey (2023) · cites this paper as [144]

  • MEC could generate large amounts of data from users, but user requirements for storage and computational resources still need accurate definitions.

    “MEC could generate large amounts of data from users [144], but user requirements for storage and computational resources still need accurate definitions.”

    From Edge AI: A survey (2023) · cites this paper as [144]

  • Different network architectures will be required for different edge computing scenarios.

    “Different network architectures will also be required for these different scenarios [125,133,144,204].”

    From Edge AI: A survey (2023) · cites this paper as [144]

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Authors
Ceselli, A., Premoli, M., & Secci, S.
Affiliations
University of Milan (IT)
Venue
2015 IFIP Networking Conference (IFIP Networking)
Publisher
IEEE
Published
2015-05
Pages
1-9
OpenAlex
W1533110991
Cited by
69
References
1
Citations by year
2025: 1 · 2023: 2 · 2022: 2 · 2021: 10 · 2020: 6 · 2019: 12 · 2018: 11 · 2017: 18 · 2016: 4 · 2015: 3
FWCI
8.94
Type
conference paper
Language
en
Open access
closed
Locations
  • IFIP Networking Conference (IFIP Networking) (publishedVersion)
  • HAL (submittedVersion)
Funders
Agence Nationale de la Recherche
Topics
  • Physical Sciences › Computer Science › Computer Networks and Communications › IoT and Edge/Fog Computing
  • Physical Sciences › Computer Science › Information Systems › Cloud Computing and Resource Management
  • Physical Sciences › Computer Science › Computer Networks and Communications › Software-Defined Networks and 5G
Keywords
mobile cloud services, access networks, virtual machine placement, virtual machine migration, live migration, user mobility, service level agreements, heuristics, base station assignment, augmented reality

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