Virtualization Framework for Cellular Networks with Downlink Rate Coverage Probability Constraints

Chatterjee, Shubhajeet; Abdel-Rahman, Mohammad J.; MacKenzie, Allen B.

doi:10.1109/glocom.2018.8647821

Cited by 6 publications

(4 citation statements)

References 15 publications

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“…Most of prior work related to SFC and VNF deployment do not account for coverage constraints [15,16]. The design of efficient allocation mechanisms for virtualized radio resources has been recently addressed in [17]. This paper aims at minimizing the leasing cost of Base Stations (BSs) so as to meet SP demands, while providing, with a given probability, a minimum data rate for any user located in the BS coverage area.…”

Section: Related Workmentioning

confidence: 99%

Radio Resource Provisioning for Network Slicing with Coverage Constraints

Luu

Kerboeuf

Mouradian

et al. 2020

ICC 2020 - 2020 IEEE International Conference on Communications (ICC)

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With network slicing, Mobile Network Operators can accommodate on a common network infrastructure various customized services from Service Providers (SPs). Usually, the Service Function Chains belonging to a slice are deployed on a best-effort basis. Nothing ensures that enough infrastructure resources can be allocated to satisfy the demands of SPs. This paper introduces a radio resources provisioning approach to satisfy the demands of slices with radio coverage constraints. By provisioning, we ensure that enough resources are reserved for further SFC deployment. Numerical results show the effectiveness of the proposed provisioning framework for a slice deployment on a mobile network infrastructure satisfying a minimum data rate for users in the geographical areas where services have to be made available.

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Section: Related Workmentioning

confidence: 99%

Radio Resource Provisioning for Network Slicing with Coverage Constraints

Luu

Kerboeuf

Mouradian

et al. 2020

ICC 2020 - 2020 IEEE International Conference on Communications (ICC)

View full text Add to dashboard Cite

show abstract

“…The design of efficient allocation mechanisms for virtualized radio resources has been recently addressed in [29]. This paper aims at minimizing the leasing cost of BSs so as to meet SP demands, while providing, with a given probability, a minimum data rate for any user located in their coverage area.…”

Section: B Related Workmentioning

confidence: 99%

“…This work borrows the slice resource provisioning approach introduced in [28], and adapts it to the joint radio and network infrastructure resource provisioning. Constraints related to the infrastructure network considered in [17,18,27,28] are combined with coverage and radio resource constraints introduced in [29,30,31,32].…”

Section: Main Contributionsmentioning

confidence: 99%

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Aggregated Resource Provisioning for Network Slices

Luu

Kieffer

Mouradian

et al. 2018

2018 IEEE Global Communications Conference (GLOBECOM)

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Network slicing appears as a key enabler for the future 5G networks. Mobile Network Operators create various slices for Service Providers (SP) to accommodate customized services. As network slices are operated on a common network infrastructure owned by some Infrastructure Provider (InP), sharing the resources across a set of network slices is important for future deployment. Moreover, in many situations, slices have to be deployed over some geographical area: coverage as well as minimum per-user rate constraints have then to be taken into account.Usually, the various Service Function Chains (SFCs) belonging to a slice are deployed on a best-effort basis. Nothing ensures that the InP will be able to allocate enough resources to cope with the increasing demands of some SP. This paper takes the InP perspective and proposes a slice resource provisioning approach to cope with multiple slice demands in terms of computing, storage, coverage, and rate constraints.The resource requirements of the various Service Function Chains to be deployed within a slice are aggregated within a graph of Slice Resource Demands (SRD). Coverage and rate constraints are also taken into account in the SRD. Infrastructure nodes and links have then to be provisioned so as to satisfy all types of resource demands. This problem leads to a Mixed Integer Linear Programming formulation. A two-step deployment approach is considered, with several variants, depending on whether the constraints of each slide to be deployed are taken into account sequentially or jointly. Once provisioning has been performed, any slice deployment strategy may be considered on the reduced-size infrastructure graph representing the nodes and links on which resources have been provisioned.Simulation results demonstrate the effectiveness of the proposed approach compared to a more classical direct slice embedding approach.

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Indoor Millimeter-Wave Systems: Design and Performance Evaluation

et al. 2020

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Indoor areas, such as offices and shopping malls, are a natural environment for initial millimeterwave (mmWave) deployments. While we already have the technology that enables us to realize indoor mmWave deployments, there are many remaining challenges associated with system-level design and planning for such. The objective of this article is to bring together multiple strands of research to provide a comprehensive and integrated framework for the design and performance evaluation of indoor mmWave systems. The paper introduces the framework with a status update on mmWave technology, including ongoing fifth generation (5G) wireless standardization efforts, and then moves on to experimentally-validated channel models that inform performance evaluation and deployment planning.

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Virtualization Framework for Cellular Networks with Downlink Rate Coverage Probability Constraints

Cited by 6 publications

References 15 publications

Radio Resource Provisioning for Network Slicing with Coverage Constraints

Radio Resource Provisioning for Network Slicing with Coverage Constraints

Aggregated Resource Provisioning for Network Slices

Indoor Millimeter-Wave Systems: Design and Performance Evaluation

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