Klein

Qazi, Zafar Ayyub; Penumarthi, Phani Krishna; Sekar, Vyas; Gopalakrishnan, V.; Joshi, Kaustubh; Das, Samir R.

doi:10.1145/2890955.2890961

Cited by 49 publications

(2 citation statements)

References 16 publications

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“…In contrast, SoftBox [49] aim at a separate core network (4G EPC) instance per UE, regardless of its traffic, but this can cause inefficient and uneven resource utilization. Other designs move the entire EPC to the edge to suit the requirements of UAV-based LTE networks [50] or rural community LTE networks [63] while others such as Klein [59] target geographic replication of entire EPC for macro-level scaling.…”

Section: Related Workmentioning

confidence: 99%

CoreKube: An Efficient, Autoscaling and Resilient Mobile Core System

Ferguson,

Larrea,

Marina

2024

GetMobile: Mobile Comp. and Comm.

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Almost everyone on the planet has a mobile phone with data connectivity to the Internet. Mobile (cellular) networks enable ubiquitous and on the move connectivity to such end user devices as well as to a myriad Internet of Things (IoT) devices. At the heart of any mobile network is the mobile core. This essential component not only handles all control functionality (authenticating devices, managing user sessions, mobility, roaming, billing, etc.) but also provides a bridge between connected devices and external networks such as the Internet. Compared to a base station whose operation affects only a small geographical area in its coverage, the mobile core serves a much wider area, so its responsive and reliable operation is key to ensuring good user experience.

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Section: Related Workmentioning

confidence: 99%

CoreKube: An Efficient, Autoscaling and Resilient Mobile Core System

Ferguson,

Larrea,

Marina

2024

GetMobile: Mobile Comp. and Comm.

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“…Network slicing covers two main parts of NG networks, namely core slicing and RAN slicing. The study on mobile core slicing focuses on the virtualization of core NFs [11], combined with the use of mature virtualization technologies (e.g., Docker [12]), thus enabling scalability [13] and augmenting flexibility [14]. RAN slicing, on the other hand, focuses on virtualizing RAN functions and resources, thus facilitating the sharing of gNBs among different slices.…”

Section: Related Workmentioning

confidence: 99%

SO-RAN: Dynamic RAN Slicing via Joint Functional Splitting and MEC Placement

Ojaghi

Adelantado

Verikoukis

2023

IEEE Trans. Veh. Technol.

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Next-Generation (NG) mobile networks are expected to revolutionize wireless communication systems, facilitating the deployment of critical applications with stringent Quality of Service (QoS) requirements. Multi-access Edge Computing (MEC) and Radio Access Network (RAN) slicing are considered vital mechanisms of upcoming NG systems as they allow creation of end-to-end isolated RAN slices and increase of serving mobile data traffic on edge. The efficient deployment of RAN functions promises flexible and disaggregated architectures for the diversified needs of NG networks. In this work, we propose a novel optimization approach that minimizes RAN/MEC economic costs and maximizes served traffic. This framework creates isolated RAN slices by optimal placement of RAN and MEC functions per slice, which solves the problem of operating cost-efficient edge networks and increases the served traffic with diverse QoS requirements. We first formulate our framework as a convex and linear problem and then decompose it using a distributed method that accelerates the performance and guarantees the optimal global solution. Our results show that our proposed work better uses the spectrum, and there is a trade-off between the achieved throughput and the cost incurred to the network.

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