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Title
SDN based Layered Backhaul Optimization and Hardware Acceleration
Description
Existing radio access networks (RANs) allow only for very limited sharing of thecommunication and computation resources among wireless operators and heterogeneous
wireless technologies. The introduced LayBack architecture facilitates communication
and computation resource sharing among different wireless operators and technologies.
LayBack organizes the RAN communication and multiaccess edge computing (MEC)
resources into layers, including a devices layer, a radio node (enhanced Node B and
access point) layer, and a gateway layer. The layback optimization study addresses
the problem of how a central SDN orchestrator can flexibly share the total backhaul
capacity of the various wireless operators among their gateways and radio nodes
(e.g., LTE enhanced Node Bs or Wi-Fi access points). In order to facilitate
flexible network service virtualization and migration, network functions (NFs) are increasingly
executed by software modules as so-called "softwarized NFs" on General-Purpose
Computing (GPC) platforms and infrastructures. GPC platforms are not specifically
designed to efficiently execute NFs with their typically intense Input/Output (I/O)
demands. Recently, numerous hardware-based accelerations have been developed to
augment GPC platforms and infrastructures, e.g., the central processing unit (CPU)
and memory, to efficiently execute NFs. The computing capabilities of client devices
are continuously increasing; at the same time, demands for ultra-low latency (ULL)
services are increasing. These ULL services can be provided by migrating some
micro-service container computations from the cloud and multi-access edge computing
(MEC) to the client devices.
Date Created
2022
Contributors
- Shantharama, Prateek (Author)
- Reisslein, Martin (Thesis advisor)
- McGarry, Michael (Committee member)
- Thyagaturu, Akhilesh (Committee member)
- Zhang, Yanchao (Committee member)
- Arizona State University (Publisher)
Topical Subject
Resource Type
Extent
442 pages
Language
eng
Copyright Statement
In Copyright
Primary Member of
Peer-reviewed
No
Open Access
No
Handle
https://hdl.handle.net/2286/R.2.N.168528
Level of coding
minimal
Cataloging Standards
Note
Partial requirement for: Ph.D., Arizona State University, 2022
Field of study: Computer Engineering
System Created
- 2022-08-22 04:25:03
System Modified
- 2022-08-22 04:25:26
- 2 years 2 months ago
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