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University of Texas – Austin

1. -3979-4771. Design and performance of resource allocation mechanisms for network slicing.

Degree: Electrical and Computer Engineering, 2018, University of Texas – Austin

Next generation wireless networks are expected to handle an exponential increase in demand for capacity generated by a collection of tenants and/or services with heterogeneous requirements. Multi-tenant network sharing, enabled through virtualization and network slicing, offers the opportunity to reduce operational and deployment costs, and the challenge of managing resource allocations among multiple tenants serving possibly mobile diverse customers. When designing shared radio resource allocation mechanisms, it is as important to provide tenants with customization and isolation guarantees, as it is to achieve high resource utilization and to do so via low complexity and easy to implement algorithms. This thesis is devoted to the design and analysis of resource allocation mechanisms that meet these objectives. We propose a sharing model in which tenants are assigned a share/budget of a pool of network resources. This share is then redistributed in the form of weights amongst users, which in turn drive dynamic resource allocations which are partially able to adapt to the traffic demands on, and requirements of, different slices customer populations. We propose and analyze two approaches for redistributing slices’ share among customers which we classify into their associated (i) cooperative, and (ii) competitive resource allocations. In the cooperative resource allocation setting, a pre-established policy is proposed, in which resources are eventually assigned in proportion to the slice’s share and the relative number of active users in currently has at a resource. This is shown to be socially optimal in a particular setting and simple to implement, with statistical multiplexing gains that increase with the number of tenants and the size of the resource pool. These gains stem from the ability of the scheme to adapt to dynamic loads leading to an up to 50% network capacity savings with respect to static allocations. We further improve these gains by presenting a framework that combines resource allocation and wireless user association which uses limited computational, information, and handoff overheads. However, using our cooperative scheme over a large pool of resources restricts the degree to which a slice can differentiate its customers’ performance at a per resource level. Thus, we study how this trade-off affects the network utility and propose a mechanism to determine an optimal partition the resources into a collection of self-managed pools under cooperative resource allocations. Our competitive resource allocation approach enables tenants to reap the performance benefits of sharing while retaining the ability to customize their own users’ allocations. This setting results in a network slicing game in which each tenant reacts to the user allocations of the others so as to maximize its own customers’ utility. We show that, under appropriate conditions, the game associated with such strategic behavior converges to a Nash equilibrium. At the Nash equilibrium, a ten- ant always achieves the same, or better, utility… Advisors/Committee Members: De Veciana, Gustavo (advisor), Banchs Roca, Albert (advisor), Andrews, Jeffrey G (committee member), Baccelli, Francois (committee member), Shakkottai, Sanjay (committee member), Hasenbein, John J (committee member).

Subjects/Keywords: Network slicing; Cellular communications; Resource allocation; Algorithm design and analysis; Heuristic algorithms; Mobile communication; Dynamic scheduling; Wireless networks; Multitenant networks; Game theory

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APA (6th Edition):

-3979-4771. (2018). Design and performance of resource allocation mechanisms for network slicing. (Thesis). University of Texas – Austin. Retrieved from http://hdl.handle.net/2152/68642

Note: this citation may be lacking information needed for this citation format:
Author name may be incomplete
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16th Edition):

-3979-4771. “Design and performance of resource allocation mechanisms for network slicing.” 2018. Thesis, University of Texas – Austin. Accessed January 15, 2019. http://hdl.handle.net/2152/68642.

Note: this citation may be lacking information needed for this citation format:
Author name may be incomplete
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7th Edition):

-3979-4771. “Design and performance of resource allocation mechanisms for network slicing.” 2018. Web. 15 Jan 2019.

Note: this citation may be lacking information needed for this citation format:
Author name may be incomplete

Vancouver:

-3979-4771. Design and performance of resource allocation mechanisms for network slicing. [Internet] [Thesis]. University of Texas – Austin; 2018. [cited 2019 Jan 15]. Available from: http://hdl.handle.net/2152/68642.

Note: this citation may be lacking information needed for this citation format:
Author name may be incomplete
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

-3979-4771. Design and performance of resource allocation mechanisms for network slicing. [Thesis]. University of Texas – Austin; 2018. Available from: http://hdl.handle.net/2152/68642

Note: this citation may be lacking information needed for this citation format:
Author name may be incomplete
Not specified: Masters Thesis or Doctoral Dissertation

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