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ORCID

https://orcid.org/0000-0002-2648-4985

Access Type

Campus-Only Access for Five (5) Years

Document Type

thesis

Embargo Period

9-1-2020

Degree Program

Electrical & Computer Engineering

Degree Type

Master of Science in Electrical and Computer Engineering (M.S.E.C.E.)

Year Degree Awarded

2020

Month Degree Awarded

September

Abstract

The sixth-generation (6G) of wireless communication systems will significantly rely on fog/edge network architectures for service provisioning. To satisfy stringent quality of service requirements using dynamically available resources at the edge, new network access schemes are needed. In this paper, we consider a cognitive dynamic edge/fog network where primary users (PUs) may temporarily share their resources and act as fog nodes for secondary users (SUs). We develop strategies for distributed dynamic fog probing so SUs can find out available connections to access the fog nodes. To handle the large-state space of the connectivity availability that includes availability of channels, computing resources, and fog nodes, and the partial observability of the states, we design a novel distributed Deep Q-learning Fog Probing (DQFP) algorithm. Our goal is to develop multi-user strategies for accessing fog nodes in a distributed manner without any centralized scheduling or message passing. By using cooperative and competitive utility functions, we analyze the impact of the multi-user dynamics on the connectivity availability and establish design principles for our DQFP algorithm.

First Advisor

Beatriz Lorenzo

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