Performance Improvements in Software-Defined and Virtualized Wireless Networks

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  • In this dissertation, we investigate performance improvements in software-defined and virtualized wireless networks with advanced in-network caching and mobile edge computing (MEC).Wireless network virtualization (WNV), software-defined networking (SDN), MEC and in-network caching are new promising technologies in next generation wireless networks. Traditionally, in-network caching and MEC have been addressed separately from WNV and SDN. However, it is necessary to jointly consider in-network caching and MEC with WNV and SDN together to provide better services in future wireless networks. Therefore, in this dissertation, we propose to integrate WNV and SDN with in-network caching and MEC in order to improve the end-to-end network performance in wireless networks.We firstly show that jointly considering WNV and in-network caching is necessary and develop an efficient alternating direction method of multipliers (ADMM)-based distributed virtual resource allocation and in-network caching scheme. Secondly, motivated by the experience of user equipment admission control in traditional wireless networks, we propose a novel concept of virtual network (VN) admission control for wireless virtualization. By limiting the number of VNs embedded in the physical network, VN admission control can effectively guarantee the quality of service experienced by users of VNs and maximize the utilization of the physical networks at the same time. Thirdly, we propose to jointly optimize video streaming, bandwidth provisioning and caching strategies in software-defined wireless networks (SDWNs) with limited network resources and quality of service (QoE) requirements. We design a novel mechanism to jointly provide proactive caching, bandwidth provisioning and adaptive video streaming. Lastly, in addition to caching, we integrate MEC into the considered SDWN to enhance the video service in next generation wireless networks. We utilize dual-decomposition method and ADMM design a decentralized algorithm to solve the proposed problems. Simulation results are presented to show the effectiveness of the proposed schemes.

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  • Copyright © 2017 the author(s). Theses may be used for non-commercial research, educational, or related academic purposes only. Such uses include personal study, research, scholarship, and teaching. Theses may only be shared by linking to Carleton University Institutional Repository and no part may be used without proper attribution to the author. No part may be used for commercial purposes directly or indirectly via a for-profit platform; no adaptation or derivative works are permitted without consent from the copyright owner.
Date Created
  • 2017


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