Thesis Defense : Auction-based Dynamic Resource Orchestration in Cloud-based Radio Access Networks

Speaker : Mira Morcos
TPT
Date: 23/01/2019
Time: 2:30 pm
Location: LINCS / EIT Digital

Abstract

The paradigm of a Cloud-based RAN (C-RAN) is a key technology that combines the enabling solutions for the 5G requirements in terms of data rate, scalability and cost savings. A C-RAN architecture is based on two key features namely, Centralization, wherein computational resources of base stations, namely Base Band Units (BBUs), are pooled together in a central Cloud, and Virtualization, with the possibility that several Mobile Virtual Network Operators (MVNOs) share the radio resources and the BBU pool in order to reduce operational expenditure costs. In this thesis, we develop a theoretical framework for dynamic resource management in the C-RAN and derive the fundamental performance limits as well as the trade offs among various system parameters.

We specifically propose 3 different resource allocation mechanisms that suit the C-RAN technology and help boost resource utilization efficiency. For each allocation mechanism, we set an auction framework to help generate high revenues.

We design a two-level auction for the allocation of radio resources, in a scenario with a central C-RAN operator, a set of MVNOs and their subscribed users. We tackle the problem of calendaring for radio resource reservation in the C-RAN, a natural context in which bandwidth calendaring can be applied owing to its centralized architecture. An auction-based framework is tailored so as to guarantee profit maximization and a market proof to manipulation. We address joint radio and processing allocation in the context of C-RAN as a combinatorial auction.

Our approaches satisfy fundamental economic properties: truthfulness, individual rationality and computational efficiency. Numerical results demonstrates the performance of our proposal in various network settings and show that our proposals can guarantee efficient outcomes.

Keywords: C-RAN, resource management, auctions