Use this URL to cite or link to this record in EThOS: http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.484426
Title: Pricing and resource allocation for telecommunications networks using revenue management
Author: Zachariadis, Grigorios
ISNI:       0000 0000 7167 1056
Awarding Body: Imperial College London
Current Institution: Imperial College London
Date of Award: 2008
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Abstract:
In this thesis we develop models for several types of telecommunications services, and obtain the optimal prices and resource allocation for the offered services. We develop our solutions within a revenue management framework, whose underlying aims is to match the offered services to the needs of the market in a way which maximises the provider's income. Firstly, a novel solution for the problem of calculating the optimal static prices and offered quality of service (QoS) is proposed for a link with flows belonging to multiple classes of service with the aim of maximising the provider's income. Two solutions are developed. The first is based on the limiting regime (LR) approximation, which reduces the complexity of the problem, and, depending on the scale of the problem, offers results within 2%-30% of the optimal ones. The second is a heuristic improvement of the LR solution, with results within 0.1-3% of the optimal ones. The obtained solutions are then extended to a network environment using a decomposition approach. We then develop a novel framework where offered prices and QoS are allowed to be actively modified by the provider, depending on the demand and the congestion of the system. Using dynamic programming we obtain a solution to the problem and we observe that using this approach, the provider's income increases between 2%-20% compared to the static approach. The problem of distributing load among different routes using pricing is addressed next. In this case, the demand for different routes partially depends on the prices and QoS for each route, and we propose methods to calculate the optimal prices for each route. Finally, we develop a framework for booking services in advance in a system with multiple classes of service. Then the optimal pricing and resource allocation are calculated with the aim of maximising the provider's income.
Supervisor: Not available Sponsor: Not available
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID: uk.bl.ethos.484426  DOI: Not available
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