Market-based distributed optimization in autonomous networks
By: by Weihong Wang.
Published: 2006
Language: eng
Number of pages: 189
ISBN-13: 9780494160053
Description: This thesis addresses performance optimization for autonomous networks with the following properties. First, the network has no dedicated server for providing resources or services, but relies on all network nodes to cooperatively provide (and consume) them. Likewise, functionalities of organizing, operating, and managing the network are carried out by the nodes themselves. Second, nodes may join and leave the network at any time, and are adaptive in contributing and consuming resources. Third, each node has only limited information about the rest of the network, due to the scale and the highly dynamic nature of the network.Recognizing the advantages and disadvantages of existing proposals, this thesis proposes a set of market-based resource management mechanisms that regulate the provision and allocation of resources in a distributed manner using service prices. We model nodes as utility-maximizing economic agents. Their individual decisions will collectively determine the provision, allocation, and usage of resources, as well as the performance of the network. By designing the distributed market mechanisms, our objective is to properly guide the decisions of participating nodes, so that the resulting network performance parameters approach those determined by network-centric centralized optimization methods.The thesis has two major contributions. First, for different resource sharing scenarios, we have designed appropriate market models and utility functions that capture relevant Quality-of-Service requirements and, with theoretical guarantees, drive the resource allocation efficiency towards the optimum. Second, we have proposed practical and efficient solutions to the utility-maximizing problems for individual nodes, so that the effectiveness of corresponding market models is maximally attained in realistic networking conditions. The thesis has presented an interdisciplinary work, combining concepts and algorithms from system control, system identification, and machine learning to overcome the limitations of underlying economic models.The proposed market models and decision making algorithms will be explained based on three application scenarios that occur most often in the overlay networking reality. With both theoretical analysis and simulation results, we have demonstrated the feasibility and effectiveness of a range of market-based schemes that optimally manage network resources in a distributed fashion.
Notes: Source: Dissertation Abstracts International, Volume: 67-07, Section: B, page: 3921.

Advisor: Baochun Li.

Thesis (Ph.D.)--University of Toronto, 2006.

Includes bibliograophic references.

Electronic version licensed for access by U. of T. users.