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Central Florida

Resource Management in Large-scale Systems

Abstract

dc:description.abstract

The focus of this thesis is resource management in large-scale systems. Our primary concerns are energy management and practical principles for self-organization and self-management. The main contributions of our work are: 1. Models. We proposed several models for different aspects of resource management, e.g., energy-aware load balancing and application scaling for the cloud ecosystem, hierarchical architecture model for self-organizing and self-manageable systems and a new cloud delivery model based on auction-driven self-organization approach. 2. Algorithms. We also proposed several different algorithms for the models described above. Algorithms such as coalition formation, combinatorial auctions and clustering algorithm for scale-free organizations of scale-free networks. 3. Evaluation. Eventually we conducted different evaluations for the proposed models and algorithms in order to verify them. All the simulations reported in this thesis had been carried out on different instances and services of Amazon Web Services (AWS). All of these modules will be discussed in detail in the following chapters respectively.

Author and committee

dc:creator, dc:contributor.*
Author dc:creator
  • Paya, Ashkan
Contributors dc:contributor
  • Marinescu, Dan

Subjects

dc:subject × 4

Rights

Language dc:language
English

Identifiers

dc:identifier.*
Identifier
CFE0005862
OAI identifier oai:identifier
oai:stars.library.ucf.edu:etd-1706

Chain of custody

source
Harvested from
Central Florida
Base URL
stars.library.ucf.edu/do/oai/
Last updated
2026-07-24
Source record
OAI-PMH GetRecord
citation

Paya, Ashkan. Resource Management in Large-scale Systems. 2015. https://stars.library.ucf.edu/etd/707