Matching Items (510)
Filtering by
- All Subjects: Creative Project
Description
Communication networks, both wired and wireless, are expected to have a certain level of fault-tolerance capability.These networks are also expected to ensure a graceful degradation in performance when some of the network components fail. Traditional studies on fault tolerance in communication networks, for the most part, make no assumptions regarding the location of node/link faults, i.e., the faulty nodes and links may be close to each other or far from each other. However, in many real life scenarios, there exists a strong spatial correlation among the faulty nodes and links. Such failures are often encountered in disaster situations, e.g., natural calamities or enemy attacks. In presence of such region-based faults, many of traditional network analysis and fault-tolerant metrics, that are valid under non-spatially correlated faults, are no longer applicable. To this effect, the main thrust of this research is design and analysis of robust networks in presence of such region-based faults. One important finding of this research is that if some prior knowledge is available on the maximum size of the region that might be affected due to a region-based fault, this piece of knowledge can be effectively utilized for resource efficient design of networks. It has been shown in this dissertation that in some scenarios, effective utilization of this knowledge may result in substantial saving is transmission power in wireless networks. In this dissertation, the impact of region-based faults on the connectivity of wireless networks has been studied and a new metric, region-based connectivity, is proposed to measure the fault-tolerance capability of a network. In addition, novel metrics, such as the region-based component decomposition number(RBCDN) and region-based largest component size(RBLCS) have been proposed to capture the network state, when a region-based fault disconnects the network. Finally, this dissertation presents efficient resource allocation techniques that ensure tolerance against region-based faults, in distributed file storage networks and data center networks.
ContributorsBanerjee, Sujogya (Author) / Sen, Arunabha (Thesis advisor) / Xue, Guoliang (Committee member) / Richa, Andrea (Committee member) / Hurlbert, Glenn (Committee member) / Arizona State University (Publisher)
Created2013
Description
Data mining is increasing in importance in solving a variety of industry problems. Our initiative involves the estimation of resource requirements by skill set for future projects by mining and analyzing actual resource consumption data from past projects in the semiconductor industry. To achieve this goal we face difficulties like data with relevant consumption information but stored in different format and insufficient data about project attributes to interpret consumption data. Our first goal is to clean the historical data and organize it into meaningful structures for analysis. Once the preprocessing on data is completed, different data mining techniques like clustering is applied to find projects which involve resources of similar skillsets and which involve similar complexities and size. This results in "resource utilization templates" for groups of related projects from a resource consumption perspective. Then project characteristics are identified which generate this diversity in headcounts and skillsets. These characteristics are not currently contained in the data base and are elicited from the managers of historical projects. This represents an opportunity to improve the usefulness of the data collection system for the future. The ultimate goal is to match the product technical features with the resource requirement for projects in the past as a model to forecast resource requirements by skill set for future projects. The forecasting model is developed using linear regression with cross validation of the training data as the past project execution are relatively few in number. Acceptable levels of forecast accuracy are achieved relative to human experts' results and the tool is applied to forecast some future projects' resource demand.
ContributorsBhattacharya, Indrani (Author) / Sen, Arunabha (Thesis advisor) / Kempf, Karl G. (Thesis advisor) / Liu, Huan (Committee member) / Arizona State University (Publisher)
Created2013
Description
As networks are playing an increasingly prominent role in different aspects of our lives, there is a growing awareness that improving their performance is of significant importance. In order to enhance performance of networks, it is essential that scarce networking resources be allocated smartly to match the continuously changing network environment. This dissertation focuses on two different kinds of networks - communication and social, and studies resource allocation problems in these networks. The study on communication networks is further divided into different networking technologies - wired and wireless, optical and mobile, airborne and terrestrial. Since nodes in an airborne network (AN) are heterogeneous and mobile, the design of a reliable and robust AN is highly complex. The dissertation studies connectivity and fault-tolerance issues in ANs and proposes algorithms to compute the critical transmission range in fault free, faulty and delay tolerant scenarios. Just as in the case of ANs, power optimization and fault tolerance are important issues in wireless sensor networks (WSN). In a WSN, a tree structure is often used to deliver sensor data to a sink node. In a tree, failure of a node may disconnect the tree. The dissertation investigates the problem of enhancing the fault tolerance capability of data gathering trees in WSN. The advent of OFDM technology provides an opportunity for efficient resource utilization in optical networks and also introduces a set of novel problems, such as routing and spectrum allocation (RSA) problem. This dissertation proves that RSA problem is NP-complete even when the network topology is a chain, and proposes approximation algorithms. In the domain of social networks, the focus of this dissertation is study of influence propagation in presence of active adversaries. In a social network multiple vendors may attempt to influence the nodes in a competitive fashion. This dissertation investigates the scenario where the first vendor has already chosen a set of nodes and the second vendor, with the knowledge of the choice of the first, attempts to identify a smallest set of nodes so that after the influence propagation, the second vendor's market share is larger than the first.
ContributorsShirazipourazad, Shahrzad (Author) / Sen, Arunabha (Committee member) / Xue, Guoliang (Committee member) / Richa, Andrea (Committee member) / Saripalli, Srikanth (Committee member) / Arizona State University (Publisher)
Created2014
Description
Resource allocation is one of the most challenging issues policy decision makers must address. The objective of this thesis is to explore the resource allocation from an economical perspective, i.e., how to purchase resources in order to satisfy customers' requests. In this thesis, we attend to answer the question: when and how to buy resources to fulfill customers' demands with minimum costs?
The first topic studied in this thesis is resource allocation in cloud networks. Cloud computing heralded an era where resources (such as computation and storage) can be scaled up and down elastically and on demand. This flexibility is attractive for its cost effectiveness: the cloud resource price depends on the actual utilization over time. This thesis studies two critical problems in cloud networks, focusing on the economical aspects of the resource allocation in the cloud/virtual networks, and proposes six algorithms to address the resource allocation problems for different discount models. The first problem attends a scenario where the virtual network provider offers different contracts to the service provider. Four algorithms for resource contract migration are proposed under two pricing models: Pay-as-You-Come and Pay-as-You-Go. The second problem explores a scenario where a cloud provider offers k contracts each with a duration and a rate respectively and a customer buys these contracts in order to satisfy its resource demand. This work shows that this problem can be seen as a 2-dimensional generalization of the classic online parking permit problem, and present a k-competitive online algorithm and an optimal online algorithm.
The second topic studied in this thesis is to explore how resource allocation and purchasing strategies work in our daily life. For example, is it worth buying a Yoga pass which costs USD 100 for ten entries, although it will expire at the end of this year? Decisions like these are part of our daily life, yet, not much is known today about good online strategies to buy discount vouchers with expiration dates. This work hence introduces a Discount Voucher Purchase Problem (DVPP). It aims to optimize the strategies for buying discount vouchers, i.e., coupons, vouchers, groupons which are valid only during a certain time period. The DVPP comes in three flavors: (1) Once Expire Lose Everything (OELE): Vouchers lose their entire value after expiration. (2) Once Expire Lose Discount (OELD): Vouchers lose their discount value after expiration. (3) Limited Purchasing Window (LPW): Vouchers have the property of OELE and can only be bought during a certain time window.
This work explores online algorithms with a provable competitive ratio against a clairvoyant offline algorithm, even in the worst case. In particular, this work makes the following contributions: we present a 4-competitive algorithm for OELE, an 8-competitive algorithm for OELD, and a lower bound for LPW. We also present an optimal offline algorithm for OELE and LPW, and show it is a 2-approximation solution for OELD.
The first topic studied in this thesis is resource allocation in cloud networks. Cloud computing heralded an era where resources (such as computation and storage) can be scaled up and down elastically and on demand. This flexibility is attractive for its cost effectiveness: the cloud resource price depends on the actual utilization over time. This thesis studies two critical problems in cloud networks, focusing on the economical aspects of the resource allocation in the cloud/virtual networks, and proposes six algorithms to address the resource allocation problems for different discount models. The first problem attends a scenario where the virtual network provider offers different contracts to the service provider. Four algorithms for resource contract migration are proposed under two pricing models: Pay-as-You-Come and Pay-as-You-Go. The second problem explores a scenario where a cloud provider offers k contracts each with a duration and a rate respectively and a customer buys these contracts in order to satisfy its resource demand. This work shows that this problem can be seen as a 2-dimensional generalization of the classic online parking permit problem, and present a k-competitive online algorithm and an optimal online algorithm.
The second topic studied in this thesis is to explore how resource allocation and purchasing strategies work in our daily life. For example, is it worth buying a Yoga pass which costs USD 100 for ten entries, although it will expire at the end of this year? Decisions like these are part of our daily life, yet, not much is known today about good online strategies to buy discount vouchers with expiration dates. This work hence introduces a Discount Voucher Purchase Problem (DVPP). It aims to optimize the strategies for buying discount vouchers, i.e., coupons, vouchers, groupons which are valid only during a certain time period. The DVPP comes in three flavors: (1) Once Expire Lose Everything (OELE): Vouchers lose their entire value after expiration. (2) Once Expire Lose Discount (OELD): Vouchers lose their discount value after expiration. (3) Limited Purchasing Window (LPW): Vouchers have the property of OELE and can only be bought during a certain time window.
This work explores online algorithms with a provable competitive ratio against a clairvoyant offline algorithm, even in the worst case. In particular, this work makes the following contributions: we present a 4-competitive algorithm for OELE, an 8-competitive algorithm for OELD, and a lower bound for LPW. We also present an optimal offline algorithm for OELE and LPW, and show it is a 2-approximation solution for OELD.
ContributorsHu, Xinhui (Author) / Richa, Andrea (Thesis advisor) / Schmid, Stefan (Committee member) / Sen, Arunabha (Committee member) / Xue, Guoliang (Committee member) / Arizona State University (Publisher)
Created2015
Description
In this dissertation, two interrelated problems of service-based systems (SBS) are addressed: protecting users' data confidentiality from service providers, and managing performance of multiple workflows in SBS. Current SBSs pose serious limitations to protecting users' data confidentiality. Since users' sensitive data is sent in unencrypted forms to remote machines owned and operated by third-party service providers, there are risks of unauthorized use of the users' sensitive data by service providers. Although there are many techniques for protecting users' data from outside attackers, currently there is no effective way to protect users' sensitive data from service providers. In this dissertation, an approach is presented to protecting the confidentiality of users' data from service providers, and ensuring that service providers cannot collect users' confidential data while the data is processed or stored in cloud computing systems. The approach has four major features: (1) separation of software service providers and infrastructure service providers, (2) hiding the information of the owners of data, (3) data obfuscation, and (4) software module decomposition and distributed execution. Since the approach to protecting users' data confidentiality includes software module decomposition and distributed execution, it is very important to effectively allocate the resource of servers in SBS to each of the software module to manage the overall performance of workflows in SBS. An approach is presented to resource allocation for SBS to adaptively allocating the system resources of servers to their software modules in runtime in order to satisfy the performance requirements of multiple workflows in SBS. Experimental results show that the dynamic resource allocation approach can substantially increase the throughput of a SBS and the optimal resource allocation can be found in polynomial time
ContributorsAn, Ho Geun (Author) / Yau, Sik-Sang (Thesis advisor) / Huang, Dijiang (Committee member) / Ahn, Gail-Joon (Committee member) / Santanam, Raghu (Committee member) / Arizona State University (Publisher)
Created2012
Description
This thesis investigates three different resource allocation problems, aiming to achieve two common goals: i) adaptivity to a fast-changing environment, ii) distribution of the computation tasks to achieve a favorable solution. The motivation for this work relies on the modern-era proliferation of sensors and devices, in the Data Acquisition Systems (DAS) layer of the Internet of Things (IoT) architecture. To avoid congestion and enable low-latency services, limits have to be imposed on the amount of decisions that can be centralized (i.e. solved in the ``cloud") and/or amount of control information that devices can exchange. This has been the motivation to develop i) a lightweight PHY Layer protocol for time synchronization and scheduling in Wireless Sensor Networks (WSNs), ii) an adaptive receiver that enables Sub-Nyquist sampling, for efficient spectrum sensing at high frequencies, and iii) an SDN-scheme for resource-sharing across different technologies and operators, to harmoniously and holistically respond to fluctuations in demands at the eNodeB' s layer.
The proposed solution for time synchronization and scheduling is a new protocol, called PulseSS, which is completely event-driven and is inspired by biological networks. The results on convergence and accuracy for locally connected networks, presented in this thesis, constitute the theoretical foundation for the protocol in terms of performance guarantee. The derived limits provided guidelines for ad-hoc solutions in the actual implementation of the protocol.
The proposed receiver for Compressive Spectrum Sensing (CSS) aims at tackling the noise folding phenomenon, e.g., the accumulation of noise from different sub-bands that are folded, prior to sampling and baseband processing, when an analog front-end aliasing mixer is utilized.
The sensing phase design has been conducted via a utility maximization approach, thus the scheme derived has been called Cognitive Utility Maximization Multiple Access (CUMMA).
The framework described in the last part of the thesis is inspired by stochastic network optimization tools and dynamics.
While convergence of the proposed approach remains an open problem, the numerical results here presented suggest the capability of the algorithm to handle traffic fluctuations across operators, while respecting different time and economic constraints.
The scheme has been named Decomposition of Infrastructure-based Dynamic Resource Allocation (DIDRA).
The proposed solution for time synchronization and scheduling is a new protocol, called PulseSS, which is completely event-driven and is inspired by biological networks. The results on convergence and accuracy for locally connected networks, presented in this thesis, constitute the theoretical foundation for the protocol in terms of performance guarantee. The derived limits provided guidelines for ad-hoc solutions in the actual implementation of the protocol.
The proposed receiver for Compressive Spectrum Sensing (CSS) aims at tackling the noise folding phenomenon, e.g., the accumulation of noise from different sub-bands that are folded, prior to sampling and baseband processing, when an analog front-end aliasing mixer is utilized.
The sensing phase design has been conducted via a utility maximization approach, thus the scheme derived has been called Cognitive Utility Maximization Multiple Access (CUMMA).
The framework described in the last part of the thesis is inspired by stochastic network optimization tools and dynamics.
While convergence of the proposed approach remains an open problem, the numerical results here presented suggest the capability of the algorithm to handle traffic fluctuations across operators, while respecting different time and economic constraints.
The scheme has been named Decomposition of Infrastructure-based Dynamic Resource Allocation (DIDRA).
ContributorsFerrari, Lorenzo (Author) / Scaglione, Anna (Thesis advisor) / Bliss, Daniel (Committee member) / Ying, Lei (Committee member) / Reisslein, Martin (Committee member) / Arizona State University (Publisher)
Created2017
Description中国商品期货市场经历30年发展，已初备协调资源分配、对冲经营风险的功能。但受产业自身和期货市场发展的制约，各期货品种市场有效性参差不齐。随着我国经济从增量阶段过渡到存量阶段，期货作为企业的价格管理和风险控制工具的重要性日益凸显，因此研究我国商品期货市场有效性具有非常好的现实意义。
本文开创性的从期货的基本功能——资源配置的角度出发，提出有效市场是指其期货价格能够对本行业社会资源起到合理的调配作用的市场。在内容安排上，本文首先总结了现有国际成熟期货品种的特点并找出能够反映期货对资源配置能力的四个指标假说，分别为期现回归性、利润波动性、库存波动性以及现金流变化，然后通过数学模型证明指标数据和品种成熟度的关联，最后应用该套指标对我国商品市场有效性进行检验。数学方法上，本文先采用Bai-Perron内生多重结构突变模型对时间序列进行突变点检验，然后对断点时间序列分别进行多元回归，并在剔除季节性和周期性后，通过平稳性检验、ARCH效应检验结果来确定相应的Garch模型，并用Garch模型来描述时间序列的波动性。
通过数学验证，我们认为期现回归性、利润波动性、库存波动性以及现金流变化这四个指标可以作为反映期货成熟度的检验指标，用该套方法对国内部分活跃品种检验后发现大连豆粕期货已经具备成熟品种的特征，本文认为豆粕期货市场是有效的；PTA、玉米淀粉期货的四个检验指标在近年来表现出时间序列优化的特点，但因时间较短尚不稳定，可以认为是接近成熟的品种；而螺纹钢和铝期货在多数指标上表现不佳，表明他们对社会资源配置能力较差，因此本文认为螺纹钢和铝期货市场是活跃但非有效的。通过进一步分析，本文认为品种的期现回归性差是制约其资源配置能力发挥的关键因素，而交易标的不明确、
仓单制作难度大、产业参与度低以及期货设计中的其他限制因素又是导致期现回归性差的重要原因。
本文开创性的从期货的基本功能——资源配置的角度出发，提出有效市场是指其期货价格能够对本行业社会资源起到合理的调配作用的市场。在内容安排上，本文首先总结了现有国际成熟期货品种的特点并找出能够反映期货对资源配置能力的四个指标假说，分别为期现回归性、利润波动性、库存波动性以及现金流变化，然后通过数学模型证明指标数据和品种成熟度的关联，最后应用该套指标对我国商品市场有效性进行检验。数学方法上，本文先采用Bai-Perron内生多重结构突变模型对时间序列进行突变点检验，然后对断点时间序列分别进行多元回归，并在剔除季节性和周期性后，通过平稳性检验、ARCH效应检验结果来确定相应的Garch模型，并用Garch模型来描述时间序列的波动性。
通过数学验证，我们认为期现回归性、利润波动性、库存波动性以及现金流变化这四个指标可以作为反映期货成熟度的检验指标，用该套方法对国内部分活跃品种检验后发现大连豆粕期货已经具备成熟品种的特征，本文认为豆粕期货市场是有效的；PTA、玉米淀粉期货的四个检验指标在近年来表现出时间序列优化的特点，但因时间较短尚不稳定，可以认为是接近成熟的品种；而螺纹钢和铝期货在多数指标上表现不佳，表明他们对社会资源配置能力较差，因此本文认为螺纹钢和铝期货市场是活跃但非有效的。通过进一步分析，本文认为品种的期现回归性差是制约其资源配置能力发挥的关键因素，而交易标的不明确、
仓单制作难度大、产业参与度低以及期货设计中的其他限制因素又是导致期现回归性差的重要原因。
ContributorsWang, Ping (Author) / Gu, Bin (Thesis advisor) / Li, Feng (Thesis advisor) / Yan, Hong (Committee member) / Arizona State University (Publisher)
Created2019
Description
How do you convey what’s interesting and important to you as an artist in a digital world of constantly shifting attentions? For many young creatives, the answer is original characters, or OCs. An OC is a character that an artist creates for personal enjoyment, whether based on an already existing story or world, or completely from their own imagination.
As creations made for purely personal interests, OCs are an excellent elevator pitch to talk one creative to another, opening up opportunities for connection in a world where communication is at our fingertips but personal connection is increasingly harder to make. OCs encourage meaningful interaction by offering themselves as muses, avatars, and story pieces, and so much more, where artists can have their characters interact with other creatives through many different avenues such as art-making, table top games, or word of mouth.
In this thesis, I explore the worlds and aesthetics of many creators and their original characters through qualitative research and collaborative art-making. I begin with a short survey of my creative peers, asking general questions about their characters and thoughts on OCs, then move to sketching characters from various creators. I focus my research to a group of seven core creators and their characters, whom I interview and work closely with in order to create a series of seven final paintings of their original characters.
As creations made for purely personal interests, OCs are an excellent elevator pitch to talk one creative to another, opening up opportunities for connection in a world where communication is at our fingertips but personal connection is increasingly harder to make. OCs encourage meaningful interaction by offering themselves as muses, avatars, and story pieces, and so much more, where artists can have their characters interact with other creatives through many different avenues such as art-making, table top games, or word of mouth.
In this thesis, I explore the worlds and aesthetics of many creators and their original characters through qualitative research and collaborative art-making. I begin with a short survey of my creative peers, asking general questions about their characters and thoughts on OCs, then move to sketching characters from various creators. I focus my research to a group of seven core creators and their characters, whom I interview and work closely with in order to create a series of seven final paintings of their original characters.
ContributorsCote, Jacqueline (Author) / Button, Melissa M (Thesis director) / Dove-Viebahn, Aviva (Committee member) / School of Art (Contributor) / Barrett, The Honors College (Contributor)
Created2020-05
Description
In the past ten years, the United States’ sound recording industries have experienced significant decreases in employment opportunities for aspiring audio engineers from economic imbalances in the music industry’s digital streaming era and reductions in government funding for career and technical education (CTE). The Recording Industry Association of America reports promises of music industry sustainability based on increasing annual revenues in paid streaming services and artists’ high creative demand. The rate of new audio engineer entries in the sound recording subsection of the music industry is not viable to support streaming artists’ high demand to engineer new music recordings. Offering CTE programs in secondary education is rare for aspiring engineers with insufficient accessibility to pursue a post-secondary or vocational education because of financial and academic limitations. These aspiring engineers seek alternatives for receiving an informal education in audio engineering on the Internet using video sharing services like YouTube to search for tutorials and improve their engineering skills. The shortage of accessible educational materials on the Internet restricts engineers from advancing their own audio engineering education, reducing opportunities to enter a desperate job market in need of independent, home studio-based engineers. Content creators on YouTube take advantage of this situation and commercialize their own video tutorial series for free and selling paid subscriptions to exclusive content. This is misleading for newer engineers because these tutorials omit important understandings of fundamental engineering concepts. Instead, content creators teach inflexible engineering methodologies that are mostly beneficial to their own way of thinking. Content creators do not often assess the incompatibility of teaching their own methodologies to potential entrants in a profession that demands critical thinking skills requiring applied fundamental audio engineering concepts and techniques. This project analyzes potential solutions to resolve the deficiencies in online audio engineering education and experiments with structuring simple, deliverable, accessible educational content and materials to new entries in audio engineering. Designing clear, easy to follow material to these new entries in audio engineering is essential for developing a strong understanding for the application of fundamental concepts in future engineers’ careers. Approaches to creating and designing educational content requires translating complex engineering concepts through simplified mediums that reduce limitations in learning for future audio engineers.
ContributorsBurns, Triston Connor (Author) / Tobias, Evan (Thesis director) / Libman, Jeff (Committee member) / Department of Information Systems (Contributor) / Barrett, The Honors College (Contributor)
Created2020-05
Description
There has been a recent push for queer fiction, especially in the young adult genre, whose focus is gay and lesbian relationships. This growth is much needed in terms of visibility and the furthering of acceptance, but there are still subjects within the LGBTQ+ community that need to be addressed, including bisexual, asexual, and non-binary erasure. There are many people who claim that these identities do not exist, are labels used as a stepping stone on one's journey to discovering that they are homosexual, or are invented excuses for overtly promiscuous or prudish behavior. The existence of negative stereotypes, particularly those of non-binary individuals, is largely due to a lack of visibility and respectful representation within media and popular culture. However, there is still a dearth of non-binary content in popular literature outside of young adult fiction. Can You See Me? aims to fill the gap in bisexual, asexual, and non-binary representation in adult literature. Each of the four stories that make up this collection deals with an aspect of gender and/or sexuality that has been erased, ignored, or denied visibility in American popular culture. The first story, "We'll Grow Lemon Trees," examines bisexual erasure through the lens of sociolinguistics. A bisexual Romanian woman emigrates to Los Angeles in 1989 and must navigate a new culture, learn new languages, and try to move on from her past life under a dictatorship where speaking up could mean imprisonment or death. The second story "Up, Down, All Around," is about a young genderqueer child and their parents dealing with microaggressions, examining gender norms, and exploring personal identity through imaginary scenarios, each involving an encounter with an unknown entity and a colander. The third story, "Aces High," follows two asexual characters from the day they're born to when they are 28 years old, as they find themselves in pop culture. The two endure identity crises, gender discrimination, erasure, individual obsessions, and prejudice as they learn to accept themselves and embrace who they are. In the fourth and final story, "Mile Marker 72," a gay Mexican man must hide in plain sight as he deals with the death of his partner and coming out to his best friend, whose brother is his partner's murderer.
ContributorsOchser, Jordyn M. (Author) / Bell, Matt (Thesis director) / Free, Melissa (Committee member) / Department of English (Contributor) / Barrett, The Honors College (Contributor)
Created2018-05