Matching Items (73)
Filtering by

Clear all filters

152236-Thumbnail Image.png
Description
Continuous Delivery, as one of the youngest and most popular member of agile model family, has become a popular concept and method in software development industry recently. Instead of the traditional software development method, which requirements and solutions must be fixed before starting software developing, it promotes adaptive planning, evolutionary

Continuous Delivery, as one of the youngest and most popular member of agile model family, has become a popular concept and method in software development industry recently. Instead of the traditional software development method, which requirements and solutions must be fixed before starting software developing, it promotes adaptive planning, evolutionary development and delivery, and encourages rapid and flexible response to change. However, several problems prevent Continuous Delivery to be introduced into education world. Taking into the consideration of the barriers, we propose a new Cloud based Continuous Delivery Software Developing System. This system is designed to fully utilize the whole life circle of software developing according to Continuous Delivery concepts in a virtualized environment in Vlab platform.
ContributorsDeng, Yuli (Author) / Huang, Dijiang (Thesis advisor) / Davulcu, Hasan (Committee member) / Chen, Yinong (Committee member) / Arizona State University (Publisher)
Created2013
152133-Thumbnail Image.png
Description
I compare the effect of anonymous social network ratings (Yelp.com) and peer group recommendations on restaurant demand. I conduct a two-stage choice experiment in which restaurant visits in the first stage are informed by online social network reviews from Yelp.com, and visits in the second stage by peer network reviews.

I compare the effect of anonymous social network ratings (Yelp.com) and peer group recommendations on restaurant demand. I conduct a two-stage choice experiment in which restaurant visits in the first stage are informed by online social network reviews from Yelp.com, and visits in the second stage by peer network reviews. I find that anonymous reviewers have a stronger effect on restaurant preference than peers. I also compare the power of negative reviews with that of positive reviews. I found that negative reviews are more powerful compared to the positive reviews on restaurant preference. More generally, I find that in an environment of high attribute uncertainty, information gained from anonymous experts through social media is likely to be more influential than information obtained from peers.
ContributorsTiwari, Ashutosh (Author) / Richards, Timothy J. (Thesis advisor) / Qiu, Yueming (Committee member) / Grebitus, Carola (Committee member) / Arizona State University (Publisher)
Created2013
151336-Thumbnail Image.png
Description
Over 2 billion people are using online social network services, such as Facebook, Twitter, Google+, LinkedIn, and Pinterest. Users update their status, post their photos, share their information, and chat with others in these social network sites every day; however, not everyone shares the same amount of information. This thesis

Over 2 billion people are using online social network services, such as Facebook, Twitter, Google+, LinkedIn, and Pinterest. Users update their status, post their photos, share their information, and chat with others in these social network sites every day; however, not everyone shares the same amount of information. This thesis explores methods of linking publicly available data sources as a means of extrapolating missing information of Facebook. An application named "Visual Friends Income Map" has been created on Facebook to collect social network data and explore geodemographic properties to link publicly available data, such as the US census data. Multiple predictors are implemented to link data sets and extrapolate missing information from Facebook with accurate predictions. The location based predictor matches Facebook users' locations with census data at the city level for income and demographic predictions. Age and relationship based predictors are created to improve the accuracy of the proposed location based predictor utilizing social network link information. In the case where a user does not share any location information on their Facebook profile, a kernel density estimation location predictor is created. This predictor utilizes publicly available telephone record information of all people with the same surname of this user in the US to create a likelihood distribution of the user's location. This is combined with the user's IP level information in order to narrow the probability estimation down to a local regional constraint.
ContributorsMao, Jingxian (Author) / Maciejewski, Ross (Thesis advisor) / Farin, Gerald (Committee member) / Wang, Yalin (Committee member) / Arizona State University (Publisher)
Created2012
151275-Thumbnail Image.png
Description
The pay-as-you-go economic model of cloud computing increases the visibility, traceability, and verifiability of software costs. Application developers must understand how their software uses resources when running in the cloud in order to stay within budgeted costs and/or produce expected profits. Cloud computing's unique economic model also leads naturally to

The pay-as-you-go economic model of cloud computing increases the visibility, traceability, and verifiability of software costs. Application developers must understand how their software uses resources when running in the cloud in order to stay within budgeted costs and/or produce expected profits. Cloud computing's unique economic model also leads naturally to an earn-as-you-go profit model for many cloud based applications. These applications can benefit from low level analyses for cost optimization and verification. Testing cloud applications to ensure they meet monetary cost objectives has not been well explored in the current literature. When considering revenues and costs for cloud applications, the resource economic model can be scaled down to the transaction level in order to associate source code with costs incurred while running in the cloud. Both static and dynamic analysis techniques can be developed and applied to understand how and where cloud applications incur costs. Such analyses can help optimize (i.e. minimize) costs and verify that they stay within expected tolerances. An adaptation of Worst Case Execution Time (WCET) analysis is presented here to statically determine worst case monetary costs of cloud applications. This analysis is used to produce an algorithm for determining control flow paths within an application that can exceed a given cost threshold. The corresponding results are used to identify path sections that contribute most to cost excess. A hybrid approach for determining cost excesses is also presented that is comprised mostly of dynamic measurements but that also incorporates calculations that are based on the static analysis approach. This approach uses operational profiles to increase the precision and usefulness of the calculations.
ContributorsBuell, Kevin, Ph.D (Author) / Collofello, James (Thesis advisor) / Davulcu, Hasan (Committee member) / Lindquist, Timothy (Committee member) / Sen, Arunabha (Committee member) / Arizona State University (Publisher)
Created2012
151593-Thumbnail Image.png
Description
Although aggression is sometimes thought to be maladaptive, evolutionary theories of resource control and dominance posit that aggression may be used to gain and maintain high social prominence within the peer group. The success of using aggression to increase social prominence may depend on the form of aggression used (relational

Although aggression is sometimes thought to be maladaptive, evolutionary theories of resource control and dominance posit that aggression may be used to gain and maintain high social prominence within the peer group. The success of using aggression to increase social prominence may depend on the form of aggression used (relational versus physical), the gender of the aggressor, and the prominence of the victim. Thus, the current study examined the associations between aggression and victimization and social prominence. In addition, the current study extended previous research by examining multiple forms of aggression and victimization and conceptualizing and measuring social prominence using social network analysis. Participants were 339 6th grade students from ethnically diverse backgrounds (50.4% girls). Participants completed a peer nomination measure assessing relational and physical aggression and victimization. They also nominated friends within their grade, which were used to calculate three indices of social prominence, using social network analysis. As expected, results indicated that relational aggression was associated with higher social prominence, particularly for girls, whereas physical aggression was less robustly associated with social prominence. Results for victimization were less clear, but suggested that, for girls, those at mid-levels of social prominence were most highly victimized. For boys, results indicated that those both high and low in prominence were most highly relationally victimized, and those at mid-levels of prominence were most highly physically victimized. These findings help inform intervention work focused on decreasing overall levels of aggressive behavior.
ContributorsAndrews, Naomi C. Z (Author) / Hanish, Laura D. (Thesis advisor) / Martin, Carol Lynn (Committee member) / Updegraff, Kimberly A (Committee member) / Arizona State University (Publisher)
Created2013
151605-Thumbnail Image.png
Description
In most social networking websites, users are allowed to perform interactive activities. One of the fundamental features that these sites provide is to connecting with users of their kind. On one hand, this activity makes online connections visible and tangible; on the other hand, it enables the exploration of our

In most social networking websites, users are allowed to perform interactive activities. One of the fundamental features that these sites provide is to connecting with users of their kind. On one hand, this activity makes online connections visible and tangible; on the other hand, it enables the exploration of our connections and the expansion of our social networks easier. The aggregation of people who share common interests forms social groups, which are fundamental parts of our social lives. Social behavioral analysis at a group level is an active research area and attracts many interests from the industry. Challenges of my work mainly arise from the scale and complexity of user generated behavioral data. The multiple types of interactions, highly dynamic nature of social networking and the volatile user behavior suggest that these data are complex and big in general. Effective and efficient approaches are required to analyze and interpret such data. My work provide effective channels to help connect the like-minded and, furthermore, understand user behavior at a group level. The contributions of this dissertation are in threefold: (1) proposing novel representation of collective tagging knowledge via tag networks; (2) proposing the new information spreader identification problem in egocentric soical networks; (3) defining group profiling as a systematic approach to understanding social groups. In sum, the research proposes novel concepts and approaches for connecting the like-minded, enables the understanding of user groups, and exposes interesting research opportunities.
ContributorsWang, Xufei (Author) / Liu, Huan (Thesis advisor) / Kambhampati, Subbarao (Committee member) / Sundaram, Hari (Committee member) / Ye, Jieping (Committee member) / Arizona State University (Publisher)
Created2013
151524-Thumbnail Image.png
Description
Process migration is a heavily studied research area and has a number of applications in distributed systems. Process migration means transferring a process running on one machine to another such that it resumes execution from the point at which it was suspended. The conventional approach to implement process migration is

Process migration is a heavily studied research area and has a number of applications in distributed systems. Process migration means transferring a process running on one machine to another such that it resumes execution from the point at which it was suspended. The conventional approach to implement process migration is to move the entire state information of the process (including hardware context, virtual memory, files etc.) from one machine to another. Copying all the state information is costly. This thesis proposes and demonstrates a new approach of migrating a process between two cores of Intel Single Chip Cloud (SCC), an experimental 48-core processor by Intel, with each core running a separate instance of the operating system. In this method the amount of process state to be transferred from one core's memory to another is reduced by making use of special registers called Lookup tables (LUTs) present on each core of SCC. Thus this new approach is faster than the conventional method.
ContributorsJain, Vaibhav (Author) / Dasgupta, Partha (Thesis advisor) / Shriavstava, Aviral (Committee member) / Davulcu, Hasan (Committee member) / Arizona State University (Publisher)
Created2013
152495-Thumbnail Image.png
Description
Attribute Based Access Control (ABAC) mechanisms have been attracting a lot of interest from the research community in recent times. This is especially because of the flexibility and extensibility it provides by using attributes assigned to subjects as the basis for access control. ABAC enables an administrator of a server

Attribute Based Access Control (ABAC) mechanisms have been attracting a lot of interest from the research community in recent times. This is especially because of the flexibility and extensibility it provides by using attributes assigned to subjects as the basis for access control. ABAC enables an administrator of a server to enforce access policies on the data, services and other such resources fairly easily. It also accommodates new policies and changes to existing policies gracefully, thereby making it a potentially good mechanism for implementing access control in large systems, particularly in today's age of Cloud Computing. However management of the attributes in ABAC environment is an area that has been little touched upon. Having a mechanism to allow multiple ABAC based systems to share data and resources can go a long way in making ABAC scalable. At the same time each system should be able to specify their own attribute sets independently. In the research presented in this document a new mechanism is proposed that would enable users to share resources and data in a cloud environment using ABAC techniques in a distributed manner. The focus is mainly on decentralizing the access policy specifications for the shared data so that each data owner can specify the access policy independent of others. The concept of ontologies and semantic web is introduced in the ABAC paradigm that would help in giving a scalable structure to the attributes and also allow systems having different sets of attributes to communicate and share resources.
ContributorsPrabhu Verleker, Ashwin Narayan (Author) / Huang, Dijiang (Thesis advisor) / Ahn, Gail-Joon (Committee member) / Dasgupta, Partha (Committee member) / Arizona State University (Publisher)
Created2014
152500-Thumbnail Image.png
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

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
152337-Thumbnail Image.png
Description
In contemporary society, sustainability and public well-being have been pressing challenges. Some of the important questions are:how can sustainable practices, such as reducing carbon emission, be encouraged? , How can a healthy lifestyle be maintained?Even though individuals are interested, they are unable to adopt these behaviors due to resource constraints.

In contemporary society, sustainability and public well-being have been pressing challenges. Some of the important questions are:how can sustainable practices, such as reducing carbon emission, be encouraged? , How can a healthy lifestyle be maintained?Even though individuals are interested, they are unable to adopt these behaviors due to resource constraints. Developing a framework to enable cooperative behavior adoption and to sustain it for a long period of time is a major challenge. As a part of developing this framework, I am focusing on methods to understand behavior diffusion over time. Facilitating behavior diffusion with resource constraints in a large population is qualitatively different from promoting cooperation in small groups. Previous work in social sciences has derived conditions for sustainable cooperative behavior in small homogeneous groups. However, how groups of individuals having resource constraint co-operate over extended periods of time is not well understood, and is the focus of my thesis. I develop models to analyze behavior diffusion over time through the lens of epidemic models with the condition that individuals have resource constraint. I introduce an epidemic model SVRS ( Susceptible-Volatile-Recovered-Susceptible) to accommodate multiple behavior adoption. I investigate the longitudinal effects of behavior diffusion by varying different properties of an individual such as resources,threshold and cost of behavior adoption. I also consider how behavior adoption of an individual varies with her knowledge of global adoption. I evaluate my models on several synthetic topologies like complete regular graph, preferential attachment and small-world and make some interesting observations. Periodic injection of early adopters can help in boosting the spread of behaviors and sustain it for a longer period of time. Also, behavior propagation for the classical epidemic model SIRS (Susceptible-Infected-Recovered-Susceptible) does not continue for an infinite period of time as per conventional wisdom. One interesting future direction is to investigate how behavior adoption is affected when number of individuals in a network changes. The affects on behavior adoption when availability of behavior changes with time can also be examined.
ContributorsDey, Anindita (Author) / Sundaram, Hari (Thesis advisor) / Turaga, Pavan (Committee member) / Davulcu, Hasan (Committee member) / Arizona State University (Publisher)
Created2013