Cloud Workload Allocation Approaches for Quality of Service Guarantee and Cybersecurity Risk Management

It has become a dominant trend in industry to adopt cloud computing --thanks to its unique advantages in flexibility, scalability, elasticity and cost efficiency -- for providing online cloud services over the Internet using large-scale data centers. In the meantime, the relentless increase in demand for affordable and high-quality cloud-based services, for individuals and businesses, has led to tremendously high power consumption and operating expense and thus has posed pressing challenges on cloud service providers in finding efficient resource allocation policies. Allowing several services or Virtual Machines (VMs) to commonly share the cloud\u27s infrastructure enables cloud providers to optimize resource usage, power consumption, and operating expense. However, servers sharing among users and VMs causes performance degradation and results in cybersecurity risks. Consequently, how to develop efficient and effective resource management policies to make the appropriate decisions to optimize the trade-offs among resource usage, service quality, and cybersecurity loss plays a vital role in the sustainable future of cloud computing. In this dissertation, we focus on cloud workload allocation problems for resource optimization subject to Quality of Service (QoS) guarantee and cybersecurity risk constraints. To facilitate our research, we first develop a cloud computing prototype that we utilize to empirically validate the performance of different proposed cloud resource management schemes under a close to practical, but also isolated and well-controlled, environment. We then focus our research on the resource management policies for real-time cloud services with QoS guarantee. Based on queuing model with reneging, we establish and formally prove a series of fundamental principles, between service timing characteristics and their resource demands, and based on which we develop several novel resource management algorithms that statically guarantee the QoS requirements for cloud users. We then study the problem of mitigating cybersecurity risk and loss in cloud data centers via cloud resource management. We employ game theory to model the VM-to-VM interdependent cybersecurity risks in cloud clusters. We then conduct a thorough analysis based on our game-theory-based model and develop several algorithms for cybersecurity risk management. Specifically, we start our cybersecurity research from a simple case with only two types of VMs and next extend it to a more general case with an arbitrary number of VM types. Our intensive numerical and experimental results show that our proposed algorithms can significantly outperform the existing methodologies for large-scale cloud data centers in terms of resource usage, cybersecurity loss, and computational effectiveness

Web-Based Courses In Higher Education: Creating Active Learning Environments

Problem. As more and more adults seek to continue their education, alternate methods of course delivery Will be required to meet their needs. Web-based courses allow students to learn at times and places that are convenient for them. There is concern, however, about whether or not such courses can create effective, active learning experiences, and whether or not knowledge can be socially constructed in online interactions. In order for higher education to provide exemplary online courses, it is important to identify necessary elements and instructional strategies to create virtual learning environments. The goals of this study were to determine instructional practices in exemplary higher education Web based courses and their perceived effectiveness and to determine implications of new delivery models for higher education. Method. This qualitative study examined the 1998 Paul Allen Virtual Education Foundation\u27s Outstanding Online Course Award winner and five of the six Honorable Mentions. Typical qualitative tools were used to gather data including a Web-based questionnaire, email correspondence, video recordings of conference presentations by four of the instructors, observations, interviews, course Web pages, plus articles and Web sites published by the instructors. Each course was a case study. Results. Effective practices and design features of these exemplary online courses demonstrate multiple ways to facilitate active learning in Web-based instruction. The rich environments of these six courses included a variety of interactions between the instructor and students and among the students themselves. They model how innovative pedagogy guides the use of technology and that virtual learning communities can be created in any discipline. Faculty who have administrative support will be more likely to design, develop, and deliver effective Web-based instruction. Conclusions. The study demonstrated ways online courses can be designed to meet the criteria of the American Psychological Association\u27s Learner-Centered Psychological Principles. A number of implications for higher education emerged

Supporting Evolution and Maintenance of android Apps

Mobile developers and testers face a number of emerging challenges. These include rapid platform evolution and API instability; issues in bug reporting and reproduction involving complex multitouch gestures; platform fragmentation; the impact of reviews and ratings on the success of their apps; management of crowd-sourced requirements; continuous pressure from the market for frequent releases; lack of effective and usable testing tools; and limited computational resources for handheld devices. Traditional and contemporary methods in software evolution and maintenance were not designed for these types of challenges; therefore, a set of studies and a new toolbox of techniques for mobile development are required to analyze current challenges and propose new solutions. This dissertation presents a set of empirical studies, as well as solutions for some of the key challenges when evolving and maintaining android apps. In particular, we analyzed key challenges experienced by practitioners and open issues in the mobile development community such as (i) android API instability, (ii) performance optimizations, (iii) automatic GUI testing, and (iv) energy consumption. When carrying out the studies, we relied on qualitative and quantitative analyses to understand the phenomena on a large scale by considering evidence extracted from software repositories and the opinions of open-source mobile developers. From the empirical studies, we identified that dynamic analysis is a relevant method for several evolution and maintenance tasks, in particular, because of the need of practitioners to execute/validate the apps on a diverse set of platforms (i.e., device and OS) and under pressure for continuous delivery. Therefore, we designed and implemented an extensible infrastructure that enables large-scale automatic execution of android apps to support different evolution and maintenance tasks (e.g., testing and energy optimization). In addition to the infrastructure we present a taxonomy of issues, single solutions to the issues, and guidelines to enable large execution of android apps. Finally, we devised novel approaches aimed at supporting testing and energy optimization of mobile apps (two key challenges in evolution and maintenance of android apps). First, we propose a novel hybrid approach for automatic GUI-based testing of apps that is able to generate (un)natural test sequences by mining real applications usages and learning statistical models that represent the GUI interactions. In addition, we propose a multi-objective approach for optimizing the energy consumption of GUIs in android apps that is able to generate visually appealing color compositions, while reducing the energy consumption and keeping a design concept close to the original

Scheduling Stochastic Multi-Stage Jobs to Elastic Hybrid Cloud Resources

[EN] We consider a special workflow scheduling problem in a hybrid-cloud-based workflow management system in which tasks are linearly dependent, compute-intensive, stochastic, deadline-constrained and executed on elastic and distributed cloud resources. This kind of problems closely resemble many real-time and workflow-based applications. Three optimization objectives are explored: number, usage time and utilization of rented VMs. An iterated heuristic framework is presented to schedule jobs event by event which mainly consists of job collecting and event scheduling. Two job collecting strategies are proposed and two timetabling methods are developed. The proposed methods are calibrated through detailed designs of experiments and sound statistical techniques. With the calibrated components and parameters, the proposed algorithm is compared to existing methods for related problems. Experimental results show that the proposal is robust and effective for the problems under study.This work is sponsored by the National Natural Science Foundations of China (Nos. 71401079, 61572127, 61472192), the National Key Research and Development Program of China (No. 2017YFB1400801) and the Collaborative Innovation Center of Wireless Communications Technology. Ruben Ruiz is partially supported by the Spanish Ministry of Economy and Competitiveness, under the project "SCHEYARD-Optimization of Scheduling Problems in Container Yards" (No. DPI2015-65895-R) financed by FEDER funds.Zhu, J.; Li, X.; Ruiz García, R.; Xu, X. (2018). Scheduling Stochastic Multi-Stage Jobs to Elastic Hybrid Cloud Resources. IEEE Transactions on Parallel and Distributed Systems. 29(6):1401-1415. https://doi.org/10.1109/TPDS.2018.2793254S1401141529

Parties and Peacebuilding: The Institutional Origin of Multiethnic Politics in India, Indonesia, and South Africa

Under what conditions do multiethnic political parties win elections in deeply divided societies? Using the cases of India, Indonesia, and South Africa, this dissertation first argues that the nature of liberation movements creates a soft path dependence that affects party formation. Ethnically inclusive liberation movements create conditions conducive to the formation of multiethnic political parties. Yet after this juncture point of party formation, multiethnic politics have dominated India and Indonesia while South Africa has experienced a slow degeneration into ethnic politics. To explain this divergence, this dissertation next examines the interaction of election rules and ethnic cleavage structure. India and Indonesia reinforce broadly crosscutting cleavages with multiple-district and candidate-centered elections. This forces parties to contest elections in ethnically diverse districts with local candidates, which encourages broad-based, inclusive political appeals. South Africa\u27s electoral system does the opposite. Its functionally single-district proportional representation system incentivizes identity politics by translating control of the ethnic majority into control of parliamentary power. This has resulted in the slow degeneration of Mandela\u27s multiethnic liberation movement into an ethnically exclusive political party

The Science of Antislavery: Scientists, Abolitionism, and the Myth of Slavery's Backwardness

"The Science of Antislavery" explores the critical though rarely studied role scientists played in the early antislavery movement. It argues that scientists not only helped legitimize abolitionism but also helped create the myth that slavery was a backward institution. During the Age of Revolution (1770-1830), when antislavery societies first took root, abolitionism attracted many scientific supporters. Though their refutations of scientific racism are perhaps better known, they also made many arguments that went beyond race. Chemists argued that new chemical techniques would fertilize the soil more effectively, which would in turn reduce the need for slave labor. Botanists touted the natural environments of new British colonies in Africa and Southeast Asia, contending that they would make ideal free labor alternatives to Caribbean plantations. Geologists argued that the western American frontier, with its unique mineral deposits, was best suited to free white agricultural settlements rather than slavery’s expansion. Even by the 1830s, when the movement was taken over by a more radical, less elite multiracial coalition, scientific arguments continued to influence antislavery arguments. From the 1830s until the Civil War, antislavery supporters on both sides of the Atlantic argued that slaveholders’ alleged refusal to adopt new machinery was evidence of their backwardness. Today, as a new generation of historians demonstrate how modern slavery in fact was, The Science of Antislavery shows how the idea that it was somehow never modern came into being

Santa Fe New Mexican, 07-24-1900

https://digitalrepository.unm.edu/sfnm_news/8813/thumbnail.jp

The Hilltop 2-26-2008

https://dh.howard.edu/hilltop_0010/1496/thumbnail.jp

Automated test of evolving software

A thesis submitted to the University of Luton, in partial fulfilment of the requirements for the degree of Doctor of PhilosophyComputers and the software they run are pervasive, yet released software is often unreliable, which has many consequences. Loss of time and earnings can be caused by application software (such as word processors) behaving incorrectly or crashing. Serious disruption can occur as in the l4th August 2003 blackouts in North East USA and Canadal, or serious injury or death can be caused as in the Therac-25 overdose incidents. One way to improve the quality of software is to test it thoroughly. However, software testing is time consuming, the resources, capabilities and skills needed to carry it out are often not available and the time required is often curtailed because of pressures to meet delivery deadlines3. Automation should allow more thorough testing in the time available and improve the quality of delivered software, but there are some problems with automation that this research addresses. Firstly, it is difficult to determine ifthe system under test (SUT) has passed or failed a test. This is known as the oracle problem4 and is often ignored in software testing research. Secondly, many software development organisations use an iterative and incremental process, known as evolutionary development, to write software. Following release, software continues evolving as customers demand new features and improvements to existing ones5. This evolution means that automated test suites must be maintained throughout the life ofthe software. A contribution of this research is a methodology that addresses automatic generation of the test cases, execution of the test cases and evaluation of the outcomes from running each test. "Predecessor" software is used to solve the oracle problem. This is software that already exists, such as a previous version of evolving software, or software from a different vendor that solves the same, or similar, problems. However, the resulting oracle is assumed not be perfect, so rules are defined in an interface, which are used by the evaluator in the test evaluation stage to handle the expected differences. The interface also specifies functional inputs and outputs to the SUT. An algorithm has been developed that creates a Markov Chain Transition Matrix (MCTM) model of the SUT from the interface. Tests are then generated automatically by making a random walk of the MCTM. This means that instead of maintaining a large suite of tests, or a large model of the SUT, only the interface needs to be maintained. 1) NERC Steering Group (2004). Technical Analysis ofthe August 14,2003, Blackout: What Happened, Why, and What Did We Learn? July 13th 2004. Available from: ftp:/ /www.nerc.com/pub/sys/all_ updl/docslblackoutINERC ]inatBlackout_Report _ 07_13_ 04.pdf 2) Leveson N. G., Turner C. S. (1993) An investigation of the Therac-25 accidents. IEEE Computer, Vo126, No 7, Pages 18-41. 3) LogicaCMG (2005) Testing Times for Board Rooms. Available from http://www.logicacmg.com/pdf/trackeditestingTimesBoardRooms.pdf 4) Bertolino, A. (2003) Software Testing Research and Practice, ASM 2003, Lecture Notes in Computer Science, Vol 2589, Pages 1-21. 5) Sommerville, 1. (2004) Software Engineering, 7th Edition. Addison Wesley. ISBN 0-321-21026-3