Strategic and operational services for workload management in the cloud

In hosting environments such as Infrastructure as a Service (IaaS) clouds, desirable application performance is typically guaranteed through the use of Service Level Agreements (SLAs), which specify minimal fractions of resource capacities that must be allocated by a service provider for unencumbered use by customers to ensure proper operation of their workloads. Most IaaS offerings are presented to customers as fixed-size and fixed-price SLAs, that do not match well the needs of specific applications. Furthermore, arbitrary colocation of applications with different SLAs may result in inefficient utilization of hosts' resources, resulting in economically undesirable customer behavior. In this thesis, we propose the design and architecture of a Colocation as a Service (CaaS) framework: a set of strategic and operational services that allow the efficient colocation of customer workloads. CaaS strategic services provide customers the means to specify their application workload using an SLA language that provides them the opportunity and incentive to take advantage of any tolerances they may have regarding the scheduling of their workloads. CaaS operational services provide the information necessary for, and carry out the reconfigurations mandated by strategic services. We recognize that it could be the case that there are multiple, yet functionally equivalent ways to express an SLA. Thus, towards that end, we present a service that allows the provably-safe transformation of SLAs from one form to another for the purpose of achieving more efficient colocation. Our CaaS framework could be incorporated into an IaaS offering by providers or it could be implemented as a value added proposition by IaaS resellers. To establish the practicality of such offerings, we present a prototype implementation of our proposed CaaS framework

Utilizing Runtime Information for Accurate Root Cause Identification in Performance Diagnosis

This dissertation highlights that existing performance diagnostic tools often become less effective due to their inherent inaccuracies in modern software. To overcome these inaccuracies and effectively identify the root causes of performance issues, it is necessary to incorporate supplementary runtime information into these tools. Within this context, the dissertation integrates specific runtime information into two typical performance diagnostic tools: profilers and causal tracing tools. The integration yields a substantial enhancement in the effectiveness of performance diagnosis. Among these tools, gprof stands out as a representative profiler for performance diagnosis. Nonetheless, its effectiveness diminishes as the time cost calculated based on CPU sampling fails to accurately and adequately pinpoint the root causes of performance issues in complex software. To tackle this challenge, the dissertation introduces an innovative methodology called value-assisted cost profiling (vProf). This approach incorporates variable values observed during runtime into the profiling process. By continuously sampling variable values from both normal and problematic executions, vProf refines function cost estimates, identifies anomalies in value distributions, and highlights potentially problematic code areas that could be the actual sources of performance is- sues. The effectiveness of vProf is validated through the diagnosis of 18 real-world performance is- sues in four widely-used applications. Remarkably, vProf outperforms other state-of-the-art tools, successfully diagnosing all issues, including three that had remained unresolved for over four years. Causal tracing tools reveal the root causes of performance issues in complex software by generating tracing graphs. However, these graphs often suffer from inherent inaccuracies, characterized by superfluous (over-connected) and missed (under-connected) edges. These inaccuracies arise from the diversity of programming paradigms. To mitigate the inaccuracies, the dissertation proposes an approach to derive strong and weak edges in tracing graphs based on the vertices’ semantics collected during runtime. By leveraging these edge types, a beam-search-based diagnostic algorithm is employed to identify the most probable causal paths. Causal paths from normal and buggy executions are differentiated to provide key insights into the root causes of performance issues. To validate this approach, a causal tracing tool named Argus is developed and tested across multiple versions of macOS. It is evaluated on 12 well-known spinning pinwheel issues in popular macOS applications. Notably, Argus successfully diagnoses the root causes of all identified issues, including 10 issues that had remained unresolved for several years. The results from both tools exemplify a substantial enhancement of performance diagnostic tools achieved by harnessing runtime information. The integration can effectively mitigate inherent inaccuracies, lend support to inaccuracy-tolerant diagnostic algorithms, and provide key insights to pinpoint the root causes

Strategic and operational services for workload management in the cloud (PhD thesis)

In hosting environments such as Infrastructure as a Service (IaaS) clouds, desirable application performance is typically guaranteed through the use of Service Level Agreements (SLAs), which specify minimal fractions of resource capacities that must be allocated by a service provider for unencumbered use by customers to ensure proper operation of their workloads. Most IaaS offerings are presented to customers as fixed-size and fixed-price SLAs, that do not match well the needs of specific applications. Furthermore, arbitrary colocation of applications with different SLAs may result in inefficient utilization of hosts’ resources, resulting in economically undesirable customer behavior. In this thesis, we propose the design and architecture of a Colocation as a Service (CaaS) framework: a set of strategic and operational services that allow the efficient colocation of customer workloads. CaaS strategic services provide customers the means to specify their application workload using an SLA language that provides them the opportunity and incentive to take advantage of any tolerances they may have regarding the scheduling of their workloads. CaaS operational services provide the information necessary for, and carry out the reconfigurations mandated by strategic services. We recognize that it could be the case that there are multiple, yet functionally equivalent ways to express an SLA. Thus, towards that end, we present a service that allows the provably-safe transformation of SLAs from one form to another for the purpose of achieving more efficient colocation. Our CaaS framework could be incorporated into an IaaS offering by providers or it could be implemented as a value added proposition by IaaS resellers. To establish the practicality of such offerings, we present a prototype implementation of our proposed CaaS framework. (Major Advisor: Azer Bestavros

Assessment of industrial energy use and carbon emissions in the textile industry

This study is to design and validate an assessment procedure for energy efficiency of manufacturing buildings. I demonstrated the assessment, based on the detailed energy audit, procedure on a case-study Scottish textile factory. This is to address the recognised need for more energy studies in the small and medium enterprise (SMEs). This heterogeneous and complicated sector inherits a range of energy efficiency barriers, and therefore requires more tailored energy efficiency studies. Over four years, half-hourly (H-H) empirical electricity and gas data, lower-resolution measured data, technology nameplate ratings and operations data have been analysed. The whole-system (site-wide) and key technology assessment assesses the baseline demand, demand variations in response to variables (such as production, weather, and departmental activity), and potential for tailored energy efficiency strategies. H-H energy data, against weekday activity and shift patterns, was used to produce average daily profiles, with trends linked to production and weather impacts, in turn allowing for identification of periods of energy wastage. Based on the 24-hour peak- and off-peak periods, specific time slots were derived to numerically estimate average demands. Consequently, various demand characteristics like baseload, disaggregation and percentage contribution at activity and departmental level were calculated. Individual key technologies were studied for behaviour- and technologyrelated energy, cost, and carbon (energy savings when transformed into carbon emissions) saving estimations. The whole assessment showed promising saving opportunities, in a way that can be potentially translated to any similar manufacturing site. As a result of applying this approach to energy analysis, indicative energy, cost, and carbon savings against a base year were estimated to be 33%, 28%, and 28% respectively, with the longest payback period of five-years. Validation for the savings associated with identified measures, through physically installing/applying the measures, was not possible due to funding limitations. Measured and nameplate rating based auditing methods were compared, where possible, to assess their discrete limitations and suitability. The promising energy and carbon reduction methodology and the lessons learnt are adaptable for both textile and the other similar industries. With this transferability, a key part of the work of this methodology in the thesis provides a framework and a series of steps that allows this approach to be taken to SME industry

COMBINING HARDWARE MANAGEMENT WITH MIXED-CRITICALITY PROVISIONING IN MULTICORE REAL-TIME SYSTEMS

Safety-critical applications in cyber-physical domains such as avionics and automotive systems require strict timing constraints because loss of life or severe financial repercussions may occur if they fail to produce correct outputs at the right moment. We call such systems “real-time systems.” When designing a real-time system, a multicore platform would be desirable to use because such platforms have advantages in size, weight, and power constraints, especially in embedded systems. However, the multicore revolution is having limited impact in safety-critical application domains. A key reason is the “one-out-of-m” problem: when validating real-time constraints on an m-core platform, excessive analysis pessimism can effectively negate the processing capacity of the additional m-1 cores so that only “one core’s worth” of capacity is available. The root of this problem is that shared hardware resources are not predictably managed. Two approaches have been investigated previously to address this problem: mixed-criticality analysis, which provision less-critical software components less pessimistically, and hardware-management techniques, which make the underlying platform itself more predictable. The goal of the research presented in this dissertation is to combine both approaches to reduce the capacity loss caused by contention for shared hardware resources in multicore platforms. Towards that goal, fundamentally new criticality-cognizant hardware-management tradeoffs must be explored. Such tradeoffs are investigated in the context of a new variant of a mixed-criticality framework, called MC2, that supports configurable criticality-based hardware management. This framework allows specific DRAM banks and areas of the last-level cache to be allocated to certain groups of tasks to provide criticality-aware isolation. MC2 is further extended to support the sharing of memory locations, which is required to realize the ability to support real-world workloads. We evaluate the impact of combining mixed-criticality provisioning and hardware-management techniques with both micro-benchmark experiments and schedulability studies. In our micro-benchmark experiments, we evaluate each hardware-management technique and consider tradeoffs that arise when applying them together. The effectiveness of the overall framework in resolving such tradeoffs is investigated via largescale overhead-aware schedulability studies. Our results demonstrate that mixed-criticality analysis and hardware-management techniques can be much more effective when applied together instead of alone.Doctor of Philosoph

Food Edu-Care in the Primary Curriculum: A collaborative case study in an inner city DEIS Gaelscoil

This applied case study explored the role of food education and its potential to nurture the lives of children who may experience disadvantage socially, culturally and economically. The research concedes at the outset that the role of ‘food’ in education is complex, that schools do not deal with curriculum matters alone but also with social justice policy issues, and that school-based ‘food poverty’ policy interventions to date are broadly motivated by nutritional concerns. The research was informed by a critical pedagogy perspective using a collaborative enquiry design focused on individual and collective agency at the school level. Multiple theoretical and analytical frameworks related to constructivist learning methodologies, educational psychology, and critical social theory framed the study. The research intervention in the inner-city DEIS Gaelscoil was at the invitation of the Parents’ Council and staff who collectively identified an urgent need for healthier eating practices and a shift to cross-curricular pedagogical practices to meet educational targets in literacy and numeracy. An Integrated Food Edu-Care curriculum module was collaboratively developed and delivered in Irish through weekly class sessions and field-trips. The integrated Food Edu-Care curriculum module consisted of; sixteen food and cooking lessons, a collaborative Hot Lunch Experience (Pedagogic Meal) and the creation of a ‘Foodbook’ as a class project. The curricular areas included in the integrated Food Edu-Care curriculum module included, Mathematics, Language, Social, Environmental and Scientific Education (SESE), Social Personal and Health Education (SPHE) and Visual Arts. The outputs from the research include an Integrated Food Edu-Care Pedagogical Guide for teachers and Pupils’ Activity Workbook, an ‘e-Foodbook’, educational videos, flashcards and posters in both English and Irish. The findings indicate that using a collaborative, experiential, caring, active and integrated Food Edu-Care curriculum module has the capacity to reach all learners and to build on classroom relationships, thereby facilitating social and emotional learning particularly in the area of self-efficacy and social skills. The research confirmed that such a curriculum module can incorporate seamless compensation for missed life chances and for on-going disadvantage. The thesis recommends a fifth domain of emotional and self-efficacy development needs among primary school children which is better facilitated by systemic policy change to school food provision and integrated curriculum with target-free pedagogies than by narrowly focused, targeted initiatives for free school lunches

Sustainability in design: now! Challenges and opportunities for design research, education and practice in the XXI century

Copyright @ 2010 Greenleaf PublicationsLeNS project funded by the Asia Link Programme, EuropeAid, European Commission

Internet Daemons: Digital Communications Possessed

We’re used to talking about how tech giants like Google, Facebook, and Amazon rule the internet, but what about daemons? Ubiquitous programs that have colonized the Net’s infrastructure—as well as the devices we use to access it—daemons are little known. Fenwick McKelvey weaves together history, theory, and policy to give a full account of where daemons come from and how they influence our lives—including their role in hot-button issues like network neutrality. Going back to Victorian times and the popular thought experiment Maxwell’s Demon, McKelvey charts how daemons evolved from concept to reality, eventually blossoming into the pandaemonium of code-based creatures that today orchestrates our internet. Digging into real-life examples like sluggish connection speeds, Comcast’s efforts to control peer-to-peer networking, and Pirate Bay’s attempts to elude daemonic control (and skirt copyright), McKelvey shows how daemons have been central to the internet, greatly influencing everyday users. Internet Daemons asks important questions about how much control is being handed over to these automated, autonomous programs, and the consequences for transparency and oversight. Table of Contents Abbreviations and Technical Terms Introduction 1. The Devil We Know: Maxwell’s Demon, Cyborg Sciences, and Flow Control 2. Possessing Infrastructure: Nonsynchronous Communication, IMPs, and Optimization 3. IMPs, OLIVERs, and Gateways: Internetworking before the Internet 4. Pandaemonium: The Internet as Daemons 5. Suffering from Buffering? Affects of Flow Control 6. The Disoptimized: The Ambiguous Tactics of the Pirate Bay 7. A Crescendo of Online Interactive Debugging? Gamers, Publics and Daemons Conclusion Acknowledgments Appendix: Internet Measurement and Mediators Notes Bibliography Index Reviews Beneath social media, beneath search, Internet Daemons reveals another layer of algorithms: deeper, burrowed into information networks. Fenwick McKelvey is the best kind of intellectual spelunker, taking us deep into the infrastructure and shining his light on these obscure but vital mechanisms. What he has delivered is a precise and provocative rethinking of how to conceive of power in and among networks. —Tarleton Gillespie, author of Custodians of the Internet Internet Daemons is an original and important contribution to the field of digital media studies. Fenwick McKelvey extensively maps and analyzes how daemons influence data exchanges across Internet infrastructures. This study insightfully demonstrates how daemons are transformative entities that enable particular ways of transferring information and connecting up communication, with significant social and political consequences. —Jennifer Gabrys, author of Program Eart

I am not content: consequences of managing a likable female image in "onlife"

This doctoral inquiry undertaken between 2015 and 2022 investigates the following premise: Women have to be “likeable” to be seen, thus becoming “content” for social media. The investigation employs an interdisciplinary approach, drawing from the fields of visual arts, social media studies, political theory and feminist studies. At the outset of the research, Jodi Dean’s essay Communicative Capitalism: Circulations and the Foreclosure of Politics (2005), along with Luciano Floridi’s concept of ‘onlife’ (2012), serve as key catalysts with subsequent writings emerging from a constellation of material feminism used to elaborate critical thinking on LIKES and likability as a matter. This research project employs the concept of “exhibition-as-chapter” (e-a-c), specifically designed for this inquiry. The aim is to drive material artistic experimentation to the fore, as a means to critically disrupt circulation. The e-a-c functions both as a system, and a method. In this approach I delve into the operative nature of the database, establishing a set of rules that physicalises the invisible instructions of the digital. The outcome is three e-a-c’s, that contribute to the creation of a fine-art practice that, whilst rooted in photography, combines with other mediums to draw attention to the developing situations of inequality and imbalance in the arts and wider public life for women artists. The original contribution to knowledge lies in identifying and developing a theory of LIKES and likability as having material consequences, especially for women in 'onlife'. I propose that the concept of likability enables researchers to understand and interpret how women are engaged with as online content. Moreover, LIKES emerge as a significant characteristic of surveillance capitalist production, influencing contemporary art worlds, and shaping artists’ livelihoods. The final submission of complementary writing makes an original contribution to scholarship in the fields of expanded photography, visual art, and education, with additional impacts on feminist theory and philosophies of the body

Selected On-Demand Medical Applications of 3D-Printing for Long-Duration Manned Space Missions

Recent technological advances in the area of Additive Manufacturing (i.e. 3D printing) allow for exploration of their use within long-duration manned space missions. Among the many potential application domains, medical and dental fabrication in support of crew health is of interest to NASA’s Advanced Exploration Systems directorate. A classification of medical events with their associated response timeline discern between those applications where current 3D printing technologies can provide adequate support. Products and devices that require on-demand fabrication (due to the high level of personal customization) but that can wait for a reasonable (e.g. few hours) fabrication time are the most promising areas. Among these non-emergency, on-demand applications, two were identified for further investigation: dental health and pharmaceutical drugs. A discussion on the challenges presented by a microgravity operational environment on these technologies is provided