New data structures, models, and algorithms for real-time resource management

Real-time resource management is the core and critical task in real-time systems. This dissertation explores new data structures, models, and algorithms for real-time resource management. At first, novel data structures, i.e., a class of Testing Interval Trees (TITs), are proposed to help build efficient scheduling modules in real-time systems. With a general data structure, i.e., the TIT* tree, the average costs of the schedulability tests in a wide variety of real-time systems can be reduced. With the Testing Interval Tree for Vacancy analysis (TIT-V), the complexities of the schedulability tests in a class of parallel/distributed real-time systems can be effectively reduced from 0(m²nlogn) to 0(mlogn+mlogm), where m is the number of processors and n is the number of tasks. Similarly, with the Testing Interval Tree for Release time and Laxity analysis (TIT-RL), the complexity of the online admission control in a uni-processor based real-time system can be reduced from 0(n²) to 0(nlogn), where n is the number of tasks. The TIT-RL tree can also be applied to a class of parallel/distributed real-time systems. Therefore, the TIT trees are effective approaches to efficient real-time scheduling modules. Secondly, a new utility accrual model, i.e., UAM+, is established for the resource management in real-time distributed systems. UAM+ is constructed based on the timeliness of computation and communication. Most importantly, the interplay between computation and communication is captured and characterized in the model. Under UAM+, resource managers are guided towards maximizing system-wide utility by exploring the interplay between computation and communication. This is in sharp contrast to traditional approaches that attempt to meet the timing constraints on computation and communication separately. To validate the effectiveness of UAM+, a resource allocation algorithm called IAUASA is developed. Simulation results reveal that IAUASA is far superior to two other resource allocation algorithms that are developed according to traditional utility accrual model and traditional idea. Furthermore, an online algorithm called IDRSA is also developed under UAM+, and a Dynamic Deadline Adjustment (DDA) technique is incorporated into IDRSA algorithm to explore the interplay between computation and communication. The simulation results show that the performance of IDRSA is very promising, especially when the interplay between computation and communication is tight. Therefore, the new utility accrual model provides a more effective approach to the resource allocation in distributed real-time systems. Thirdly, a general task model, which adapts the concept of calculus curve from the network calculus domain, is established for those embedded real-time systems with random event/task arrivals. Under this model, a prediction technique based on history window and calculus curves is established, and it provides the foundation for dynamic voltage-frequency scaling in those embedded real-time systems. Based on this prediction technique, novel energy-efficient algorithms that can dynamically adjust the operating voltage-frequency according to the predicted workload are developed. These algorithms aim to reduce energy consumption while meeting hard deadlines. They can accommodate and well adapt to the variation between the predicted and the actual arrivals of tasks as well as the variation between the predicted and the actual execution times of tasks. Simulation results validate the effectiveness of these algorithms in energy saving

Utility-Aware Scheduling of Stochastic Real-Time Systems

Time utility functions offer a reasonably general way to describe the complex timing constraints of real-time and cyber-physical systems. However, utility-aware scheduling policy design is an open research problem. In particular, scheduling policies that optimize expected utility accrual are needed for real-time and cyber-physical domains. This dissertation addresses the problem of utility-aware scheduling for systems with periodic real-time task sets and stochastic non-preemptive execution intervals. We model these systems as Markov Decision Processes. This model provides an evaluation framework by which different scheduling policies can be compared. By solving the Markov Decision Process we can derive value-optimal scheduling policies for moderate sized problems. However, the time and memory complexity of computing and storing value-optimal scheduling policies also necessitates the exploration of other more scalable solutions. We consider heuristic schedulers, including a generalization we have developed for the existing Utility Accrual Packet Scheduling Algorithm. We compare several heuristics under soft and hard real-time conditions, different load conditions, and different classes of time utility functions. Based on these evaluations we present guidelines for which heuristics are best suited to particular scheduling criteria. Finally, we address the memory complexity of value-optimal scheduling, and examine trade-offs between optimality and memory complexity. We show that it is possible to derive good low complexity scheduling decision functions based on a synthesis of heuristics and reduced-memory approximations of the value-optimal scheduling policy

Multi-objective reinforcement learning for responsive grids

The original publication is available at www.springerlink.comInternational audienceGrids organize resource sharing, a fundamental requirement of large scientific collaborations. Seamless integration of grids into everyday use requires responsiveness, which can be provided by elastic Clouds, in the Infrastructure as a Service (IaaS) paradigm. This paper proposes a model-free resource provisioning strategy supporting both requirements. Provisioning is modeled as a continuous action-state space, multi-objective reinforcement learning (RL) problem, under realistic hypotheses; simple utility functions capture the high level goals of users, administrators, and shareholders. The model-free approach falls under the general program of autonomic computing, where the incremental learning of the value function associated with the RL model provides the so-called feedback loop. The RL model includes an approximation of the value function through an Echo State Network. Experimental validation on a real data-set from the EGEE grid shows that introducing a moderate level of elasticity is critical to ensure a high level of user satisfaction

Management Accounting Change: A hybrid institutional and managerial perspective : The case of the Greek Higher Education Institutions

The responses of certain organisations, such as Higher Educational Institutions (HEIs), to the demands of their institutional environment are central to this study. In today’s economic climate and under the existing political and social conditions, it is inevitable for organisations to consider and/or undergo some form of change and to reform the existing management practices so that to become more efficient and accountable regarding the acquisition and use of the public sector resources thus, adopting the New Public Management principles. In this vein, accounting was expected to play a major role in providing new forms of financial information. This information would then be utilized towards the improvement of the public sector’s performance and accountability in order to achieve efficiency, effectiveness and economy and the presence of the accrual basis accounting system has constituted an important change component. The current study focuses on providing an answer to the question of how HEIs in Greece responded to governmental pressures for accounting reform during the decade of 1998-2008; specifically, it focuses on the extent to which HEIs implement the accrual accounting system and the influence of the isomorphic and intra organizational dynamics on its implementation. The aim of this enquiry is to assist in providing a deep understanding of the external and internal dynamics that influence the adoption and implementation of the Management Accounting (MA) systems, resulting thus, to new daily accounting practices within certain organizations. The current study is not limited in researching the various ways in which the Greek HEIs cope with the management of the change pressures but also aims towards studying the effect of the internal and external institutional environment within which organizations operate. This institutional environment exerts influence on the behavior of the organizations with regard to change. The theoretical framework employed various institutional theory strands and perspectives on change management theories regarding change management processes that consider the ways in which MA practices can undergo change. Consequently, a hybrid institutional approach of MA change derived from the integration of various strands of institutional theory, such as Old Institutional Economics (OIE) and New Institutional Theory (NIS) and perspectives on change management theories. The adoption of a subjectivism interpretive philosophy has been suggested as the most appropriate and a case study research strategy has been adopted for the scope of this study including an in part survey strategy. The Greek higher education system is considered to be the case study under investigation. The complexity of the phenomena under investigation implied the need for a sequential mixed method approach in order to best understand and explain the phenomenon under investigation. The current research aims to contribute to the growing body of literature of MA and change management that combine OIE and NIS perspectives with change management theories and to provide major implications for the successful MA change in certain organizations, such as higher education sector institutions. With respect to this specific research area, twofold objectives have been considered to be achieved via this study concerning theoretical and practical aspects equally. The theoretical objective of this thesis was to develop a valuable theoretical framework by using complementary various theoretical strands and perspectives. The second objective was the empirical investigation of the accrual accounting system implementation in certain organizations such as the Greek HEIs. The findings of the empirical study have been expected to provide organizational actors with a further understanding of the MA change and the influence of isomorphic and intra organizational dynamics in the accounting change process. This thesis has provided evidence of how the intra organizational dynamics have been activated towards the implementation of the new accounting system under the government pressure and the isomorphic forces enacted for. Furthermore, it resulted in that the implementation of the accrual accounting system and the attempted MA change were dependent on the activation and interaction of the isomorphic forces as well as of the intra organizational dynamics which guided the whole process of change from the starting point to its resulting thus to the new daily accounting practices and routines up rising as taken for granted. In particular, based strictly on an investigation of the existing literature and the analysis of the derived findings by the survey structured questionnaire and the face-to-face interviews, it is assumed that isomorphic forces have been insufficiently activated by the external environment in order to push the Greek HEIs forward towards the adoption of the accounting reform demanded by the legislator (Presidential Decree 205/1998). It is also supported that the intra organizational dynamics, activated within each individual HEI that implemented the accrual accounting system, have not resulted sufficiently to the development of new accounting routines, considering them as the positive outcome of the successful accounting change process

Corporation tax: a survey

The corporation tax is arguably the most well-studied tax found throughout the world. Countless numbers of professionals study the impact of corporate tax law on the affairs of the corporation. Yet, despite considerable resources that are expended on compliance, the tax in many countries raises only a small portion of revenue for governments. For example, in the G7 countries, taxes paid by corporations account for less than 8 per cent of tax revenues raised by governments, except for Japan where the corporation tax yields about 15 per cent of government revenue. This low revenue yield and high compliance cost have resulted in some experts and politicians questioning the usefulness of the corporate income tax.

Multi-dimensional optimization for cloud based multi-tier applications

Emerging trends toward cloud computing and virtualization have been opening new avenues to meet enormous demands of space, resource utilization, and energy efficiency in modern data centers. By being allowed to host many multi-tier applications in consolidated environments, cloud infrastructure providers enable resources to be shared among these applications at a very fine granularity. Meanwhile, resource virtualization has recently gained considerable attention in the design of computer systems and become a key ingredient for cloud computing. It provides significant improvement of aggregated power efficiency and high resource utilization by enabling resource consolidation. It also allows infrastructure providers to manage their resources in an agile way under highly dynamic conditions. However, these trends also raise significant challenges to researchers and practitioners to successfully achieve agile resource management in consolidated environments. First, they must deal with very different responsiveness of different applications, while handling dynamic changes in resource demands as applications' workloads change over time. Second, when provisioning resources, they must consider management costs such as power consumption and adaptation overheads (i.e., overheads incurred by dynamically reconfiguring resources). Dynamic provisioning of virtual resources entails the inherent performance-power tradeoff. Moreover, indiscriminate adaptations can result in significant overheads on power consumption and end-to-end performance. Hence, to achieve agile resource management, it is important to thoroughly investigate various performance characteristics of deployed applications, precisely integrate costs caused by adaptations, and then balance benefits and costs. Fundamentally, the research question is how to dynamically provision available resources for all deployed applications to maximize overall utility under time-varying workloads, while considering such management costs. Given the scope of the problem space, this dissertation aims to develop an optimization system that not only meets performance requirements of deployed applications, but also addresses tradeoffs between performance, power consumption, and adaptation overheads. To this end, this dissertation makes two distinct contributions. First, I show that adaptations applied to cloud infrastructures can cause significant overheads on not only end-to-end response time, but also server power consumption. Moreover, I show that such costs can vary in intensity and time scale against workload, adaptation types, and performance characteristics of hosted applications. Second, I address multi-dimensional optimization between server power consumption, performance benefit, and transient costs incurred by various adaptations. Additionally, I incorporate the overhead of the optimization procedure itself into the problem formulation. Typically, system optimization approaches entail intensive computations and potentially have a long delay to deal with a huge search space in cloud computing infrastructures. Therefore, this type of cost cannot be ignored when adaptation plans are designed. In this multi-dimensional optimization work, scalable optimization algorithm and hierarchical adaptation architecture are developed to handle many applications, hosting servers, and various adaptations to support various time-scale adaptation decisions.Ph.D.Committee Chair: Pu, Calton; Committee Member: Liu, Ling; Committee Member: Liu, Xue; Committee Member: Schlichting, Richard; Committee Member: Schwan, Karsten; Committee Member: Yalamanchili, Sudhaka

Adaptive Mid-term and Short-term Scheduling of Mixed-criticality Systems

A mixed-criticality real-time system is a real-time system having multiple tasks classified according to their criticality. Research on mixed-criticality systems started to provide an effective and cost efficient a priori verification process for safety critical systems. The higher the criticality of a task within a system and the more the system should guarantee the required level of service for it. However, such model poses new challenges with respect to scheduling and fault tolerance within real-time systems. Currently, mixed-criticality scheduling protocols severely degrade lower criticality tasks in case of resource shortage to provide the required level of service for the most critical ones. The actual research challenge in this field is to devise robust scheduling protocols to minimise the impact on less critical tasks. This dissertation introduces two approaches, one short-term and the other medium-term, to appropriately allocate computing resources to tasks within mixed-criticality systems both on uniprocessor and multiprocessor systems. The short-term strategy consists of a protocol named Lazy Bailout Protocol (LBP) to schedule mixed-criticality task sets on single core architectures. Scheduling decisions are made about tasks that are active in the ready queue and that have to be dispatched to the CPU. LBP minimises the service degradation for lower criticality tasks by providing to them a background execution during the system idle time. After, I refined LBP with variants that aim to further increase the service level provided for lower criticality tasks. However, this is achieved at an increased cost of either system offline analysis or complexity at runtime. The second approach, named Adaptive Tolerance-based Mixed-criticality Protocol (ATMP), decides at runtime which task has to be allocated to the active cores according to the available resources. ATMP permits to optimise the overall system utility by tuning the system workload in case of shortage of computing capacity at runtime. Unlike the majority of current mixed-criticality approaches, ATMP allows to smoothly degrade also higher criticality tasks to keep allocated lower criticality ones

The role of Management Accounting Practices in shaping efficiency in a Colombian Utility Conglomerate

The thesis contributes to generating an understanding of the role of management accounting practices in shaping efficiency in a Colombian Utility Conglomerate (CUC) . Data for the thesis was derived from multiple sources including interviews, non-participative observations and document analysis, reports and archives about CUC, which has helped to understand the studied phenomenon. The thesis, which builds on structuration theory (Giddens 1984, Giddens 1993), delineates the interplay between social structures and agency at CUC, the way this interplay led to the reproduction of the very notion of efficiency. In addition, the thesis extends the work of Englund and Gerdin (2008) by illustrating how management accounting practices can be analytical constructs integrating not only situated recurrent (inter-)actions but also the structural principles that underline those practices. Thus, the thesis analyses the influence of the managerial autonomy, the long-term financial approach and the technostructure in shaping efficiency at CUC (Aristizábal et al. 1988, López 2005, Varela 2011). Additionally, the thesis analyses the broader influence of the School of Mines and multilateral development banks to enable an understanding of why management accounting practices shape efficiency at CUC. The approach of structuration theory applied enables move beyond how efficiency is understood within New Public Management reforms, to consider the way how CUC manages to adapt the structural adjustments as demanded by multilateral development banks. The empirical insights show that in CUC efficiency is constructed more as a corporate value exercised through management accounting practices rather than being an exclusive indicator calculated through input/output relationships. The analysis unfolds how CUC creatively undertook the changes and adjustments to enable a public company to work with the profitability criteria prevailing in private enterprises. In this way, the thesis demonstrates how social structures related to utility companies as profitable businesses and public utilities as economic commodities are reproduced through management accounting practices in a public company within a Latin-American emerging economy

Linking Research and Policy: Assessing a Framework for Organic Agricultural Support in Ireland

This paper links social science research and agricultural policy through an analysis of support for organic agriculture and food. Globally, sales of organic food have experienced 20% annual increases for the past two decades, and represent the fastest growing segment of the grocery market. Although consumer interest has increased, farmers are not keeping up with demand. This is partly due to a lack of political support provided to farmers in their transition from conventional to organic production. Support policies vary by country and in some nations, such as the US, vary by state/province. There have been few attempts to document the types of support currently in place. This research draws on an existing Framework tool to investigate regionally specific and relevant policy support available to organic farmers in Ireland. This exploratory study develops a case study of Ireland within the framework of ten key categories of organic agricultural support: leadership, policy, research, technical support, financial support, marketing and promotion, education and information, consumer issues, inter-agency activities, and future developments. Data from the Irish Department of Agriculture, Fisheries and Food, the Irish Agriculture and Food Development Authority (Teagasc), and other governmental and semi-governmental agencies provide the basis for an assessment of support in each category. Assessments are based on the number of activities, availability of information to farmers, and attention from governmental personnel for each of the ten categories. This policy framework is a valuable tool for farmers, researchers, state agencies, and citizen groups seeking to document existing types of organic agricultural support and discover policy areas which deserve more attention