Universal Sorting: Finding a DAG using Priced Comparisons

We resolve two open problems in sorting with priced information, introduced by [Charikar, Fagin, Guruswami, Kleinberg, Raghavan, Sahai (CFGKRS), STOC 2000]. In this setting, different comparisons have different (potentially infinite) costs. The goal is to sort with small competitive ratio (algorithmic cost divided by cheapest proof). 1) When all costs are in $\{0,1,n,\infty\}$, we give an algorithm that has $\widetilde{O}(n^{3/4})$ competitive ratio. Our algorithm generalizes the algorithms for generalized sorting (all costs are either $1$ or $\infty$), a version initiated by [Huang, Kannan, Khanna, FOCS 2011] and addressed recently by [Kuszmaul, Narayanan, FOCS 2021]. 2) We answer the problem of bichromatic sorting posed by [CFGKRS]: The input is split into $A$ and $B$, and $A-A$ and $B-B$ comparisons are more expensive than an $A-B$ comparisons. We give a randomized algorithm with a O(polylog n) competitive ratio. These results are obtained by introducing the universal sorting problem, which generalizes the existing framework in two important ways. We remove the promise of a directed Hamiltonian path in the DAG of all comparisons. Instead, we require that an algorithm outputs the transitive reduction of the DAG. For bichromatic sorting, when $A-A$ and $B-B$ comparisons cost $\infty$, this generalizes the well-known nuts and bolts problem. We initiate an instance-based study of the universal sorting problem. Our definition of instance-optimality is inherently more algorithmic than that of the competitive ratio in that we compare the cost of a candidate algorithm to the cost of the optimal instance-aware algorithm. This unifies existing lower bounds, and opens up the possibility of an $O(1)$-instance optimal algorithm for the bichromatic version.Comment: 40 pages, 5 figure

Algorithm Engineering for fundamental Sorting and Graph Problems

Fundamental Algorithms build a basis knowledge for every computer science undergraduate or a professional programmer. It is a set of basic techniques one can find in any (good) coursebook on algorithms and data structures. In this thesis we try to close the gap between theoretically worst-case optimal classical algorithms and the real-world circumstances one face under the assumptions imposed by the data size, limited main memory or available parallelism

The organisational effects of installing a distributed processing system

Bibliography: 238-248.Since its introduction to business in 1952, computerised data processing has undergone a number of substantial changes, both in the hardware and the techniques that are used. The introduction of miniaturisation, and the resultant lowering of the costs of circuitry, has led to the widespread use of mini- and micro-computers. There has also been a large increase in the use of communication facilities. Initially, almost all organisations centralised their computer facilities at the Head Office and systems were run in the batch mode. The need to service the requirements of remote users was resolved by installing on-line facilities and providing unintelligent terminals to those users. Alternatively, stand-alone computers were installed at the remote locations. However, the requirements of businesses for centralised reporting and control led to the need to install processing units at the user sites and to connect those computers, via communications links, to a computer facility located at Head Office. In this way distributed data processing evolved. The provision of this type of processing mode has important implications to the organisation in such areas as costs, staffing, planning, control and systems design. This thesis, therefore, investigates the current (1980) trends in relation to distributed processing. It specifically examines the developments in hardware, software, and data communications. It assesses the criteria that should be considered by an organisation in selecting either the centralisation or distribution of its processing facilities. Through a field study both successful and unsuccessful distributed installations are examined. Conclusions are then drawn and recommendations made, to provide management with working guidelines when assessing the feasibility and practicality of distributed processing for its organisation. The findings of the study are appropriate for both general management and DP management with only centralised computing experience; and for individuals offering professional computer consultancy services to existing or potential users

Auditing & EDP

https://egrove.olemiss.edu/aicpa_guides/1018/thumbnail.jp

Implementacija umjetne inteligencije i njezin budući potencijal

Firstly, in the paper, I explored the history of artificial intelligence (AI) thought spanning from the early conceptual beginnings, then through early examples of primitive AI applications and all the way to recent feats in this field. Next, I analyzed types of AI, both present and future, encompassing two wide schools of thought; after which I detailed the pathways to achieving practical implementation of AI through machine learning (ML) and deep learning (DL) as well as a brief history of TensorFlow. The following chapters focused on analyzing case studies of AI application in the fields of banking and finance from the financial sector, and transportation in general, with the ensuing critical analyses. The final chapter is concerned with future implementation of AI

Implementacija umjetne inteligencije i njezin budući potencijal

Firstly, in the paper, I explored the history of artificial intelligence (AI) thought spanning from the early conceptual beginnings, then through early examples of primitive AI applications and all the way to recent feats in this field. Next, I analyzed types of AI, both present and future, encompassing two wide schools of thought; after which I detailed the pathways to achieving practical implementation of AI through machine learning (ML) and deep learning (DL) as well as a brief history of TensorFlow. The following chapters focused on analyzing case studies of AI application in the fields of banking and finance from the financial sector, and transportation in general, with the ensuing critical analyses. The final chapter is concerned with future implementation of AI

Economic-based Distributed Resource Management and Scheduling for Grid Computing

Computational Grids, emerging as an infrastructure for next generation computing, enable the sharing, selection, and aggregation of geographically distributed resources for solving large-scale problems in science, engineering, and commerce. As the resources in the Grid are heterogeneous and geographically distributed with varying availability and a variety of usage and cost policies for diverse users at different times and, priorities as well as goals that vary with time. The management of resources and application scheduling in such a large and distributed environment is a complex task. This thesis proposes a distributed computational economy as an effective metaphor for the management of resources and application scheduling. It proposes an architectural framework that supports resource trading and quality of services based scheduling. It enables the regulation of supply and demand for resources and provides an incentive for resource owners for participating in the Grid and motives the users to trade-off between the deadline, budget, and the required level of quality of service. The thesis demonstrates the capability of economic-based systems for peer-to-peer distributed computing by developing users' quality-of-service requirements driven scheduling strategies and algorithms. It demonstrates their effectiveness by performing scheduling experiments on the World-Wide Grid for solving parameter sweep applications

Engineering Algorithms for Route Planning in Multimodal Transportation Networks

Practical algorithms for route planning in transportation networks are a showpiece of successful Algorithm Engineering. This has produced many speedup techniques, varying in preprocessing time, space, query performance, simplicity, and ease of implementation. This thesis explores solutions to more realistic scenarios, taking into account, e.g., traffic, user preferences, public transit schedules, and the options offered by the many modalities of modern transportation networks

Energy-aware service provisioning in P2P-assisted cloud ecosystems

Cotutela Universitat Politècnica de Catalunya i Instituto Tecnico de LisboaEnergy has been emerged as a first-class computing resource in modern systems. The trend has primarily led to the strong focus on reducing the energy consumption of data centers, coupled with the growing awareness of the adverse impact on the environment due to data centers. This has led to a strong focus on energy management for server class systems. In this work, we intend to address the energy-aware service provisioning in P2P-assisted cloud ecosystems, leveraging economics-inspired mechanisms. Toward this goal, we addressed a number of challenges. To frame an energy aware service provisioning mechanism in the P2P-assisted cloud, first, we need to compare the energy consumption of each individual service in P2P-cloud and data centers. However, in the procedure of decreasing the energy consumption of cloud services, we may be trapped with the performance violation. Therefore, we need to formulate a performance aware energy analysis metric, conceptualized across the service provisioning stack. We leverage this metric to derive energy analysis framework. Then, we sketch a framework to analyze the energy effectiveness in P2P-cloud and data center platforms to choose the right service platform, according to the performance and energy characteristics. This framework maps energy from the hardware oblivious, top level to the particular hardware setting in the bottom layer of the stack. Afterwards, we introduce an economics-inspired mechanism to increase the energy effectiveness in the P2P-assisted cloud platform as well as moving toward a greener ICT for ICT for a greener ecosystem.La energía se ha convertido en un recurso de computación de primera clase en los sistemas modernos. La tendencia ha dado lugar principalmente a un fuerte enfoque hacia la reducción del consumo de energía de los centros de datos, así como una creciente conciencia sobre los efectos ambientales negativos, producidos por los centros de datos. Esto ha llevado a un fuerte enfoque en la gestión de energía de los sistemas de tipo servidor. En este trabajo, se pretende hacer frente a la provisión de servicios de bajo consumo energético en los ecosistemas de la nube asistida por P2P, haciendo uso de mecanismos basados en economía. Con este objetivo, hemos abordado una serie de desafíos. Para instrumentar un mecanismo de servicio de aprovisionamiento de energía consciente en la nube asistida por P2P, en primer lugar, tenemos que comparar el consumo energético de cada servicio en la nube P2P y en los centros de datos. Sin embargo, en el procedimiento de disminuir el consumo de energía de los servicios en la nube, podemos quedar atrapados en el incumplimiento del rendimiento. Por lo tanto, tenemos que formular una métrica, sobre el rendimiento energético, a través de la pila de servicio de aprovisionamiento. Nos aprovechamos de esta métrica para derivar un marco de análisis de energía. Luego, se esboza un marco para analizar la eficacia energética en la nube asistida por P2P y en la plataforma de centros de datos para elegir la plataforma de servicios adecuada, de acuerdo con las características de rendimiento y energía. Este marco mapea la energía desde el alto nivel independiente del hardware a la configuración de hardware particular en la capa inferior de la pila. Posteriormente, se introduce un mecanismo basado en economía para aumentar la eficacia energética en la plataforma en la nube asistida por P2P, así como avanzar hacia unas TIC más verdes, para las TIC en un ecosistema más verde.Postprint (published version

CPA\u27s handbook of fraud and commercial crime prevention

https://egrove.olemiss.edu/aicpa_guides/1819/thumbnail.jp