Evaluation of Storage Systems for Big Data Analytics

abstract: Recent trends in big data storage systems show a shift from disk centric models to memory centric models. The primary challenges faced by these systems are speed, scalability, and fault tolerance. It is interesting to investigate the performance of these two models with respect to some big data applications. This thesis studies the performance of Ceph (a disk centric model) and Alluxio (a memory centric model) and evaluates whether a hybrid model provides any performance benefits with respect to big data applications. To this end, an application TechTalk is created that uses Ceph to store data and Alluxio to perform data analytics. The functionalities of the application include offline lecture storage, live recording of classes, content analysis and reference generation. The knowledge base of videos is constructed by analyzing the offline data using machine learning techniques. This training dataset provides knowledge to construct the index of an online stream. The indexed metadata enables the students to search, view and access the relevant content. The performance of the application is benchmarked in different use cases to demonstrate the benefits of the hybrid model.Dissertation/ThesisMasters Thesis Computer Science 201

Single system image: A survey

Single system image is a computing paradigm where a number of distributed computing resources are aggregated and presented via an interface that maintains the illusion of interaction with a single system. This approach encompasses decades of research using a broad variety of techniques at varying levels of abstraction, from custom hardware and distributed hypervisors to specialized operating system kernels and user-level tools. Existing classification schemes for SSI technologies are reviewed, and an updated classification scheme is proposed. A survey of implementation techniques is provided along with relevant examples. Notable deployments are examined and insights gained from hands-on experience are summarized. Issues affecting the adoption of kernel-level SSI are identified and discussed in the context of technology adoption literature

The Categorization of Soil Moisture Content in the Near Infrared Spectrum

A new shortwave infrared remote sensing instrument potentially capable of measuring soil moisture from space was designed, tested and developed. The atmospheric spectral information and target detection range for infrared spectroscopy was analyzed. In order to measure soil moisture using grating spectroscopy, a trade study of the Argus 1000 spectrometer components was performed. This provided the basis for the chassis and component modifications required so that the desired spectral region could be viewed. The laboratory methodologies for soil baking, radiometric and wavelength calibration, and spectral collection was developed and performed. The soil baking methodology produced an error measurement of 2.4 %. Spectral measurements proved well, resulting in the confirmation of the wavelength region 1964 nm in being able to provide potential use for measuring soil moisture content from space

Distributed Operating Systems

Distributed operating systems have many aspects in common with centralized ones, but they also differ in certain ways. This paper is intended as an introduction to distributed operating systems, and especially to current university research about them. After a discussion of what constitutes a distributed operating system and how it is distinguished from a computer network, various key design issues are discussed. Then several examples of current research projects are examined in some detail, namely, the Cambridge Distributed Computing System, Amoeba, V, and Eden. © 1985, ACM. All rights reserved

Play in the theory and practice of art

This thesis focuses on the notion of play in the theory and practice of art in the 20th and 21st centuries. I approach play both as an internal element of the concept of art (following the philosophical tradition) and as the external model for the creative process (as applied by modern and postmodern artists). The main purpose is to produce an interpretation of play that would span various, often contradictory, features of this concept and would serve to reinterpret the notion of artistic representation, traditionally linked with the vocabulary and approaches coming from the domain of work (production, mastery, preconceived outcomes, fixity, and the nature/culture dichotomy). My thesis defends representation, however, supplemented with the notion of play. In my project of highlighting the role of play in the discourse of art and aesthetics, I draw on Jacques Derrida's reading of Kant and Plato. Derrida s analysis of the logic of supplementarity in Western thought and terms such as parergon, pharmakon and undecidable, help me to argue that the ambivalence of play and the movement in between the opposites allow us to understand play as a condition of artistic representation. I also use Mihaly Spariosu's distinction between the interpretations of play as rational or prerational to inscribe play into the argument between representation and non-representation in the theory and practice of art. In terms of practice, I link the emergence of the strategy of play with the rhetorics of primitivism in modern avant-gardes from Dada to Fluxus. I analyse play as a tool of transgression and an attractive supplement of the creative process a way to activate the public and change the traditional proper function (ergon) of art. I trace the assimilation of play in recent participatory (relational, dialogic) art intended to go beyond representation. I argue that play has become a commonly used tactic and an undercurrent of today's artistic and social network. In the final discussion I reinterpret the notions of work (ergon, essence) and play (parergon, supplement) in the light of the 20th century artistic revolution. Using vocabulary and approaches coming from the domain of play (and specifically Role-Playing Game) I attempt to overcome the prejudice against the notion of representation

Motivating Time as a First Class Entity

In hard real-time applications, programs must not only be functionally correct but must also meet timing constraints. Unfortunately, little work has been done to allow a high-level incorporation of timing constraints into distributed real-time programs. Instead the programmer is required to ensure system timing through a complicated synchronization process or through low-level programming, making it difficult to create and modify programs. In this report, we describe six features that must be integrated into a high level language and underlying support system in order to promote time to a first class position in distributed real-time programming systems: expressibility of time, real-time communication, enforcement of timing constraints, fault tolerance to violations of constraints, ensuring distributed system state consistency in the time domain, and static timing verification. For each feature we describe what is required, what related work had been performed, and why this work does not adequately provide sufficient capabilities for distributed real-time programming. We then briefly outline an integrated approach to provide these six features using a high-level distributed programming language and system tools such as compilers, operating systems, and timing analyzers to enforce and verify timing constraints

Planetary micro-rover operations on Mars using a Bayesian framework for inference and control

With the recent progress toward the application of commercially-available hardware to small-scale space missions, it is now becoming feasible for groups of small, efficient robots based on low-power embedded hardware to perform simple tasks on other planets in the place of large-scale, heavy and expensive robots. In this paper, we describe design and programming of the Beaver micro-rover developed for Northern Light, a Canadian initiative to send a small lander and rover to Mars to study the Martian surface and subsurface. For a small, hardware-limited rover to handle an uncertain and mostly unknown environment without constant management by human operators, we use a Bayesian network of discrete random variables as an abstraction of expert knowledge about the rover and its environment, and inference operations for control. A framework for efficient construction and inference into a Bayesian network using only the C language and fixed-point mathematics on embedded hardware has been developed for the Beaver to make intelligent decisions with minimal sensor data. We study the performance of the Beaver as it probabilistically maps a simple outdoor environment with sensor models that include uncertainty. Results indicate that the Beaver and other small and simple robotic platforms can make use of a Bayesian network to make intelligent decisions in uncertain planetary environments