A Workflow for Fast Evaluation of Mapping Heuristics Targeting Cloud Infrastructures

Resource allocation is today an integral part of cloud infrastructures management to efficiently exploit resources. Cloud infrastructures centers generally use custom built heuristics to define the resource allocations. It is an immediate requirement for the management tools of these centers to have a fast yet reasonably accurate simulation and evaluation platform to define the resource allocation for cloud applications. This work proposes a framework allowing users to easily specify mappings for cloud applications described in the AMALTHEA format used in the context of the DreamCloud European project and to assess the quality for these mappings. The two quality metrics provided by the framework are execution time and energy consumption.Comment: 2nd International Workshop on Dynamic Resource Allocation and Management in Embedded, High Performance and Cloud Computing DREAMCloud 2016 (arXiv:cs/1601.04675

SimGrid: a Sustained Effort for the Versatile Simulation of Large Scale Distributed Systems

In this paper we present Simgrid, a toolkit for the versatile simulation of large scale distributed systems, whose development effort has been sustained for the last fifteen years. Over this time period SimGrid has evolved from a one-laboratory project in the U.S. into a scientific instrument developed by an international collaboration. The keys to making this evolution possible have been securing of funding, improving the quality of the software, and increasing the user base. In this paper we describe how we have been able to make advances on all three fronts, on which we plan to intensify our efforts over the upcoming years.Comment: 4 pages, submission to WSSSPE'1

Exploring the implementation of the Last Planner® System through IGLC community: twenty one years of experience

There is robust evidence that the level of implementation of the Last Planner® System (LPS) is increasing geographically and geometrically in construction. The I nternational Group for Lean Construction (IGLC) community has reported this growth at IGLC conferences over this period. However, no study has explored how the LPS and its implementation has developed or improved. This study explored developments in the LPS from the review of IGLC conference papers. Qualitative research design utilising content analysis was adopted for this study comprising 57 IGLC reports on LPS implementation across 16 countries. The study reveals components of LPS implemented, with measuring of PPC, Weekly Work Planning meeting and recording reasons for non-completion the most reported. The study developed a timeline for the LPS development and revealed that some of the papers reviewed have no defined methodology. The study concludes that the LPS has developed in terms of its level of implementation, theory development, and as a vehicle to improve construction management practice across the major continents of the world, with elements that had little presence at the onset now prominent. The study recommends that more attention should be given to the relationship between practical applications and research methods to aid the establishment of sound theory to improve practice

A Visual Analytics Approach to Debugging Cooperative, Autonomous Multi-Robot Systems' Worldviews

Autonomous multi-robot systems, where a team of robots shares information to perform tasks that are beyond an individual robot's abilities, hold great promise for a number of applications, such as planetary exploration missions. Each robot in a multi-robot system that uses the shared-world coordination paradigm autonomously schedules which robot should perform a given task, and when, using its worldview--the robot's internal representation of its belief about both its own state, and other robots' states. A key problem for operators is that robots' worldviews can fall out of sync (often due to weak communication links), leading to desynchronization of the robots' scheduling decisions and inconsistent emergent behavior (e.g., tasks not performed, or performed by multiple robots). Operators face the time-consuming and difficult task of making sense of the robots' scheduling decisions, detecting de-synchronizations, and pinpointing the cause by comparing every robot's worldview. To address these challenges, we introduce MOSAIC Viewer, a visual analytics system that helps operators (i) make sense of the robots' schedules and (ii) detect and conduct a root cause analysis of the robots' desynchronized worldviews. Over a year-long partnership with roboticists at the NASA Jet Propulsion Laboratory, we conduct a formative study to identify the necessary system design requirements and a qualitative evaluation with 12 roboticists. We find that MOSAIC Viewer is faster- and easier-to-use than the users' current approaches, and it allows them to stitch low-level details to formulate a high-level understanding of the robots' schedules and detect and pinpoint the cause of the desynchronized worldviews.Comment: To appear in IEEE Conference on Visual Analytics Science and Technology (VAST) 202

Scalable visual analytics over voluminous spatiotemporal data

2018 Fall.Includes bibliographical references.Visualization is a critical part of modern data analytics. This is especially true of interactive and exploratory visual analytics, which encourages speedy discovery of trends, patterns, and connections in data by allowing analysts to rapidly change what data is displayed and how it is displayed. Unfortunately, the explosion of data production in recent years has led to problems of scale as storage, processing, querying, and visualization have struggled to keep pace with data volumes. Visualization of spatiotemporal data pose unique challenges, thanks in part to high-dimensionality in the input feature space, interactions between features, and the production of voluminous, high-resolution outputs. In this dissertation, we address challenges associated with supporting interactive, exploratory visualization of voluminous spatiotemporal datasets and underlying phenomena. This requires the visualization of millions of entities and changes to these entities as the spatiotemporal phenomena unfolds. The rendering and propagation of spatiotemporal phenomena must be both accurate and timely. Key contributions of this dissertation include: 1) the temporal and spatial coupling of spatially localized models to enable the visualization of phenomena at far greater geospatial scales; 2) the ability to directly compare and contrast diverging spatiotemporal outcomes that arise from multiple exploratory "what-if" queries; and 3) the computational framework required to support an interactive user experience in a heavily resource-constrained environment. We additionally provide support for collaborative and competitive exploration with multiple synchronized clients

STARS GUI : a web application for the analysis of astronomical schedules

The main objective of astronomical observations is to observe as many planets as possible in a given period of time. To do this, most telescopes have a scheduler, which is a software that plans the different tasks/planets that the telescope must observe in a given period of time taking into account constraints, that a scientist can give for a certain observation such as the moon phase or the luminosity of the sun. The Institute of Space Sciences (ICE) is involved in a wide variety of scheduling projects for space and ground-based telescopes. The problem is that the result that these planners give is difficult to understand, therefore, there is a need to create a visualization tool that allows to easily understand the result of the schedulers. This article introduces the development process for creating a web application that can represent the output of astronomical schedulers in an easy-to-understand way through statistical information and plots of targets included in the plan.L'objectiu principal de les observacions astronòmiques és observar la major quantitat de planetes en un període de temps fixat. Per a això, la majoria dels telescopis tenen un planificador, que és un programari que planifica les diferents tasques/planetes que ha d'observar el telescopi en un període de temps fixat tenint en compte restriccions, que un científic pugui donar per a una determinada observació com, per exemple, la fase lunar o la lluminositat del sol. L'Institut de Ciències de l'Espai (ICE) està involucrat en una gran varietat de projectes de planificadors per a telescopis terrestres i en satèl·lits. El problema és que el resultat que treuen aquests planificadors és difícil d'entendre, per això sorgeix la necessitat de crear una eina de visualització que permeti entendre fàcilment el resultat dels planificadors. Aquest article presenta el procés de desenvolupament per a crear una aplicació web que permeti representar el resultat dels planificadors astronòmics d'una forma fàcil d'entendre a través d'informació estadística i gràfics dels planetes en la planificació.El objetivo principal de las observaciones astronómicas es observar la mayor cantidad de planetas en un periodo de tiempo fijado. Para ello, la mayoría de los telescopios tienen un planificador, que es un software que planifica las diferentes tareas/planetas que debe de observar el telescopio en un periodo de tiempo fijado teniendo en cuenta restricciones, que un científico pueda dar para una determinada observación como, por ejemplo, la fase lunar o la luminosidad del sol. El Instituto de Ciencias del Espacio (ICE) está involucrado en una gran variedad de proyectos de planificadores para telescopios terrestres y en satélites. El problema es que el resultado que sacan estos planificadores es difícil de entender, por ello surge la necesidad de crear una herramienta de visualización que permita entender fácilmente el resultado de los planificadores. Este artículo presenta el proceso de desarrollo para crear una aplicación web que permita representar el resultado de los planificadores astronómicos de una forma fácil de entender a través de información estadística y gráficos de los planetas en la planificación

Business Process Redesign in the Perioperative Process: A Case Perspective for Digital Transformation

This case study investigates business process redesign within the perioperative process as a method to achieve digital transformation. Specific perioperative sub-processes are targeted for re-design and digitalization, which yield improvement. Based on a 184-month longitudinal study of a large 1,157 registered-bed academic medical center, the observed effects are viewed through a lens of information technology (IT) impact on core capabilities and core strategy to yield a digital transformation framework that supports patient-centric improvement across perioperative sub-processes. This research identifies existing limitations, potential capabilities, and subsequent contextual understanding to minimize perioperative process complexity, target opportunity for improvement, and ultimately yield improved capabilities. Dynamic technological activities of analysis, evaluation, and synthesis applied to specific perioperative patient-centric data collected within integrated hospital information systems yield the organizational resource for process management and control. Conclusions include theoretical and practical implications as well as study limitations

Dependency Mapping Software for Jira, Project Management Tool

Efficiently managing a software development project is extremely important in industry and is often overlooked by the software developers on a project. Pieces of development work are identified by developers and are then handed off to project managers, who are left to organize this information. Project managers must organize this to set expectations for the client, and ensure the project stays on track and on budget. The main block in this process are dependency chains between tasks. Dependency chains can cause a project to take much longer than anticipated or result in the under utilization of developers on a project. While project managers do have access to project management tools, few have capabilities to effectively visualize dependencies. The goal of this research was to interact with a project management tool\u27s API, pull down dependency information for a project, and build out possible timelines for a set of tasks. We visualize this problem with a directed graph, where each node is a task and edges in the graph indicate dependencies. The relationships between this problem and more well-known problems in graph theory are used to inform the development of the algorithms. Two algorithms are explored to handle the problem and are then run under different conditions. Analysis of the results provide insight to what structures of dependency chains can be handled by the algorithms. The resulting software could be used to save companies both time and money when planning software development projects