Using MapReduce Streaming for Distributed Life Simulation on the Cloud

Distributed software simulations are indispensable in the study of large-scale life models but often require the use of technically complex lower-level distributed computing frameworks, such as MPI. We propose to overcome the complexity challenge by applying the emerging MapReduce (MR) model to distributed life simulations and by running such simulations on the cloud. Technically, we design optimized MR streaming algorithms for discrete and continuous versions of Conway’s life according to a general MR streaming pattern. We chose life because it is simple enough as a testbed for MR’s applicability to a-life simulations and general enough to make our results applicable to various lattice-based a-life models. We implement and empirically evaluate our algorithms’ performance on Amazon’s Elastic MR cloud. Our experiments demonstrate that a single MR optimization technique called strip partitioning can reduce the execution time of continuous life simulations by 64%. To the best of our knowledge, we are the first to propose and evaluate MR streaming algorithms for lattice-based simulations. Our algorithms can serve as prototypes in the development of novel MR simulation algorithms for large-scale lattice-based a-life models.https://digitalcommons.chapman.edu/scs_books/1014/thumbnail.jp

Front-Line Physicians' Satisfaction with Information Systems in Hospitals

Day-to-day operations management in hospital units is difficult due to continuously varying situations, several actors involved and a vast number of information systems in use. The aim of this study was to describe front-line physicians' satisfaction with existing information systems needed to support the day-to-day operations management in hospitals. A cross-sectional survey was used and data chosen with stratified random sampling were collected in nine hospitals. Data were analyzed with descriptive and inferential statistical methods. The response rate was 65 % (n = 111). The physicians reported that information systems support their decision making to some extent, but they do not improve access to information nor are they tailored for physicians. The respondents also reported that they need to use several information systems to support decision making and that they would prefer one information system to access important information. Improved information access would better support physicians' decision making and has the potential to improve the quality of decisions and speed up the decision making process.Peer reviewe

Information technology and military performance

Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Political Science, 2011.Cataloged from PDF version of thesis.Includes bibliographical references (p. 519-544).Militaries have long been eager to adopt the latest technology (IT) in a quest to improve knowledge of and control over the battlefield. At the same time, uncertainty and confusion have remained prominent in actual experience of war. IT usage sometimes improves knowledge, but it sometimes contributes to tactical blunders and misplaced hubris. As militaries invest intensively in IT, they also tend to develop larger headquarters staffs, depend more heavily on planning and intelligence, and employ a larger percentage of personnel in knowledge work rather than physical combat. Both optimists and pessimists about the so-called "revolution in military affairs" have tended to overlook the ways in which IT is profoundly and ambiguously embedded in everyday organizational life. Technocrats embrace IT to "lift the fog of war," but IT often becomes a source of breakdowns, misperception, and politicization. To describe the conditions under which IT usage improves or degrades organizational performance, this dissertation develops the notion of information friction, an aggregate measure of the intensity of organizational struggle to coordinate IT with the operational environment. It articulates hypotheses about how the structure of the external battlefield, internal bureaucratic politics, and patterns of human-computer interaction can either exacerbate or relieve friction, which thus degrades or improves performance. Technological determinism alone cannot account for the increasing complexity and variable performances of information phenomena. Information friction theory is empirically grounded in a participant-observation study of U.S. special operations in Iraq from 2007 to 2008. To test the external validity of insights gained through fieldwork in Iraq, an historical study of the 1940 Battle of Britain examines IT usage in a totally different structural, organizational, and technological context.(cont.) These paired cases show that high information friction, and thus degraded performance, can arise with sophisticated IT, while lower friction and impressive performance can occur with far less sophisticated networks. The social context, not just the quality of technology, makes all the difference. Many shorter examples from recent military history are included to illustrate concepts. This project should be of broad interest to students of organizational knowledge, IT, and military effectiveness.by Jon Randall Lindsay.Ph.D

Social work with airports passengers

Social work at the airport is in to offer to passengers social services. The main methodological position is that people are under stress, which characterized by a particular set of characteristics in appearance and behavior. In such circumstances passenger attracts in his actions some attention. Only person whom he trusts can help him with the documents or psychologically

Task Allocation in Foraging Robot Swarms:The Role of Information Sharing

Autonomous task allocation is a desirable feature of robot swarms that collect and deliver items in scenarios where congestion, caused by accumulated items or robots, can temporarily interfere with swarm behaviour. In such settings, self-regulation of workforce can prevent unnecessary energy consumption. We explore two types of self-regulation: non-social, where robots become idle upon experiencing congestion, and social, where robots broadcast information about congestion to their team mates in order to socially inhibit foraging. We show that while both types of self-regulation can lead to improved energy efficiency and increase the amount of resource collected, the speed with which information about congestion flows through a swarm affects the scalability of these algorithms