The effects of potentiallydisruptive technology on business model - a case study of new technologies in ICT industry

This study examines how firms interpret new, potentially disruptive technologies in their own strategic context. The work presents a cross-case analysis of four potentially disruptive technologies or technical operating models: Bluetooth, WLAN, Grid computing and Mobile Peer-to-peer paradigm. The technologies were investigated from the perspective of three mobile operators, a device manufacturer and a software company in the ICT industry. The theoretical background for the study consists of the resource-based view of the firm with dynamic perspective, the theories on the nature of technology and innovations, and the concept of business model. The literature review builds up a propositional framework for estimating the amount of radical change in the companies' business model with two middle variables, the disruptiveness potential of a new technology, and the strategic importance of a new technology to a firm. The data was gathered in group discussion sessions in each company. The results of each case analysis were brought together to evaluate, how firms interpret the potential disruptiveness in terms of changes in product characteristics and added value, technology and market uncertainty, changes in product-market positions, possible competence disruption and changes in value network positions. The results indicate that the perceived disruptiveness in terms ofproduct characteristics does not necessarily translate into strategic importance. In addition, firms did not see the new technologies as a threat in terms of potential competence disruption.

Efficient Peer Selection in P2P JXTA-Based Platforms

Peer-reviewed

Asiakkuudenhallinta SaaS-periaatteella

Kandidaatintyö käsittelee Software as a Serviceä (SaaS, verkkosovelluspalvelu) käsitteenä ja ilmiönä. Työssä paneudutaan myös SaaS-mallin nykytilaan ja tulevaisuuden näkymiin. Tarkemmaksi tarkastelukohteeksi työssä on valittu SaaS-pohjainen asiakkuudenhallinta, ja SaaS-pohjaisten asiakkuudenhallintajärjestelmien nykytilan sekä kehityksen yksityiskohtainen analysointi. Työssä käsitellään aihetta alan julkaisujen ja kirjallisuuden avulla. Työssä vertaillaan merkittävimpien SaaS-pohjaisten asiakkuudenhallinta-järjestelmätoimittajien kehitystä Yhdysvalloissa ja Euroopassa sekä heidän ohjelmistojen nykytilaa, vahvuuksia, heikkouksia ja verkkosovelluspalveluiden tulevaisuuden näkymiä. Yhtenä osa-alueena käsitellään myös verkkosovelluspalvelun integrointia yrityksen muihin tietojärjestelmiin. Työssä todetaan, että SaaS on vielä uusi ja yleistyvä käsite ohjelmistoalalla sekä varteenotettava vaihtoehto hankkia yrityksen ohjelmistoja, kuten asiakkuudenhallintajärjestelmä. Tällä hetkellä SaaS-markkinoilla on vielä tilaa kilpailulle, joten tavasta toimittaa ohjelmistot yrityksille palveluna uskotaan yleistyvän tulevaisuudessa.

Web-sovellus Google App Engine alustalle

App Engine on lyhenne englanninkielisistä termeistä application, sovellus ja engine, moottori. Kyseessä on Google, Inc. -konsernin toteuttama kaupallinen palvelu, joka noudattaa pilvimallin tietojenkäsittelyn periaatteita ja mahdollistaa asiakkaan oman sovelluskehityksen. Järjestelmään on mahdollista ohjelmoida itse ideoitu palvelu Internet - verkon välityksellä käytettäväksi, joko yksityisesti tai julkisesti. Kyse on siis hajautetusta palvelinjärjestelmästä, jonka tarjoaa dynaamisesti kuormitukseen sopeutuvan sovellusalustan, jossa asiakas ei vuokraa virtuaalikoneita. Myös järjestelmän tarjoama tallennuskapasiteetti on saatavilla joustavasti. Itse kandidaatintyössä syvennytään yksityiskohtaisemmin sovelluksen toteuttamiseen palvelussa, rajoitteisiin ja soveltuvuuteen. Alussa käydään läpi pilvikäsite, joista monilla tietokoneiden käyttäjillä on epäselvä käsitys. Erilaisia kokonaisuuksia voidaan luoda erittäin monella tavalla, joista rajaamme käsittelyn kohteeksi toteuttamiskelpoiset yleiset ratkaisut.

Optimizing Customer Energy Invoice Calculation with Parallel Computation

Diplomityön tarkoituksena on optimoida asiakkaiden sähkölaskun laskeminen hajautetun laskennan avulla. Älykkäiden etäluettavien energiamittareiden tullessa jokaiseen kotitalouteen, energiayhtiöt velvoitetaan laskemaan asiakkaiden sähkölaskut tuntiperusteiseen mittaustietoon perustuen. Kasvava tiedonmäärä lisää myös tarvittavien laskutehtävien määrää. Työssä arvioidaan vaihtoehtoja hajautetun laskennan toteuttamiseksi ja luodaan tarkempi katsaus pilvilaskennan mahdollisuuksiin. Lisäksi ajettiin simulaatioita, joiden avulla arvioitiin rinnakkaislaskennan ja peräkkäislaskennan eroja. Sähkölaskujen oikeinlaskemisen tueksi kehitettiin mittauspuu-algoritmi.

ERP-järjestelmät pilvipalveluna

Työssä tutkitaan ERP-järjestelmää pilvipalveluna. Tutkimusmenetelmänä on käytetty kirjallisuuskatsausta. Työn tavoitteena on antaa lukijalle kuva siitä, mitä käsitteellä ERP-pilvipalveluna tarkoitetaan, miten se eroaa perinteisestä ERP–järjestelmästä sekä analysoida hyötyjä ja haittoja molemmissa ratkaisuissa. ERP-pilvipalvelulla tarkoitetaan ostettua palvelua, jota hallinnoi ja ylläpitää ulkopuolinen yritys. Järjestelmän käytöstä maksetaan kiinteä kuukausittainen maksu ja käyttäjämääriin perustuva maksu. Yrityksen käyttäessä ERP-pilvipalvelua sen ei tarvitse investoida laitteisiin. ERP-pilvipalvelu voi olla toteutettuna yritykselle varatussa yksityisessä pilvessä tai julkisessa pilvessä. Pilvipalveluna toteutettu ERP tekee kustannusten arvioinnin helpommaksi lyhyellä aikavälillä sen maksurakenteen takia. Pieni alkuinvestointi kannustaa ERP-pilvipalvelun käyttöön varsinkin pienissä yrityksissä. Isot yritykset kuitenkin suosivat perinteisiä ERP–ratkaisuja niiden paremman muokattavuuden takia. Suurin osa ERP–järjestelmistä on perinteisiä ratkaisuja. Yritykset pitävät pilvipalveluna toteutetun ERP:n suurimpana haasteena tietoturvariskejä. ERP-pilvipalvelu tekee yrityksen enemmän riippuvaiseksi palveluntarjoajasta.

BeETLe: Herramienta ETL geo-espacial libre

Las herramientas ETL (Extract, Transform, Load – extraer, transformar, cargar) permiten modelizar flujos de datos, facilitando la ejecución automática de procesos repetitivos. El intercambio de información entre dos modelos de datos heterogéneos es un claro ejemplo del tipo de tareas que pueden abordarse con software ETL. El proyecto Kettle es una herramienta ETL con licencia LGPL (Library General Public License) que utiliza técnicas de computación grid (ejecución paralela y distribuida) para poder procesar grandes cantidades de datos en un tiempo reducido. Kettle combina una potente ejecución en modo servidor con una intuitiva herramienta de escritorio para modelar los procesos y configurar los parámetros de ejecución. GeoKettle es una extensión de Kettle, que añade la posibilidad de tratar datos con componente geográfica, si bien está limitado a datos vectoriales y a ciertas operaciones espaciales muy concreta. El Centro Temático Europeo de Usos del Suelo e Información Espacial (ETC-LUSI) está impulsando un proyecto complementario, llamado BeETLe, que pretende ampliar drásticamente las capacidades de análisis y transformación espacial de GeoKettle. Para ello se ha elegido el proyecto Sextante, una librería de análisis espacial que incluye más de doscientos algoritmos ráster y vectoriales. La intención del proyecto BeETLe es integrar el conjunto de algoritmos de Sextante en GeoKettle, de forma que estén disponibles como transformaciones de GeoKettle. Las principales características de la herramienta BeETLe incluyen: automatización de procesos de análisis espacial o de transformaciones repetitivas de datos espaciales, ejecución paralela y distribuida (grid computing), capacidad para procesar grandes cantidades de datos sin limitaciones de memoria, y soporte de datos ráster y vectorial. Los usuarios actuales de Sextante descubrirán que BeETLe les propone una forma de trabajo sencilla e intuitiva, que añade a Sextante toda la potencia que ofrecen las herramientas ETL para procesar y transformar información en bases de datos

Running climate models on grids using G-Rex

Compute grids are used widely in many areas of environmental science, but there has been limited uptake of grid computing by the climate modelling community, partly because the characteristics of many climate models make them difficult to use with popular grid middleware systems. In particular, climate models usually produce large volumes of output data, and running them also involves complicated workflows implemented as shell scripts. A new grid middleware system that is well suited to climate modelling applications is presented in this paper. Grid Remote Execution (G-Rex) allows climate models to be deployed as Web services on remote computer systems and then launched and controlled as if they were running on the user's own computer. Output from the model is transferred back to the user while the run is in progress to prevent it from accumulating on the remote system and to allow the user to monitor the model. G-Rex has a REST architectural style, featuring a Java client program that can easily be incorporated into existing scientific workflow scripts. Some technical details of G-Rex are presented, with examples of its use by climate modellers.

Distributed mining of molecular fragments

In real world applications sequential algorithms of data mining and data exploration are often unsuitable for datasets with enormous size, high-dimensionality and complex data structure. Grid computing promises unprecedented opportunities for unlimited computing and storage resources. In this context there is the necessity to develop high performance distributed data mining algorithms. However, the computational complexity of the problem and the large amount of data to be explored often make the design of large scale applications particularly challenging. In this paper we present the first distributed formulation of a frequent subgraph mining algorithm for discriminative fragments of molecular compounds. Two distributed approaches have been developed and compared on the well known National Cancer Institute’s HIV-screening dataset. We present experimental results on a small-scale computing environment.

Parallel Monte Carlo approach for integration of the rendering equation

This paper is addressed to the numerical solving of the rendering equation in realistic image creation. The rendering equation is integral equation describing the light propagation in a scene accordingly to a given illumination model. The used illumination model determines the kernel of the equation under consideration. Nowadays, widely used are the Monte Carlo methods for solving the rendering equation in order to create photorealistic images. In this work we consider the Monte Carlo solving of the rendering equation in the context of the parallel sampling scheme for hemisphere. Our aim is to apply this sampling scheme to stratified Monte Carlo integration method for parallel solving of the rendering equation. The domain for integration of the rendering equation is a hemisphere. We divide the hemispherical domain into a number of equal sub-domains of orthogonal spherical triangles. This domain partitioning allows to solve the rendering equation in parallel. It is known that the Neumann series represent the solution of the integral equation as a infinity sum of integrals. We approximate this sum with a desired truncation error (systematic error) receiving the fixed number of iteration. Then the rendering equation is solved iteratively using Monte Carlo approach. At each iteration we solve multi-dimensional integrals using uniform hemisphere partitioning scheme. An estimate of the rate of convergence is obtained using the stratified Monte Carlo method. This domain partitioning allows easy parallel realization and leads to convergence improvement of the Monte Carlo method. The high performance and Grid computing of the corresponding Monte Carlo scheme are discussed.

A novel approach for distributed application scheduling based on prediction of communication events

The evolution of commodity computing lead to the possibility of efficient usage of interconnected machines to solve computationally-intensive tasks, which were previously solvable only by using expensive supercomputers. This, however, required new methods for process scheduling and distribution, considering the network latency, communication cost, heterogeneous environments and distributed computing constraints. An efficient distribution of processes over such environments requires an adequate scheduling strategy, as the cost of inefficient process allocation is unacceptably high. Therefore, a knowledge and prediction of application behavior is essential to perform effective scheduling. In this paper, we overview the evolution of scheduling approaches, focusing on distributed environments. We also evaluate the current approaches for process behavior extraction and prediction, aiming at selecting an adequate technique for online prediction of application execution. Based on this evaluation, we propose a novel model for application behavior prediction, considering chaotic properties of such behavior and the automatic detection of critical execution points. The proposed model is applied and evaluated for process scheduling in cluster and grid computing environments. The obtained results demonstrate that prediction of the process behavior is essential for efficient scheduling in large-scale and heterogeneous distributed environments, outperforming conventional scheduling policies by a factor of 10, and even more in some cases. Furthermore, the proposed approach proves to be efficient for online predictions due to its low computational cost and good precision. (C) 2009 Elsevier B.V. All rights reserved.

Performance results of running parallel applications on the InteGrade

The InteGrade middleware intends to exploit the idle time of computing resources in computer laboratories. In this work we investigate the performance of running parallel applications with communication among processors on the InteGrade grid. As costly communication on a grid can be prohibitive, we explore the so-called systolic or wavefront paradigm to design the parallel algorithms in which no global communication is used. To evaluate the InteGrade middleware we considered three parallel algorithms that solve the matrix chain product problem, the 0-1 Knapsack Problem, and the local sequence alignment problem, respectively. We show that these three applications running under the InteGrade middleware and MPI take slightly more time than the same applications running on a cluster with only LAM-MPI support. The results can be considered promising and the time difference between the two is not substantial. The overhead of the InteGrade middleware is acceptable, in view of the benefits obtained to facilitate the use of grid computing by the user. These benefits include job submission, checkpointing, security, job migration, etc. Copyright (C) 2009 John Wiley & Sons, Ltd.

Forensiska Undersökningar av Molntjänster

Användning av molntjänster har gjort forensiska undersökningar mer komplicerade. Däremot finns det goda förutsättningar om molnleverantörerna skapar tjänster för att få ut all information. Det skulle göra det enklare och mer tillförlitligt. Informationen som ska tas ut från molntjänsterna är svår att få ut på ett korrekt sätt. Undersökningen görs inte på en skrivskyddad kopia, utan i en miljö som riskerar att förändras. Det är då möjligt att ändringar görs under tiden datan hämtas ut, vilket inte alltid syns. Det går heller inte att jämföra skillnaderna genom att ta hashsummor på filerna som görs vid forensiska undersökningar av datorer. Därför är det viktigt att dokumentera hur informationen har tagits ut, helst genom att filma datorskärmen under tiden informationen tas ut. Informationen finns sparad på flera platser då molntjänsterna Office 365 och Google Apps används, både i molnet och på den eller de datorer som har använts för att ansluta till molntjänsten. Webbläsare sparar mycket information om vad som har gjorts. Därför är det viktigt att det går att ta reda på vilka datorer som har använts för att ansluta sig till molntjänsten, vilket idag inte möjligt. Om det är möjligt att undersöka de datorer som använts kan bevis som inte finns kvar i molnet hittas. Det bästa ur forensisk synvinkel skulle vara om leverantörerna av molntjänster erbjöd en tjänst som hämtar ut all data som rör en användare, inklusive alla relevanta loggar. Då skulle det ske på ett mycket säkrare sätt, då det inte skulle gå att ändra informationen under tiden den hämtas ut. 

Arquitetura para um ambiente de grade computacional direcionado às aplicações distribuídas, móveis e conscientes do contexto da computação pervasiva

Neste início de década, observa-se a transformação das áreas de Computação em Grade (Grid Computing) e Computação Móvel (Mobile Computing) de uma conotação de interesse emergente para outra caracterizada por uma demanda real e qualificada de produtos, serviços e pesquisas. Esta tese tem como pressuposto a identificação de que os problemas hoje abordados isoladamente nas pesquisas relativas às computações em grade, consciente do contexto e móvel, estão presentes quando da disponibilização de uma infra-estrutura de software para o cenário da Computação Pervasiva. Neste sentido, como aspecto central da sua contribuição, propõe uma solução integrada para suporte à Computação Pervasiva, implementada na forma de um middleware que visa criar e gerenciar um ambiente pervasivo, bem como promover a execução, sob este ambiente, das aplicações que expressam a semântica siga-me. Estas aplicações são, por natureza, distribuídas, móveis e adaptativas ao contexto em que seu processamento ocorre, estando disponíveis a partir de qualquer lugar, todo o tempo. O middleware proposto, denominado EXEHDA (Execution Environment for Highly Distributed Applications), é adaptativo ao contexto e baseado em serviços, sendo chamado de ISAMpe o ambiente por este disponibilizado. O EXEHDA faz parte dos esforços de pesquisa do Projeto ISAM (Infra-Estrutura de Suporte às Aplicações Móveis Distribuídas), em andamento na UFRGS. Para atender a elevada flutuação na disponibilidade dos recursos, inerente à Computação Pervasiva, o EXEHDA é estruturado em um núcleo mínimo e em serviços carregados sob demanda. Os principais serviços fornecidos estão organizados em subsistemas que gerenciam: (a) a execução distribuída; (b) a comunicação; (c) o reconhecimento do contexto; (d) a adaptação; (e) o acesso pervasivo aos recursos e serviços; (f) a descoberta e (g) o gerenciamento de recursos No EXEHDA, as condições de contexto são pró-ativamente monitoradas e o suporte à execução deve permitir que tanto a aplicação como ele próprio utilizem essas informações na gerência da adaptação de seus aspectos funcionais e não-funcionais. O mecanismo de adaptação proposto para o EXEHDA emprega uma estratégia colaborativa entre aplicação e ambiente de execução, através da qual é facultado ao programador individualizar políticas de adaptação para reger o comportamento de cada um dos componentes que constituem o software da aplicação. Aplicações tanto do domínio da Computação em Grade, quanto da Computação Pervasiva podem ser programadas e executadas sob gerenciamento do middleware proposto.