291 research outputs found

    Semantic discovery and reuse of business process patterns

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    Patterns currently play an important role in modern information systems (IS) development and their use has mainly been restricted to the design and implementation phases of the development lifecycle. Given the increasing significance of business modelling in IS development, patterns have the potential of providing a viable solution for promoting reusability of recurrent generalized models in the very early stages of development. As a statement of research-in-progress this paper focuses on business process patterns and proposes an initial methodological framework for the discovery and reuse of business process patterns within the IS development lifecycle. The framework borrows ideas from the domain engineering literature and proposes the use of semantics to drive both the discovery of patterns as well as their reuse

    Concluding dialogue

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    This is a chapter in a book with the overall description: This is a critical time in design. Concepts and practices of design are changing in response to historical developments in the modes of industrial design production and consumption. Indeed, the imperative of more sustainable development requires profound reconsideration of design today. Theoretical foundations and professional definitions are at stake, with consequences for institutions such as museums and universities as well as for future practitioners. This is ‘critical’ on many levels, from the urgent need to address societal and environmental issues to the reflexivity required to think and do design differently

    Introductions

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    This is the introduction to the book with the overall description: This is a critical time in design. Concepts and practices of design are changing in response to historical developments in the modes of industrial design production and consumption. Indeed, the imperative of more sustainable development requires profound reconsideration of design today. Theoretical foundations and professional definitions are at stake, with consequences for institutions such as museums and universities as well as for future practitioners. This is ‘critical’ on many levels, from the urgent need to address societal and environmental issues to the reflexivity required to think and do design differently

    On Security and Privacy for Networked Information Society : Observations and Solutions for Security Engineering and Trust Building in Advanced Societal Processes

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    Our society has developed into a networked information society, in which all aspects of human life are interconnected via the Internet — the backbone through which a significant part of communications traffic is routed. This makes the Internet arguably the most important piece of critical infrastructure in the world. Securing Internet communications for everyone using it is extremely important, as the continuing growth of the networked information society relies upon fast, reliable and secure communications. A prominent threat to the security and privacy of Internet users is mass surveillance of Internet communications. The methods and tools used to implement mass surveillance capabilities on the Internet pose a danger to the security of all communications, not just the intended targets. When we continue to further build the networked information upon the unreliable foundation of the Internet we encounter increasingly complex problems,which are the main focus of this dissertation. As the reliance on communication technology grows in a society, so does the importance of information security. At this stage, information security issues become separated from the purely technological domain and begin to affect everyone in society. The approach taken in this thesis is therefore both technical and socio-technical. The research presented in this PhD thesis builds security in to the networked information society and provides parameters for further development of a safe and secure networked information society. This is achieved by proposing improvements on a multitude of layers. In the technical domain we present an efficient design flow for secure embedded devices that use cryptographic primitives in a resource-constrained environment, examine and analyze threats to biometric passport and electronic voting systems, observe techniques used to conduct mass Internet surveillance, and analyze the security of Finnish web user passwords. In the socio-technical domain we examine surveillance and how it affects the citizens of a networked information society, study methods for delivering efficient security education, examine what is essential security knowledge for citizens, advocate mastery over surveillance data by the targeted citizens in the networked information society, and examine the concept of forced trust that permeates all topics examined in this work.Yhteiskunta, jossa elĂ€mme, on muovautunut teknologian kehityksen myötĂ€ todelliseksi tietoyhteiskunnaksi. Monet verkottuneen tietoyhteiskunnan osa-alueet ovat kokeneet muutoksen tĂ€mĂ€n kehityksen seurauksena. TĂ€mĂ€n muutoksen keskiössĂ€ on Internet: maailmanlaajuinen tietoverkko, joka mahdollistaa verkottuneiden laitteiden keskenĂ€isen viestinnĂ€n ennennĂ€kemĂ€ttömĂ€ssĂ€ mittakaavassa. Internet on muovautunut ehkĂ€ keskeisimmĂ€ksi osaksi globaalia viestintĂ€infrastruktuuria, ja siksi myös globaalin viestinnĂ€n turvaaminen korostuu tulevaisuudessa yhĂ€ enemmĂ€n. Verkottuneen tietoyhteiskunnan kasvu ja kehitys edellyttĂ€vĂ€t vakaan, turvallisen ja nopean viestintĂ€jĂ€rjestelmĂ€n olemassaoloa. Laajamittainen tietoverkkojen joukkovalvonta muodostaa merkittĂ€vĂ€n uhan tĂ€mĂ€n jĂ€rjestelmĂ€n vakaudelle ja turvallisuudelle. Verkkovalvonnan toteuttamiseen kĂ€ytetyt menetelmĂ€t ja työkalut eivĂ€t vain anna mahdollisuutta tarkastella valvonnan kohteena olevaa viestiliikennettĂ€, vaan myös vaarantavat kaiken Internet-liikenteen ja siitĂ€ riippuvaisen toiminnan turvallisuuden. Kun verkottunutta tietoyhteiskuntaa rakennetaan tĂ€mĂ€n kaltaisia valuvikoja ja haavoittuvuuksia sisĂ€ltĂ€vĂ€n jĂ€rjestelmĂ€n varaan, keskeinen uhkatekijĂ€ on, ettĂ€ yhteiskunnan ydintoiminnot ovat alttiina ulkopuoliselle vaikuttamiselle. NĂ€iden uhkatekijöiden ja niiden taustalla vaikuttavien mekanismien tarkastelu on tĂ€mĂ€n vĂ€itöskirjatyön keskiössĂ€. Koska työssĂ€ on teknisen sisĂ€llön lisĂ€ksi vahva yhteiskunnallinen elementti, tarkastellaan tiukan teknisen tarkastelun sijaan aihepiirĂ€ laajemmin myös yhteiskunnallisesta nĂ€kökulmasta. TĂ€ssĂ€ vĂ€itöskirjassa pyritÀÀn rakentamaan kokonaiskuvaa verkottuneen tietoyhteiskunnan turvallisuuteen, toimintaan ja vakauteen vaikuttavista tekijöistĂ€, sekĂ€ tuomaan esiin uusia ratkaisuja ja avauksia eri nĂ€kökulmista. Työn tavoitteena on osaltaan mahdollistaa entistĂ€ turvallisemman verkottuneen tietoyhteiskunnan rakentaminen tulevaisuudessa. TeknisestĂ€ nĂ€kökulmasta työssĂ€ esitetÀÀn suunnitteluvuo kryptografisia primitiivejĂ€ tehokkaasti hyödyntĂ€ville rajallisen laskentatehon sulautetuviiille jĂ€rjestelmille, analysoidaan biometrisiin passeihin, kansainvĂ€liseen passijĂ€rjestelmÀÀn, sekĂ€ sĂ€hköiseen ÀÀnestykseen kohdistuvia uhkia, tarkastellaan joukkovalvontaan kĂ€ytettyjen tekniikoiden toimintaperiaatteita ja niiden aiheuttamia uhkia, sekĂ€ tutkitaan suomalaisten Internet-kĂ€yttĂ€jien salasanatottumuksia verkkosovelluksissa. Teknis-yhteiskunnallisesta nĂ€kökulmasta työssĂ€ tarkastellaan valvonnan teoriaa ja perehdytÀÀn siihen, miten valvonta vaikuttaa verkottuneen tietoyhteiskunnan kansalaisiin. LisĂ€ksi kehitetÀÀn menetelmiĂ€ parempaan tietoturvaopetukseen kaikilla koulutusasteilla, mÀÀritellÀÀn keskeiset tietoturvatietouden kĂ€sitteet, tarkastellaan mahdollisuutta soveltaa tiedon herruuden periaatetta verkottuneen tietoyhteiskunnan kansalaisistaan kerÀÀmĂ€n tiedon hallintaan ja kĂ€yttöön, sekĂ€ tutkitaan luottamuksen merkitystĂ€ yhteiskunnan ydintoimintojen turvallisuudelle ja toiminnalle, keskittyen erityisesti pakotetun luottamuksen vaikutuksiin

    Power Modeling and Resource Optimization in Virtualized Environments

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    The provisioning of on-demand cloud services has revolutionized the IT industry. This emerging paradigm has drastically increased the growth of data centers (DCs) worldwide. Consequently, this rising number of DCs is contributing to a large amount of world total power consumption. This has directed the attention of researchers and service providers to investigate a power-aware solution for the deployment and management of these systems and networks. However, these solutions could be bene\ufb01cial only if derived from a precisely estimated power consumption at run-time. Accuracy in power estimation is a challenge in virtualized environments due to the lack of certainty of actual resources consumed by virtualized entities and of their impact on applications\u2019 performance. The heterogeneous cloud, composed of multi-tenancy architecture, has also raised several management challenges for both service providers and their clients. Task scheduling and resource allocation in such a system are considered as an NP-hard problem. The inappropriate allocation of resources causes the under-utilization of servers, hence reducing throughput and energy e\ufb03ciency. In this context, the cloud framework needs an e\ufb00ective management solution to maximize the use of available resources and capacity, and also to reduce the impact of their carbon footprint on the environment with reduced power consumption. This thesis addresses the issues of power measurement and resource utilization in virtualized environments as two primary objectives. At \ufb01rst, a survey on prior work of server power modeling and methods in virtualization architectures is carried out. This helps investigate the key challenges that elude the precision of power estimation when dealing with virtualized entities. A di\ufb00erent systematic approach is then presented to improve the prediction accuracy in these networks, considering the resource abstraction at di\ufb00erent architectural levels. Resource usage monitoring at the host and guest helps in identifying the di\ufb00erence in performance between the two. Using virtual Performance Monitoring Counters (vPMCs) at a guest level provides detailed information that helps in improving the prediction accuracy and can be further used for resource optimization, consolidation and load balancing. Later, the research also targets the critical issue of optimal resource utilization in cloud computing. This study seeks a generic, robust but simple approach to deal with resource allocation in cloud computing and networking. The inappropriate scheduling in the cloud causes under- and over- utilization of resources which in turn increases the power consumption and also degrades the system performance. This work \ufb01rst addresses some of the major challenges related to task scheduling in heterogeneous systems. After a critical analysis of existing approaches, this thesis presents a rather simple scheduling scheme based on the combination of heuristic solutions. Improved resource utilization with reduced processing time can be achieved using the proposed energy-e\ufb03cient scheduling algorithm

    Ernst Denert Award for Software Engineering 2020

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    This open access book provides an overview of the dissertations of the eleven nominees for the Ernst Denert Award for Software Engineering in 2020. The prize, kindly sponsored by the Gerlind & Ernst Denert Stiftung, is awarded for excellent work within the discipline of Software Engineering, which includes methods, tools and procedures for better and efficient development of high quality software. An essential requirement for the nominated work is its applicability and usability in industrial practice. The book contains eleven papers that describe the works by Jonathan BrachthĂ€user (EPFL Lausanne) entitled What You See Is What You Get: Practical Effect Handlers in Capability-Passing Style, Mojdeh Golagha’s (Fortiss, Munich) thesis How to Effectively Reduce Failure Analysis Time?, Nikolay Harutyunyan’s (FAU Erlangen-NĂŒrnberg) work on Open Source Software Governance, Dominic Henze’s (TU Munich) research about Dynamically Scalable Fog Architectures, Anne Hess’s (Fraunhofer IESE, Kaiserslautern) work on Crossing Disciplinary Borders to Improve Requirements Communication, Istvan Koren’s (RWTH Aachen U) thesis DevOpsUse: A Community-Oriented Methodology for Societal Software Engineering, Yannic Noller’s (NU Singapore) work on Hybrid Differential Software Testing, Dominic Steinhofel’s (TU Darmstadt) thesis entitled Ever Change a Running System: Structured Software Reengineering Using Automatically Proven-Correct Transformation Rules, Peter WĂ€gemann’s (FAU Erlangen-NĂŒrnberg) work Static Worst-Case Analyses and Their Validation Techniques for Safety-Critical Systems, Michael von Wenckstern’s (RWTH Aachen U) research on Improving the Model-Based Systems Engineering Process, and Franz Zieris’s (FU Berlin) thesis on Understanding How Pair Programming Actually Works in Industry: Mechanisms, Patterns, and Dynamics – which actually won the award. The chapters describe key findings of the respective works, show their relevance and applicability to practice and industrial software engineering projects, and provide additional information and findings that have only been discovered afterwards, e.g. when applying the results in industry. This way, the book is not only interesting to other researchers, but also to industrial software professionals who would like to learn about the application of state-of-the-art methods in their daily work

    WiFi-Based Human Activity Recognition Using Attention-Based BiLSTM

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    Recently, significant efforts have been made to explore human activity recognition (HAR) techniques that use information gathered by existing indoor wireless infrastructures through WiFi signals without demanding the monitored subject to carry a dedicated device. The key intuition is that different activities introduce different multi-paths in WiFi signals and generate different patterns in the time series of channel state information (CSI). In this paper, we propose and evaluate a full pipeline for a CSI-based human activity recognition framework for 12 activities in three different spatial environments using two deep learning models: ABiLSTM and CNN-ABiLSTM. Evaluation experiments have demonstrated that the proposed models outperform state-of-the-art models. Also, the experiments show that the proposed models can be applied to other environments with different configurations, albeit with some caveats. The proposed ABiLSTM model achieves an overall accuracy of 94.03%, 91.96%, and 92.59% across the 3 target environments. While the proposed CNN-ABiLSTM model reaches an accuracy of 98.54%, 94.25% and 95.09% across those same environments
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