Swedish Institute of Computer Science Publications Database
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Domain based storage protection with secure access control for the cloud
No full textCloud computing has evolved from a promising concept to one of the fastest growing segments of the IT industry. However, many businesses and individuals continue to view cloud computing as a technology that risks exposing their data to unauthorized users. We introduce a data confidentiality and integrity protection mechanism for Infrastructure-as-a-Service (IaaS) clouds, which relies on trusted computing principles to provide transparent storage isolation between IaaS clients. We also address the absence of reliable data sharing mechanisms, by providing an XML-based language framework which enables clients of IaaS clouds to securely share data and clearly define access rights granted to peers. The proposed improvements have been prototyped as a code extension for a popular cloud platform
Applications of Optimization Methods in Industrial Maintenance Scheduling and Software Testing
No full textAs the world is getting more and more competitive, efficiency has become a bigger concern than ever for many businesses. Certain efficiency concerns can naturally be expressed as optimization problems, which is a well studied field in the academia. However, optimization algorithms are not as widely employed in industrial practice as they could. There are various reasons for the lack of widespread adoption. For example, it can be difficult or even impossible for non-experts to formulate a detailed mathematical model of the problem. On the other hand, a scientist usually does not have a deep enough understanding of critical business details, and may fail to capture enough details of the real- world phenomenon of concern. While a model at an arbitrary abstraction level is often good enough to demonstrate the optimization approach, ignoring relevant aspects can easily render the solution impractical for the industry. This is an important problem, because applicability concerns hinder the possible gains that can be achieved by using the academic knowledge in industrial practice.
In this thesis, we study the challenges of industrial optimization problems in the form of four case studies at four different companies, in the domains of maintenance schedule optimization and search-based software testing. Working with multiple case studies in different domains allows us to better understand the possible gains and practical challenges in applying optimization methods in an industrial setting. Often there is a need to trade precision for applicability, which is typically very context dependent. Therefore, we compare our results against base values, e.g., results from simpler algorithms or the state of the practice in the given context, where applicable.
Even though we cannot claim that optimization methods are applicable in all situations, our work serves as an empirical evidence for the usability of optimization methods for improvements in different industrial contexts. We hope that our work can encourage the adoption of optimization techniques by more industrial practitioners
The Pursuit of 'Appiness: Exploring Android Market Download Behaviour in a Nationwide Cellular Network
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Personalised continuous software engineering
No full textThis work describes how human factors can influence continuous software engineering. The reasoning begins from the Agile Manifesto promoting individuals and interactions over processes and tools. The organisational need to continuously develop, release and learn from software development in rapid cycles requires empowered and self-organised agile teams. However, these teams are formed without necessarily considering the members’ individual characteristics towards effective teamwork, from the personality and cognitive perspective. In this realm, this paper proposes a two level approach: first, form teams based on their collective personality traits and second, provide personalised tools and methods based on their individual differences in cognitive processing. The approach is motivated by a study conducted in a business environment focusing on task execution, satisfaction and effectiveness of team members in relation to their personalities and cognitive characteristics. Our preliminary results show that human factors provide a promising basis for increasing the capability of continuous software engineering
Defining a method for identifying architectural candidates as part of engineering a system architecture
No full textEngineering system architectures for complex systems involves the tasks of analyzing architectural drivers, identifying architectural concerns, identifying valid architecture candidates, and evaluation of alternatives. One problem to overcome when architecting a system is the identification of valid of architectural candidates. We have developed a step-wise method for performing system architecture analysis and tested it on a sub-system in a project developing a drive system for heavy automotive applications. In this paper we present the complete method of nine steps for engineering an architecture and we elaborate in detail on the procedure to identify architectural candidates based on previously identified architectural drivers. We present a diagram depicting the proposed information model, its concepts and their relationships. In addition, the expectations on such a method as expressed by practitioners have been elicited, and we elaborate on the validity by examining how well the method indicate fulfillment. Our conclusion is that the proposed method does not fail to deliver on any of the needs and this gives an indication of usefulness. When identifying architectural candidates it is important to use proper criteria in the process. Our conclusion is that the practitioners should focus on candidates that affect the system at hand (within system boundaries), and on the candidates that address the architecturally significant system use. This is reflected in our method where we prescribe evaluation of the design candidates by validating that they solve only the right problem and by ensuring that they address the system at hand
How Many Auditory Icons, in a Control Room Environment, Can You Learn?
No full textPrevious research has shown that auditory icons can be
effective warnings. The aim of this study was to determine the number of auditory icons that can be learned, in a control room context. The participants in the study consisted of 14 control room operators and 15 people who were not control room operators. The participants were divided into three groups. Prior to the testing the three groups practiced on 10, 20 and 30 different sounds. Each group was tested using the sounds that they had practiced. The results support the potential for learning and recalling a large number of auditory icons, as many as 30. The results also show that sounds with similar characteristics are easily confused
Who Were Where When? On the Use of Social Collective Intelligence in Computational Epidemiology
No full textA triangular (case, theoretical, and literature) study approach is used to investigate if and how social collective intelligence is useful to computational epidemiology. The hypothesis is that the former can be employed for assisting in converting data into useful information through intelligent analyses by deploying new methods from data analytics that render previously unintelligible data intelligible. A conceptual bridge is built between the two concepts of crowd signals and syndromic surveillance. A concise list of empirical observations supporting the hypothesis is presented. The key observation is that new social collective intelligence methods and algorithms allow for massive data analytics to stay with the individual, in micro. It is thus possible to provide the analyst with advice tailored to the individual and with relevant policies, without resorting to macro (statistical) analyses of homogeneous populations
Understanding Link Dynamics in Wireless Sensor Networks with Dynamically Steerable Directional Antennas
Get PDFUsing timetabling optimization prototype tools in new ways to support decision making
No full textThe Swedish infrastructure manager Trafikverket is funding research for timetabling optimization tools as part of their overall mission to utilize the existing infrastructure more efficiently. Currently, Trafikverket is modernizing both planning processes and the IT architecture, and will soon be ready to start using optimization tools on a broad scale. Meanwhile, innovative uses of a prototype developed at SICS have shown how a prototype does not necessarily merely serve to pave way for a future, large-scale implementation. This paper shows how computers in railway planning, coupled with OR techniques, relevant data and apt modeling, can help provide a future user with valuable insights even before the full-fledged tool is in place