A Unified Load Generator for Geographically Distributed Generation ofNetwork Traffic

During the last decade, the Internet usage has been growing at an enormous rate which has beenaccompanied by the developments of network applications (e.g., video conference, audio/videostreaming, E-learning, E-Commerce and real-time applications) and allows several types ofinformation including data, voice, picture and media streaming. While end-users are demandingvery high quality of service (QoS) from their service providers, network undergoes a complex trafficwhich leads the transmission bottlenecks. Considerable effort has been made to study thecharacteristics and the behavior of the Internet. Simulation modeling of computer networkcongestion is a profitable and effective technique which fulfills the requirements to evaluate theperformance and QoS of networks. To simulate a single congested link, simulation is run with asingle load generator while for a larger simulation with complex traffic, where the nodes are spreadacross different geographical locations generating distributed artificial loads is indispensable. Onesolution is to elaborate a load generation system based on master/slave architecture.

Cloud computing - Moving to the cloud

Cloud computing innebär användning av datorresurser som är tillgängliga via ett nätverk, oftast Internet och är ett område som har vuxit fram i snabb takt under de senaste åren. Allt fler företag migrerar hela eller delar av sin verksamhet till molnet. Sogeti i Borlänge har behov av att migrera sina utvecklingsmiljöer till en molntjänst då drift och underhåll av dessa är kostsamma och tidsödande. Som Microsoftpartners vill Sogeti använda Microsoft tjänst för cloud computing, Windows Azure, för detta syfte. Migration till molnet är ett nytt område för Sogeti och de har inga beskrivningar för hur en sådan process går till. Vårt uppdrag var att utveckla ett tillvägagångssätt för migration av en IT-lösning till molnet. En del av uppdraget blev då att kartlägga cloud computing, dess beståndsdelar samt vilka för- och nackdelar som finns, vilket har gjort att vi har fått grundläggande kunskap i ämnet. För att utveckla ett tillvägagångssätt för migration har vi utfört flera migrationer av virtuella maskiner till Windows Azure och utifrån dessa migrationer, litteraturstudier och intervjuer dragit slutsatser som mynnat ut i ett generellt tillvägagångssätt för migration till molnet. Resultatet har visat att det är svårt att göra en generell men samtidigt detaljerad beskrivning över ett tillvägagångssätt för migration, då scenariot ser olika ut beroende på vad som ska migreras och vilken typ av molntjänst som används. Vi har dock utifrån våra erfarenheter från våra migrationer, tillsammans med litteraturstudier, dokumentstudier och intervjuer lyft vår kunskap till en generell nivå. Från denna kunskap har vi sammanställt ett generellt tillvägagångssätt med större fokus på de förberedande aktiviteter som en organisation bör genomföra innan migration. Våra studier har även resulterat i en fördjupad beskrivning av cloud computing. I vår studie har vi inte sett att någon tidigare har beskrivit kritiska framgångsfaktorer i samband med cloud computing. I vårt empiriska arbete har vi dock identifierat tre kritiska framgångsfaktorer för cloud computing och i och med detta täckt upp en del av kunskapsgapet där emellan.

Ubiquitous computing in education : a SWOT analysis by students and teachers

Learning from anywhere anytime is a contemporary phenomenon in the field of education that is thought to be flexible, time and cost saving. The phenomenon is evident in the way computer technology mediates knowledge processes among learners. Computer technology is however, in some instances, faulted. There are studies that highlight drawbacks of computer technology use in learning. In this study we aimed at conducting a SWOT analysis on ubiquitous computing and computer-mediated social interaction and their affect on education. Students and teachers were interviewed on the mentioned concepts using focus group interviews. Our contribution in this study is, identifying what teachers and students perceive to be the strength, weaknesses, opportunities and threats of ubiquitous computing and computer-mediated social interaction in education. We also relate the findings with literature and present a common understanding on the SWOT of these concepts. Results show positive perceptions. Respondents revealed that ubiquitous computing and computer-mediated social interaction are important in their education due to advantages such as flexibility, efficiency in terms of cost and time, ability to acquire computer skills. Nevertheless disadvantages where also mentioned for example health effects, privacy and security issues, noise in the learning environment, to mention but a few. This paper gives suggestions on how to overcome threats mentioned.

How does data quality in a network affect heuristic solutions?

To have good data quality with high complexity is often seen to be important. Intuition says that the higher accuracy and complexity the data have the better the analytic solutions becomes if it is possible to handle the increasing computing time. However, for most of the practical computational problems, high complexity data means that computational times become too long or that heuristics used to solve the problem have difficulties to reach good solutions. This is even further stressed when the size of the combinatorial problem increases. Consequently, we often need a simplified data to deal with complex combinatorial problems. In this study we stress the question of how the complexity and accuracy in a network affect the quality of the heuristic solutions for different sizes of the combinatorial problem. We evaluate this question by applying the commonly used p-median model, which is used to find optimal locations in a network of p supply points that serve n demand points. To evaluate this, we vary both the accuracy (the number of nodes) of the network and the size of the combinatorial problem (p). The investigation is conducted by the means of a case study in a region in Sweden with an asymmetrically distributed population (15,000 weighted demand points), Dalecarlia. To locate 5 to 50 supply points we use the national transport administrations official road network (NVDB). The road network consists of 1.5 million nodes. To find the optimal location we start with 500 candidate nodes in the network and increase the number of candidate nodes in steps up to 67,000 (which is aggregated from the 1.5 million nodes). To find the optimal solution we use a simulated annealing algorithm with adaptive tuning of the temperature. The results show that there is a limited improvement in the optimal solutions when the accuracy in the road network increase and the combinatorial problem (low p) is simple. When the combinatorial problem is complex (large p) the improvements of increasing the accuracy in the road network are much larger. The results also show that choice of the best accuracy of the network depends on the complexity of the combinatorial (varying p) problem.

Soft computing in biometrics : a pragmatic appraisal

The ever increasing spurt in digital crimes such as image manipulation, image tampering, signature forgery, image forgery, illegal transaction, etc. have hard pressed the demand to combat these forms of criminal activities. In this direction, biometrics - the computer-based validation of a persons' identity is becoming more and more essential particularly for high security systems. The essence of biometrics is the measurement of person’s physiological or behavioral characteristics, it enables authentication of a person’s identity. Biometric-based authentication is also becoming increasingly important in computer-based applications because the amount of sensitive data stored in such systems is growing. The new demands of biometric systems are robustness, high recognition rates, capability to handle imprecision, uncertainties of non-statistical kind and magnanimous flexibility. It is exactly here that, the role of soft computing techniques comes to play. The main aim of this write-up is to present a pragmatic view on applications of soft computing techniques in biometrics and to analyze its impact. It is found that soft computing has already made inroads in terms of individual methods or in combination. Applications of varieties of neural networks top the list followed by fuzzy logic and evolutionary algorithms. In a nutshell, the soft computing paradigms are used for biometric tasks such as feature extraction, dimensionality reduction, pattern identification, pattern mapping and the like.