Browsing by discipline "Computer science"

With the increase in bandwidths available for internet users, cloud storage services have emerged to offer home users an easy way to share files and extend the storage space available for them. Most systems offer a limited free storage quota and combining these resources from multiple providers could be intriguing to cost-oriented users. In this study, we will implement a virtual file system that utilizes multiple different commercial cloud storage services (Dropbox, Google Drive, Microsoft OneDrive) to store its data. The data will be distributed among the different services and the structure of the data will be managed locally by the file system. The file system will be run in user space using FUSE and will use APIs provided by the cloud storage services to access the data. Our goal is to show that it is feasible to combine the free space offered by multiple services into a single easily accessible storage medium. Building such a system requires making design choices in multiple problem areas ranging from data distribution and performance to data integrity and data security. We will show how our file system is designed to address these requirements and will then conduct several tests to measure and analyze the level of performance provided by our system in different file system operation scenarios. The results will also be compared to the performance of using the distinct cloud storage services directly without distributing the data. This will help us to estimate the overhead or possible gain in performance caused by the distribution of data. It will also help us to locate the bottlenecks of the system. Finally, we will discuss some of the ways that could be used to improve the system based on test results and examples from existing distributed file systems.

Tämä työ tutkii Clojure-ohjelmointikieltä, joka on erityisesti rinnakkaisohjelmointiin suunniteltu Lisp-kielen murre. Clojure tukee vahvaa liitosta Java-ympäristöön ja sillä kirjoitetut ohjelmat suoritetaan JVM-virtuaalikoneella. Tutkielmassa käydään läpi Lisp-kielten historia, rinnakkaisohjelmoinnin yleiset haasteet ja funktionaalisen ohjelmointiparadigman perusteet. Lisäksi käsitellään Java-kielen ja JVM-virtuaalikoneen ja Clojure-kielen rinnakkaisohjelmointipiirteet. Tutkielman analyysiosassa verrataan Clojuren ja Javan rinnakkaisuusratkaisuja muun muassa tehokkuuden ja käytettävyyden osalta. Clojuren rinnakkaisuusratkaisuista transaktiomuisti osoittautui laskennallisesti hyvin raskaaksi. Lisäksi rinnakkaisratkaisujen lukottomuudesta seuraa se, että tietyt rinnakkaisohjelmointiongelmat ovat hankalia toteuttaa ilman, että käytetään Javan rinnakkaisratkaisuja. Erityisesti synkronisten rinnakkaisratkaisujen osalta kielessä olisi kehittämisen varaa. Javaan verrattuna Clojuren rinnakkaisuusratkaisut ovat hieman yksinkertaisempia käyttää. Tämä johtuu kuitenkin pitkälle Clojuren dynaamisesta tyypityksestä ja funktionaalisesta perusrakenteesta.

Biological cell is complicated and complex environment, in which thousands of entities interact surprisingly among each other. This integrated device continuously receives internal and external signals to perform the most vital processes to keep the continuation of life. Even though thousands of interactions are catalysed in very small spaces, biologists assert there are no coincidences or accidental events. On the other hand, fast discoveries in biology and the rapid evolution in the data pool make it even more difficult to construct concrete perspective that scientifically interprets all observations. Thereby, co-operation has become necessary between biologists, mathematicians, physicists and computer engineers. The goal of this virtual corporation is pursuance what is known as modelling biological network. The final thesis is aiming to make comparisons across different computational tools, which are built for modeling biological network. Additionally, technical themes, such as reaction kinetic, are explained beforehand. These topics represent backbone in the software functionality. Beside the technical issues, the study will compare different features such as GUI, command line, importing/exporting files, etc.

Along with the proliferation of smartphones, smartphone context-aware applications are gaining more and more attention from manufactures and users. With the capability to infer user's context information i.e., if the user is in a meeting, driving, running or at home, smartphone applications can react accordingly. However, limiting factors such as limited battery capacity, computing power and inaccuracy of inference caused by the in-accurate machine learning models and sensors hinder the large deployment of context-aware applications. In this master thesis, I develop CompleSense, a cooperative sensing framework designed for Android devices that facilitates the establishment and management of cooperation group so that developers can further exploit the potentials of cooperative sensing without worrying about the implementation of system monitoring, data throttling, aggregation and synchronization of data streams and wireless message passing via Wi-Fi. The system adopts Wi-Fi Direct technology for service advertisement and peer discovery. Once the cooperative group is formed, devices can share sensing and computing resources within short range via Wi-Fi connection. CompleSense allows developers to customize the system based on their own optimization needs, e.g., optimizing the trade-offs of cooperative sensing. System components are loosely coupled to ensure extensibility, resilience and scalability of the system, so that failure or change of a single component will not affect the remaining parts of the system. Developers can extend from the current system by adding customized data processing kernels, machine learning models and optimized sharing schemes. In addition to that, CompleSense abstracts the controlling logic of sensors, developers can easily integrate new sensors into the system by following a pre-defined a programming interface. The performance of CompleSense is evaluated by carrying out a cooperative audio similarity calculation task with varied number of clients which also confirms that CompleSense is feasible to be deployed for lower tier devices, such as Motorola Moto G.

Advanced low-cost wireless technologies have enabled a huge variety of real life applications in the past years. Wireless sensor technologies have emerged in almost every application field imaginable. Smartphones equipped with Internet connectivity and home electronics with networking capability have made their way to everyday life. The Internet of Things (IoT) is a novel paradigm that has risen to frame the idea of a large scale sensing ecosystem, in which all possible devices could contribute. The definition of a thing in this context is very vague. It can be anything from passive RFID tags on retail packaging to intelligent transducers observing the surrounding world. The amount of connected devices in such a worldwide sensing network would be enormous. This is ultimately challenging for the current Internet architecture which is several decades old and is based on host-to-host connectivity. The current Internet addresses content by location. It is based on point-to-point connections, which eventually means that every connected device has to be uniquely addressable through a hostname or an IP address. This paradigm was originally designed for sharing resources rather than data. Today the majority of Internet usage consists of sharing data, which is not what it was originally designed for. Various patchy improvements have come and gone, but a thorough architectural redesign is required sooner or later. Information-Centric Networking (ICN) is a new networking paradigm that addresses content by name instead of location. Its goal is to replace the current where with what, since the location of most content on the Internet is irrelevant to the end user. Several ICN architecture proposals have emerged from the research community, out of which Content-Centric Networking (CCN) is the most significant one in the context of this thesis. We have come up with the idea of combining CCN with the concept of IoT. In this thesis we look at different ways on how to make use of the hierarchical CCN content naming, in-network caching and other information-centric networking characteristics in a sensor environment. As a proof of concept we implemented a presentation bridge for a home automation system that provides services to the network through CCN.

In this thesis we present and evaluate a novel approach for energy-efficient and continuous transportation behavior monitoring for smartphones. Our work builds on a novel adaptive hierarchical sensor management scheme (HASMET), which decomposes the classification task into smaller subtasks. In comparison to previous work, our approach improves the task of transportation behavior monitoring on three aspects. First, by employing only the minimal set of necessary sensors for each subtask, we are able to significantly reduce power consumption of the detection task. Second, using the hierarchical decomposition, we are able to tailor features and classifiers for each subtask, improving the accuracy and robustness of the detection task. Third, we are able to extend the detectable motorised modalities to cover most common public transportation vehicles. All of these attributes are highly desirable for real-time transportation behavior monitoring and serve as important steps toward implementing the first truly practical transportation behavior monitoring on mobile phones. In the course of the research, we have developed an Android application for sensor data collection and utilized it to collect over 200 hours of transportation data, along with 2.5 hours of energy consumption data of the sensors. We apply our method on the data to demonstrate that compared to current state-of-art, our method offers higher detection accuracy, provides more robust transportation behavior monitoring and achieves significant reduction in power consumption. For evaluating results with respect to the continuous nature of the transportation behavior monitoring, we use event and frame-based metrics presented by Ward et al.

Pervasive longitudinal studies in people's intimate surroundings involve gathering data about how people behave in their various places of presence. It is hard to be fully pervasive as it has traditionally required sophisticated instrumentation that may be difficult to acquire and prohibitively expensive. Moreover, setting up such an experiment is laborious. We present a system, in the form of its requirements, design and implementation, that is primarily aimed at collecting data from people's homes. It aims to be as pervasive as possible, and can collect data about a family in the form of audio and video feed from microphones and cameras, network logs and home appliance (eg., TV) usage patterns. The data is then transported over the Internet to a server placed in the close proximity of the researcher, while protecting it from unauthorised access. Instead of instrumenting the test subjects' existing devices, we build our own integrated appliance which is to be placed inside their houses, and has all the necessary features for data collection and transportation. We build the system using cheap off-the-shelf commodity hardware and free and open source software, and evaluate different hardware and software configurations to see how well they can be integrated and how performant or reliable they are in real life scenarios. Finally, we demonstrate a few simple techniques that can be used to analyze the data to gain some insights into the behaviour of the participants.

Metagenomics promises to shed light on the functioning of microbial communities and their surrounding ecosystem. In metagenomic studies the genomic sequences of a collection of microorganisms are directly extracted from a specific environment. Up to 99% of microbes cannot be cultivated in the lab; thus, traditional analysis techniques have very limited applicability in this challenging setting. By directly extracting the sequences from the environment, metagenomic studies circumvents this dilemma. Thus, metagenomics has become a powerful tool in the analysis of the diversity and metabolic capability of environmental microbes. However, metagenomic studies have challenges of their own. In this thesis we investigate several aspects of metagenomic data set analysis, focusing on means of (1) verifying adequacy of taxonomic unit and enzyme representation and annotation in the sample, (2) highlighting similarities between samples by principal component analysis, (3) visualizing metabolic pathways with manually drawn metabolic maps from the Kyoto Encyclopedia of Genes and Genomes, and (4) estimating taxonomic distributions of pathways with a novel strategy. A case study of deep bedrock groundwater metagenomic samples will illustrate these methods. Water samples from boreholes, up to 2500 meter deep, of two different sites of Finland display the applicability and limitations of aforementioned methods. In addition publicly available metagenomic and genomic samples serve as baseline references. Our analysis resulted in a taxonomic and metabolic characterization of the samples. We were able to adequately retrieve and annotate the metabolic content based on the deep bedrock samples. The visualization provided a tool for further investigation. The microbial community distribution could be characterized on higher levels of abstraction. Previously suspected similarities to fungi or archaea were not verified. First promising results were observed with the novel strategy in estimating taxonomic distributions of pathways. Further results can be found at: http://www.cs.helsinki.fi/group/urenzyme/deepfun/

Self-aware computing is an emerging research area, which aims to solve issues stemming from a combination of increasingly more complex systems and diverse operating conditions. It adapts the key concepts of human self-awareness to the computational context. These concepts are well established in cognitive science, psychology, social psychology and philosophy, but novel in the software engineering context. Self-aware systems are able to acquire information about their environment and their internal state. The obtained information is used to build knowledge through reasoning. This increasing knowledge is used for building an internal learning model, which enables the system to adapt its actions. Self-aware systems can autonomously navigate runtime changes in their goals and environmental conditions, thus enabling a high degree of adaptivity to changing conditions that are difficult to predict at design time. In contrast, traditional systems have to operate with a set of predefined rules that are reliant on the design time knowledge of the designer. This study aims to identify proposed software architecture solutions that are of value for both practitioners and researchers. The study was conducted as a systematic literature review, for which we have developed a repeatable review protocol in order to cover all relevant literature in the area. The review protocol was explicitly defined and applied rigorously. In our review we managed to extract several proposed architecture designs from the reviewed 9 primary studies. These solutions propose several solutions, such as reference architectures, architecture frameworks, and architectural patterns for designing self-aware systems. This study can be used to get an overview of state of the art software architecture designs for self-aware systems. Additionally, this study can provide support for finding future research direction regarding self-aware systems.

Large screens, interactive or not, are becoming a common sight at shopping centers and other public places. These screens are used to advertise or share information interactively. Combined with the omnipresence of smartphones this gives rise for a unique opportunity to join these two interfaces and to combine their strengths and complement their weaknesses. Smartphones are very mobile thanks to their small size and can access information virtually from anywhere, but suffer from overflow of information. Users have too many applications and web sites to search relevant information to find what they want or need in a timely fashion. On the other hand, public screens are too large to provide information everywhere or in a personalized way, but they do often have the information you need, when and where you need it. Thus large screens provide an ideal place for users to select content onto their smartphones. Large screens also have the advantage of screen size and research has indicated that using a second screen with small handheld devices can improve the user experience. This thesis undertook design and development of a prototype Android application for existing large interactive public screen. The initial goal was to study the different aspects of personal mobile devices coupled with large public screens. This large screen interface is also under development as a ubiquitous system and the mobile application was designed to be part of this system. Thus the design of the mobile application needed to be consistent with the public screen. During the development of this application it was observed that the small mobile screen could not support the content or interactions designed for a much larger screen because of its small size. As a result this thesis focuses on developing a prototype that further research could draw upon. This lead to a study of small screen graph data visualization and previous research on mobile applications working together with large public screens. This thesis presents a novel approach for displaying graph data designed for large screens on a small mobile screen. This work also discusses many challenges and questions related to large screen interaction with mobile device that rose during the development of the prototype. An evaluation was conducted to gather both quantitative and qualitative data on the interface design and the consistency with the large screen interface to further analyze the resulting prototype. The most important findings in this work are the problems encountered and questions raised during the development of the mobile application prototype. This thesis provides several suggestions for future research using the application, the ubiquitous system and the large screen interface. The study of related work and prototype development also lead to suggestion of design guidelines for this type of applications. The evaluation data also suggests that the final mobile application design is both consistent with and performs better than a faithful implementation of the visuals and interaction model of the original large screen interface.