https://dasya.itu.dk/semester/fall-2019/ Recent content in Fall 2019 on DASYA Hugo -- gohugo.io en-us © DASYA, IT University of Copenhagen Mon, 16 Dec 2019 00:00:00 +0000 https://dasya.itu.dk/for-students/proposals/archive/a-gui-for-the-things-network-lorawan-stack-v3/ Mon, 16 Dec 2019 00:00:00 +0000 https://dasya.itu.dk/for-students/proposals/archive/a-gui-for-the-things-network-lorawan-stack-v3/ The Things Network Stack v3 for LoRaWAN is an open source LoRaWAN network stack suitable for large, global and geo-distributed public and private networks as well as smaller networks. The architecture follows the LoRaWAN Network Reference Model for standards compliancy and interoperability. - https://github.com/TheThingsNetwork/lorawan-stack This stack, currently in pre-rollout testing, however has no Web GUI yet, and is administered solely via a CLI. This project aims at building a user-friendly, inclusive and innovative web GUI, with hooks to new informative features such as node and gateway statistics, location services and others. https://dasya.itu.dk/for-students/proposals/archive/accelerated-distributed-platform-for-spatial-queries/ Mon, 16 Dec 2019 00:00:00 +0000 https://dasya.itu.dk/for-students/proposals/archive/accelerated-distributed-platform-for-spatial-queries/ It is now common to query terabytes of spatial data. Several new frameworks extend distributed computing platforms such as Hadoop and Spark to enable them to efficiently process spatial queries by providing (1) mechanisms to efficiently store spatial data and index them ; and (2) packages of built in spatial operations for these platforms. Meanwhile, it is now common to accelerate Hadoop and Spark using accelerators such as GPUs and FPGAs. https://dasya.itu.dk/for-students/proposals/archive/competitor-for-the-video-browser-showdown/ Mon, 16 Dec 2019 00:00:00 +0000 https://dasya.itu.dk/for-students/proposals/archive/competitor-for-the-video-browser-showdown/ The goal of this project is to integrate Exquisitor with other pieces of existing technology and turn into a competitor for a live video retrieval competition. The project is suitable for 3-4 well-qualified MSc students. The ​Video Browser Showdown​ (VBS) is a live competition​ for video search andretrieval, held at the International Conference on Multimedia Modeling (MMM). In VBS, the competition tasks involve finding videos from a collection of 1000 hours of videos. https://dasya.itu.dk/for-students/proposals/archive/computational-storage/ Mon, 16 Dec 2019 00:00:00 +0000 https://dasya.itu.dk/for-students/proposals/archive/computational-storage/ Offloading processing to storage is a means to avoid data movement and thus deal efficiently with very large volumes of stored data. In the 90s, there were pioneering efforts to develop Processing-in-Memory as well as Active Disks. We are considering data stored on Open-Channel SSDs with a programmable storage controller (i.e., a Linux-based ARM processor) integrated into a network switch (e.g., Broadcom Stingray or NXP LS2). Topics for thesis include (1) the design/implementation and evaluation of a prototype key-value store running on the storage controller, (2) the design/implementation/evaluation of a 100GB Ethernet-based RPC connection between host and storage controller, and (3) the development of a new recovery scheme for a user-space Flash Translation Layer embedded on the storage controller. https://dasya.itu.dk/for-students/proposals/archive/database-performance-characteristics/ Mon, 16 Dec 2019 00:00:00 +0000 https://dasya.itu.dk/for-students/proposals/archive/database-performance-characteristics/ Characterize the performance of commercial database systems on an NVIDIA Titan GPU, or Characterize the performance of DB2 PureScale on a cluster equipped with shared storage with a range of different benchmarks. Design and conduct experiment with a range of tuning strategies to measure their impact on performance and reliability. https://dasya.itu.dk/for-students/proposals/archive/decentralized-cloud-management/ Mon, 16 Dec 2019 00:00:00 +0000 https://dasya.itu.dk/for-students/proposals/archive/decentralized-cloud-management/ In the context of the Orkney Cloud project, we are preparing the deployment of a decentralized cloud infrastructure on the archipelago. The infrastructure is composed of a collection of Pods (point of delivery) and a wireless core (5G + Wifi). Each Pod is equipped with storage, computing and communication components (so that it is connected to the core and to local endpoints). Each Pod is powered directly on a renewable source, via a power conditioner, and is thus equipped with batteries. https://dasya.itu.dk/for-students/proposals/archive/diversity-of-relevance-feedback/ Mon, 16 Dec 2019 00:00:00 +0000 https://dasya.itu.dk/for-students/proposals/archive/diversity-of-relevance-feedback/ The goal of this project is ensure diversity in the relevance feedback results, to improve quality of the user experience. The project is suitable for 1-3 well-qualified MSc students. In many creative tasks, the designer will knowsome stock image is good for a design just stumbling upon the image. This “Aha!” moment requires browsing thousands of images by categories. In other words, it requires labeled and categorized images. Labeling hundreds of millions of images, such as the 99. https://dasya.itu.dk/for-students/proposals/archive/efficient-os-level-context-switching-for-thread-migration/ Mon, 16 Dec 2019 00:00:00 +0000 https://dasya.itu.dk/for-students/proposals/archive/efficient-os-level-context-switching-for-thread-migration/ Spreading the computation of similar concurrent tasks that have a large instruction footprint over multiple cores via thread migration is shown to improve the instruction cache utilization drastically since it allows instruction re-use across the concurrent tasks. However, thread migrations are costly due to the context switching overhead. To reduce this overhead, recent work mainly proposed techniques at the hardware-level. However, developing techniques at the level of the OS might be more effective in terms of the adoption of such thread migration mechanisms. https://dasya.itu.dk/for-students/proposals/archive/exploring-image-collections-via-eye-tracking/ Mon, 16 Dec 2019 00:00:00 +0000 https://dasya.itu.dk/for-students/proposals/archive/exploring-image-collections-via-eye-tracking/ The goal of this project is to use state of the art in eye tracking to design, implement and evaluate different eye-tracking interfaces for Exquisitor. The project is suitable for 1-3 well-qualified MSc students. Image and media collections are becoming a central information resource for a growing number of domains. This calls for very effective tools for interactive exploration of the contents of those collections [1]. Since humans typically look at the targets of interest before making a selection, the eyes can become a very efficient means browsing media collections (e. https://dasya.itu.dk/for-students/proposals/archive/extending-spark-scheduler-for-heterogeneous-clusters/ Mon, 16 Dec 2019 00:00:00 +0000 https://dasya.itu.dk/for-students/proposals/archive/extending-spark-scheduler-for-heterogeneous-clusters/ Spark assumes that it executes its applications on a homogeneous cluster of similar nodes. However, it is becoming common that in-house clusters have heterogeneous compute re- sources and it is good to exploit all of them in the most efficient way. The objective of this master thesis is to extend the Spark scheduler to be resources- aware and to efficiently schedule Spark tasks on all the available resources in the cluster. https://dasya.itu.dk/for-students/proposals/archive/leveraging-heterogeneous-hardware/ Mon, 16 Dec 2019 00:00:00 +0000 https://dasya.itu.dk/for-students/proposals/archive/leveraging-heterogeneous-hardware/ The computer architecture community is moving toward commoditization of hardware specialization instead of general purpose CPUs and more agile hardware development instead of years-long production cycles to enable faster, more energy-efficient, and more cost-effective hardware/software co-designs. This will lead to a disruption in the way we design and maintain the emerging data management systems as well. As the heterogeneity of hardware resources increase, it becomes essential for the data management systems to decide on the optimal design options based on the processor types they are running on. https://dasya.itu.dk/for-students/proposals/archive/micro-architectural-analysis-of-systemml/ Mon, 16 Dec 2019 00:00:00 +0000 https://dasya.itu.dk/for-students/proposals/archive/micro-architectural-analysis-of-systemml/ Apache SystemML is an open-source platform to run machine learning tasks efficiently thanks to the hardware-conscious query compilation techniques it adopts. It can be run standalone or on top of Apache Spark. It is considered to be state-of-the-art when running machine learning tasks (i.e., in ACM SIGMOD 2017, there were ~5 papers that used SystemML as a comparison point). This project aims at understanding how efficiently SystemML utilizes the resources of commodity server hardware, and how this differs from some other widely used systems used to run machine learning (e. https://dasya.itu.dk/for-students/proposals/archive/mobile-air-quality-monitoring/ Mon, 16 Dec 2019 00:00:00 +0000 https://dasya.itu.dk/for-students/proposals/archive/mobile-air-quality-monitoring/ New types of networks such as LoRaWAN and Sigfox enable us to deploy inexpensive mobile Air Quality Sensors, e.g. on bicycles or vehicles, boats or trains, and help map and understand urban pollution. Such data would be valuable for e.g. the international citizen science project Luftdaten https://luftdaten.info/en/home-en/ in which we are participating. We have an ongoing collaboration with the Asian Instite of Technology, Bangkok, experience in collaborationg with the Institute for Environmental Science, and a concrete request from a municipality here in Denmark. https://dasya.itu.dk/for-students/proposals/archive/mobile-version-of-exquisitor/ Mon, 16 Dec 2019 00:00:00 +0000 https://dasya.itu.dk/for-students/proposals/archive/mobile-version-of-exquisitor/ The goal of this project is build a prototype of the Exquisitor system for mobile devices. The project is suitable for 1-3 well-qualified MSc students. Image and media collections are becoming a central information resource for a growing number of domains. This calls for very effective tools for interactive exploration of the contents of those collections [1].Based on past research results [2], we have built a prototype of such an exploration tool, called Exquisitor. https://dasya.itu.dk/for-students/proposals/archive/multi-query-optimization-in-spark/ Mon, 16 Dec 2019 00:00:00 +0000 https://dasya.itu.dk/for-students/proposals/archive/multi-query-optimization-in-spark/ Distributed computing platforms such as Hadoop and Spark focus on addressing the fol- lowing challenges in large systems: (1) latency, (2) scalability, and (3) fault tolerance. Dedicating computing resources for each application executed by Spark can lead to a waste of resources. Unified distributed file systems such as Alluxio has provided a platform for computing results among simultaneously running applications. However, it is up to the developers to decide on what to share. https://dasya.itu.dk/for-students/proposals/archive/predicting-execution-times-queries-executed-on-accelerated-distributed-platforms/ Mon, 16 Dec 2019 00:00:00 +0000 https://dasya.itu.dk/for-students/proposals/archive/predicting-execution-times-queries-executed-on-accelerated-distributed-platforms/ In the last few years, it became common to accelerate Hadoop and Spark by enabling them to execute tasks and jobs on accelerators such as GPUs and FPGAs. The objective of this master thesis is to study new approaches that efficiently predicts the execution time of Spark tasks and jobs executed on GPUs. Part of the work will be to build a performance prediction model for GPUs, which can be built using machine learning techniques among others. https://dasya.itu.dk/for-students/proposals/archive/satellite-data/ Mon, 16 Dec 2019 00:00:00 +0000 https://dasya.itu.dk/for-students/proposals/archive/satellite-data/ Can we combine satellite data with terrestrial and marine sensor data, to study their correlation, and benefit our understanding of environmental processes, both in urban and agricultural/rural context? Potential collaboration with several organizations in Kenya and Orkney islands. https://dasya.itu.dk/for-students/proposals/archive/small-smart-city/ Mon, 16 Dec 2019 00:00:00 +0000 https://dasya.itu.dk/for-students/proposals/archive/small-smart-city/ Not far from the IT University, citizens are buillding a “Small Smart City”, aiming to measure and analyze e.g. water and resource consumption. Help build the Small Smart City! https://dasya.itu.dk/for-students/proposals/archive/a-sound-based-predictive-maintenance/ Mon, 16 Dec 2019 00:00:00 +0000 https://dasya.itu.dk/for-students/proposals/archive/a-sound-based-predictive-maintenance/ Survey of potential sensor modalities (sounds, ultrasounds, vibrations) and related work (e.g., wind turbines) Starting with sound: Piezo contact mics/transducers, MEMS sensors Characterization of state based on known signatures (classification problem) Characterization of state transitions (HMM) Experimentation on Coffee machine/Blender/3D printer at PitLab 1..k sensors; Local/cloud-based processing. Experimentation on roller compacter/tableting machines at NN https://dasya.itu.dk/for-students/proposals/archive/storage-system-performance-characteristics/ Mon, 16 Dec 2019 00:00:00 +0000 https://dasya.itu.dk/for-students/proposals/archive/storage-system-performance-characteristics/ New forms of Solid State Drives have interesting characteristics in terms of performance (10 to 100x faster than previous generations of SSDs) and in terms of functionalities (SSDs can now suspend the execution of writes or erase operations to minimize read latency). The performance characteristics of these devices is not well understood yet. The topic of this thesis is to design and conduct experiments to fully characterize the performance of such SSDs. https://dasya.itu.dk/for-students/proposals/archive/b-temperature-based-predictive-maintenance/ Mon, 16 Dec 2019 00:00:00 +0000 https://dasya.itu.dk/for-students/proposals/archive/b-temperature-based-predictive-maintenance/ Survey of potential sensor modalities (IR temp sensor, thermal imager) and related work Starting with consumer USB cams generate series of images or phone cams Characterization of state based on known signatures (classification problem) Characterization of state transitions (HMM) Experimentation on Coffee machine/Blender/3D printer at PitLab 1..k sensors; Local/cloud-based processing. Experimentation on roller compacter/tableting machines at NN https://dasya.itu.dk/for-students/proposals/archive/the-ms-iot-gateway/ Mon, 16 Dec 2019 00:00:00 +0000 https://dasya.itu.dk/for-students/proposals/archive/the-ms-iot-gateway/ Most data collection in IoT does not critically depend on latency or speed from data collection to data analytics. Occasionally though we meet tasks that would benefit from near-realtime features, such as collection of wave and tidal dynamics around marine energy infrastructures. This project explores the limits of speed by bringing together a LoRa PHY, a LoRaWAN gateway, LoRaWAN stack, ultrafast storage and near data processing in one physical unit. This project combines hardware, software and networks aspects of embedded computing. https://dasya.itu.dk/for-students/proposals/archive/the-trekktracker/ Mon, 16 Dec 2019 00:00:00 +0000 https://dasya.itu.dk/for-students/proposals/archive/the-trekktracker/ In collaboration with the IoT Lab at Computer Science Dept at Kathmandu University, Nepal, we are developing a potential service for tracking trekkers, i.e. offering a security service for tourists trekking the Himalayas, in particular Mt. Everest. This service very critically depends on having a robust hardware component, the actual GPS/GNSS tracker. Requirements with respect to battery life, temperature, physical environment are extremely challenging, and need to be tackled in a combination of hardware and software optimization. https://dasya.itu.dk/for-students/proposals/archive/what-is-htap/ Mon, 16 Dec 2019 00:00:00 +0000 https://dasya.itu.dk/for-students/proposals/archive/what-is-htap/ The popularity of large-scale real-time analytics applications (real-time inventory/pricing, recommendations from mobile apps, fraud detection, risk analysis, IoT, etc.) keeps rising. These applications require distributed data management systems that can handle fast concurrent transactions (OLTP) and analytics on the recent data. Some of them even need running analytical queries (OLAP) as part of transactions. Efficient processing of individual transactional and analytical requests, however, leads to different optimizations and architectural decisions while building a data management system. https://dasya.itu.dk/for-students/proposals/archive/4-wind-turbine-data-publication/ Mon, 16 Dec 2019 00:00:00 +0000 https://dasya.itu.dk/for-students/proposals/archive/4-wind-turbine-data-publication/ Wind turbine electricity production data is sensitive for Energinet (and for the wind turbine producers). Energinet would like to publish wind turbine electricity production data sets that can be used to train relevant models and to develop innovative applications, without giving away sensitive data. The goal of the project is to explore various data publishing methods for that purpose. https://dasya.itu.dk/for-students/proposals/archive/wind-turbine-electricity-production-analysis/ Mon, 16 Dec 2019 00:00:00 +0000 https://dasya.itu.dk/for-students/proposals/archive/wind-turbine-electricity-production-analysis/ Energinet has a model that describes the electricity production of a given wind turbine given wind conditions. The current model based on kNN is trained with DMI weather data and historical electricity production data for the wind turbine. The goal of the project is to improve the current model with lifelong learning, extended weather data and different models for a range of different wind turbines. Testing models in reverse, it should also be possible to derive wind conditions from a turbine’s electricity production. https://dasya.itu.dk/for-students/proposals/archive/wind-turbine-electricity-production-prediction/ Mon, 16 Dec 2019 00:00:00 +0000 https://dasya.itu.dk/for-students/proposals/archive/wind-turbine-electricity-production-prediction/ The goal of the project is to explore the accuracy of electricity production predictions based on historical data and weather predictions. This may be tackled as a sequence prediction problem using recurrent neural networks The long term goal is to incorporate wind turbines in the reserve market for electricity. https://dasya.itu.dk/for-students/proposals/archive/3-wind-turbine-non-invasive-instrumentation/ Mon, 16 Dec 2019 00:00:00 +0000 https://dasya.itu.dk/for-students/proposals/archive/3-wind-turbine-non-invasive-instrumentation/ The goal of the project is to explore new ways of gathering data about wind turbines as well as local wind/weather conditions. To this end, sound/vibration-based and/or image-based instrumentation as well as innovative experiments such as balloons and light weight weather stations might be considered. https://dasya.itu.dk/for-students/proposals/archive/workload-characterization-for-big-data-management/ Mon, 16 Dec 2019 00:00:00 +0000 https://dasya.itu.dk/for-students/proposals/archive/workload-characterization-for-big-data-management/ The Transaction Processing Performance Council (TPC) is a non-profit IT organization founded to define database benchmarks and disseminate objective, verifiable performance data to the industry. TPC has standardized several new benchmarks (e.g., TPCx-HS and TPCx-BB), in recent years. Older popular benchmarks, like TPC-C (representing high-performance transaction processing) and TPC-H (representing traditional analytical processing), are not suitable to explain the behavior of the emerging big data applications (with heavy ingest rates and complex analytical queries involving machine learning) on modern hardware. https://dasya.itu.dk/for-students/projects/archive/speechrecognition/ Sun, 15 Dec 2019 00:00:00 +0000 https://dasya.itu.dk/for-students/projects/archive/speechrecognition/ Investigating the behavior of acoustic model training via deep learning on co-processors of different price groups