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Open theses topics for the 2021/2022 study year
List of Supervisors
Making #smartenvironment smarter with #fog – #cloud computing platform
A list of Updated Thesis Topics can be found in this Google Doc: https://docs.google.com/document/d/14SPgOTF6f8nw8bpxl-3RMbDxwELranK1_bYBK2jzoy8/edit?usp=sharing
Contact: email@example.com, Delta building r3040
Serverless, IoT , Edge and Fog Computing
(Shivananda Poojara, firstname.lastname@example.org Delta R3033)
1. Predictive maintainance of SD Cards in IoT devices
The memory card faults or persistent failureness is major problem in IoT devices. There are several factors that implicitly effect the failureness of teh SD cars such as deployment of devcies in harsh envrionemnts, development of bad blocks and malware attacks, etc,. So an aim of theses is to setup IoT devices test bed using RPIs, try to collect failure data by emulating the scenarios and design solutions for prediction of the system using machine learning algorithms.
2. Autoscaling of serverless data pipelines in fog environments fog/edge computing environments.
In large scale IoT deployments, handling the fast movement of data is crucial. Most of the data movements are triggered by events with uncertainty. This fast inflow of events carrying data, needs to be handled efficiently to enact the QoS requirements. This can be achieved using various data flow engines such as Apache Nifi and stateless serverless functions. An aim of the given topic is to design novel auto scaling techniques to handle uneven requests of serverless functions to minimize the service time, latency and other QoS expectations. Scalability can be achieved within the cluster of fog nodes.
3. Usage based inusrance using IoT
Insurance policies historically have been based mostly on how much you drive, but with advanced telemetry and sensor data, it is possible to incorporate actual driving behaviors into insurance risk models. These behaviors include acceleration/deceleration, speed compared to speed limits, and types of driving, such as commuting on freeway compared to commuting on surface streets. Insurers base policies on observed driving behaviour, which means that safe drivers can be rewarded with lower insurance premiums. This can be achieved using IoT technology. So an aim of the theses is to look in to IoT devices and its ecosystem for usage based inusrance sector
4. COSCO: Container Orchestration Using Co-Simulation for Fog Computing Environments
The aim of this thesis is to explore COSCO(a fog computing tool) and understand the different container orchestration algorithms in this tool and propose solutions to address the challenges faced in data-oriented workflow-based deployments in edge fog applications. The COSCO is built with efficient machine learning algorithms for container placement with various QoS parameters such as energy, latency, etc.
5. Investigation of various managed serverless data pipelines
The goal of the topic is to investigate and benchmark functional and nonfunctional metrics for serverless data pipeline mechanisms provided by Google cloud, Azure Cloud, and AWS cloud services.
6. Investigation of opensource serverless platforms
The aim of the thesis is to study the existing investigation of the opensource serverless platforms such as OpenFaaS, Nuclio, Knative, Fission, and Kubeless. The following would be research questions that need to address.
- What are the architectural components used to design these systems?
- How do throughput and latency behaviors on various types s work workloads?
- How do auto-scaling works?
7. Study on edge anaytic frameworks
Internet of Things topics
(Already Taken) Cataloguing the Smart City and Building data (B, M) (Pelle Jakovits)
Nowadays it is quite common for new buildings to have hundreds or even thousands of sensors that generate data. The same can be said for cities, where data about different systems, devices, vehicles and people are being sensed and collected. Often this data is stored in a technical manner that is the most convenient for the actual hardware devices and networks that are used, but which makes it difficult to understand for humans and complicated to reuse in other applications. The goal of this topic is to investigate how to build both human- and machine-understandable data models for cataloguing the data that is being collected in Smart Buildings (E.g. Delta building) and Smart Cities (e.g. Tartu), with the aim to simplify the understanding and reusability of the data.
Synthetic IoT data generator for large scale IoT Device simulation (M) (Pelle Jakovits)
This topic is related to the Cyber defence simulation of Internet of Things and Mobile Networks in the Cyber Range project.
The student should evaluate extending open source tool for generating real-like IoT data based on existing captured data traces and “play it back” to simulate real data in an IoT network. The goal is to design and create a solution which processes existing data traces and can generate similar behaving data stream with high-volume and frequency. It should also support customizing the generated data stream, including volume and frequency, structure (like ratios between the different types of sub-streams), randomizing certain fields of records.
IoT data analytics for real-time visitor count estimation in the DELTA building (B, M) (Pelle Jakovits)
The Delta Building is a new building to house the Institute of Computer Science. Its construction was finished in 2020. A number of different modern sensors were placed in the building or can be placed in the future. The Computer Graphics and Virtual Reality lab’s students have created a real-time visualization of the people and activities inside the building. For that purpose, there is a desire to know how many people occupy each room (including the hallways) at any given moment. The goal of this topic is to study the state-of-the-art of sensor analytics or image processing (or fusion) and to create a usable approach for real-time visitor count estimation in lecture rooms.
(Already Taken) Reliability and performance of industrial IoT platforms (B, M) (Pelle Jakovits)
The goal of this topic is to analyse the reliability and performance of IoT platforms (e.g open-source IoT platforms, cloud services like Cumulocity, Amazon IoT, IBM IoT) focusing on solutions that support large use cases (e.g not home automation but rather Smart City, devices deployed over large geographical locations). The main aspects to focus on are the performance, stability and the scope of features (e.g device integration, integration with external services, data processing and analytics, extensibility). The main questions to answer are:
- Which of the solutions in the market are the most suitable for supporting large Smart City use cases.
- How easy is to integrate new IoT devices.
- Are open source IoT frameworks mature enough for production systems and are they feasible alternatives to cloud-managed subscription-based IoT platforms.
Universal Home hub (B) (Pelle Jakovits, Jakob Mass)
The goal of this topic is to investigate the feasibility and cost of building universal home hubs in comparison to depending on commercial brand home hubs. Each different home automation brand (e.g Philips or Fibaro) comes with its own hub, which makes integrating devices from different brands a complicated approach and may require deploying many different hubs in the same rooms, cluttering the space. Some sub-topics to focus on would be: home automation possibilities on open platforms, cloud Home Robots be used as home automation hubs.
Wireless vs wired home automation (B) (Pelle Jakovits, Jakob Mass)
Most new off-the-shelf Home automation IoT devices use Wireless connections, while typical building automation systems utilize wired connections. The goal of this topic is to investigate what are the disadvantages and advantages of wireless home automation devices, investigate their inter-connectivity, protocols, security, etc. One of the main research questions to answer would be: how many devices can a standard size homes/rooms support before the wireless networks quality starts degrading and what parameters can improve or degrade the quality and performance of such networks.
Large Scale Data Processing
Stream data processing on resource constrained devices (B/M) (Pelle Jakovits)
With the ever increasing amount of data that needs to be collected from IoT data sources, it becomes more and more expensive to simply stream all the data to a cloud-side data processing platform. Depending on specific scenarios, it may be beneficial to (pre-)process the data as close to its source as possible. However, there are limitations on how powerful computing resources are available near the data sources. The goal of this thesis is to evaluate existing solutions for streaming data processing which allow performing part of the data processing nearer to the source, give an overview of their usability, advantages and disadvantages and analyse their effectiveness in comparison to more classical stream data processing frameworks such as Apache Spark or Storm.
Distributed Serverless Data Processing in IoT networks (M) (Pelle Jakovits)
The goal of this topic is to study how efficiently Serverless technologies can be utilized to process data streams in multi layer (Fog computing) IoT networks in a distributed manner and compare the efficiency, reliability and security of this approach in comparison to the typical Cloud centric data processing.
Mobile Applications & Mobile Development
Automated Homework Grader for Android applications (Jakob Mass)
The Mobile Computing & Internet of Things course involves several assignments where students develop an Android application according to a set of requirements. Most of the functionality can usually be validated by means of testing interactions with the UI. The validation and grading could potentially be automated using UI testing tools such as Espresso or Roboelectric. In this thesis, the student should design & implement an automated grading system for Android for use by students and course instructors. The system should allow students to submit compiled Android apps and which give students feedback based on their submission. Further, the different submissions and results should be so that course organizers can keep track which students have successfully submitted which tasks.
Extending rule-based automation in the Home Assistant smart home platform (BSc)
Home Assistant is an open-source software platform which integrates a large selection of commercially available and also DIY IoT devices, supports manual and automated control of the devices in a smart home through UI dashboards, a rule-based automation system and more. This thesis will analyse Home Assistants existing automation system, understand its limits and based on the findings, propose an extension or replacement for it. One such replacement could potentially be based on a logic-based language such as Datalog, allowing more declarative, logical predicate-based rules and automation which are more flexible than a “if-this-then-that” based system. Alternatively, an improvement could be to introduce a system which detect common patterns of the smart home actions and propose to convert common habits into rules for the user. E.g. if the user always switches off all the lights in the living room after the TV is turned on on a weekday, the system could detect this pattern and recommend to automate it.