Research Trends in the Internet of Things


This seminar is fully booked

Learning Goals

Based on up-to-date examples, students learn and deepen their skills in independent and self-responsible working with scientific literature as well as with written and oral presentation of scientific and technical content.

Students reflect presented content and practise expressing their opinion in discussions among peers.

Depending on their topic, students get to know a concrete system, a generic concept, or one or multiple technical implementations. At the end of the semester they are able to put their topic in a wider context and are able to autonomously judge on the pros and cons.


At the beginning students are introduced to basic principles of scientific work including literature research, writing techniques, and presentation styles. This shall help and guide students from a methodological point of view. The actual work (paper writing and preparation of presentation) happens in tight and individual interaction with the respective advisor. The results of the research are then presented in front of the plenum and discussed in the group. Topic-wise, the seminar covers all aspects of IoT ranging from the operation of a data centre, to specialised operating systems, to big data analytics, and middleware.

General Information

  • Lecturer

  • Institute

    Information Resource Management

  • Pre-requisits


  • Elective lecture

    For students Master Communication Technology,

  • ECTS


  • Effort

    V/Ü/P/S 0/0/0/1

  • Language

    English or German

  • Type


  • Grading Method

    Graded based on self-initiative, quality of paper, quality of talk, presence, and activity in discussions

  • Lecture Start

    15.04.16 at 13:00

  • Number of Students

    4 - 12

  • Dates and times

    as announced in moodle

  • Registration and material


Topic 1 - Data locality

Many IoT devices produce data e.g. from sensor measurements. Instead of transmitting all data to a central point (i.e. the cloud), it can also be stored more locally to save communication bandwidth. Depending on the location and behaviour of producers and consumers of data and the availability of data storage, different data storage strategies might be considered. Data that changes frequently but is seldomly read might be placed close to the producer, while frequently accessed data could be stored closer to the consumer to optimize performance. For some cases it might even be reasonable to replicate data to save bandwidth.

This seminary talk/topic summarizes recent efforts to optimize data locality and compares them with respect to overhead and applicability to different scenarios.

One possible starting point could be this paper.

Topic 2 - Database scalability and elasticity frameworks for IoT

Along with the evolvement of IoT the growing amount of highly distributed applications put new challenges on the specific application types, especially on the scalability and elasticity. Regarding databases, the NoSQL movement already provided a large set of distributed databases (e.g MongoDB, Apache Cassandra). They promise a highly scalable architecture and providing elasticity to cope with the dynamic Cloud and IoT environment. However, to unfold the full potential of these distributed databases and optimising their scalability and elasticity capabilities additional frameworks are required. This seminar topic should give an overview of existing framework solutions for distributed databases targeting their scalability and elasticity capabilities.

A starting point could be the Tiramola and MET frameworks.

Topic 3 - Network Flow Observation for Flow Control with SDN

Software Defined Networks (SDN) offer a flexible approach for controlling the network flow dynamically. A global view of the network and its network devices (i.e. sensors or virtual machines in a Cloud) allow to react on the actual needs: flows can be optimised between heavily loaded devices, or can be blocked in case of intrusions. While SDN offers the control mechanisms, sFlow defines a standard to monitor and analyse network devices.

The research question to be answered in this topic is as follows: how to detect shortcomings and network issues in IP based networks, in order to react on them using SDN functionalities?

As a starting point the following paper might be helpful.

Topic 4 - Edge Computing Usecases

During the past few years, with the proliferation of the Internet of Things (IoT), many application areas have started to exploit this paradigm, and bring together many technological areas together, such as cloud environments. Additionally, network providers want to bring processing power within a close proximity to their subscribers. Hence, the concept of reducing the latency, and offloading tasks with data intensive jobs to more powerful machines is emerging.

The research that has to be done for this topic is, to identify different usecases that can take advantage of moving computations to the edge of network and define their requirements.

A starting point for this can be this paper

Topic 5 - Dataflows in an IoT ecosystem

An interconnected environment can be consisted of multiple devices, sensors, machines, all coupled together in an IoT ecosystem. Data processing levels within this ecosystem are forced in order to deliver the expected result to the end user on time. Hence, computation results can be combined and fed as an input to another computation, formulating an execution flow.

The research of this topic focuses on how context awareness can enhance the delivery of such execution flow within an IoT ecosystem.

A good start for the topic can be this paper

Topic 6 - Orchestration of IoT devices

Internet of Things (IoT) describes the idea of enhancing objects by the ability to interconnect themselves and receiving, processing and transmitting data. These devices are typically very constrained. In future there will be a huge amount of connected IoT devices. Each device offers different capabilities and services. It requires management platforms to make use of them. For example if a device needs to do a task engaging heavy processing it could be better to outsource it to a device that has more processing power. A management system could handle the allocation of the needed resources for a task based on the constraints of a certain IoT device.

This seminary talk/topic summarizes the a selection of approaches in middlewares, platforms or protocols, that try to cater for managing IoT devices. A comparison works out and discusses the differences in terms of features as well as architectural approaches.

An example for such an approach could be found here and here.

This topic can be done by multiple students, each with the focus on another type of approach (middleware, platform and protocol).

Topic 7 - SDN traffic monitoring framework

Software Defined Networking (SDN) is a trending concept which is based on separating the data plane from the control plane. In SDN systems such as large-scale data centre networks, an essential part of network management is continuous monitoring of different performance metrics. One example can be link utilization for faster adoption of forwarding rules with respect to dynamic workload. The statistical results from monitoring have to be accurate and timely. The current flowbased network monitoring tools produce extreme overhead since the statistics are generated from the overall network at the central controller. To gain high accuracy and low overhead, some concepts have been developed: 1. OpenSketch, 2. PayLess, 3. MicroTE, 4. OpenSample

The evaluation should consist of an analysis of the above options such as their pros and cons as well as drawing a conclusion by determining the best solution for reduced overhead and high accuracy. The question that should be tackled after investigating the above options is, 'How to increase accuracy and decrease network overhead when aggregating the networks statistics by the SDN controller or a monitoring device?'

A good starting point can be this paper.

Topic 8 - IoT of today, future perspectives and directions

Together with Cloud Computing belongs Internet of Things (IoT) to the main trends of 2016. It is a complex concept with own paradigms, definitions and directions. Today IoT connects almost all aspects of our life. That’s why it is absolutely true to say that being an expert in this area gives you all chances to be successful in IT sphere today.

The idea of this topic is to get global knowledge about IoT – what paradigms and directions does it have, what of them are the most popular, interesting and actual for today. Also the nearest future should be considered – what directions could be successful tomorrow, what could be chosen as topic for deep investigation and research, especially with a connection to the Cloud Computing and Microcomputers. At the finish of the research the student should choose the 1 favourite IoT field and make a short description of it from IT-developer’s point of view – what software and frameworks could be used to work there.

As start point for the research could be analysed this paper

This topic can be done by multiple students, each with the focus on another IoT application.

Topic 9 - Enable High Performance Computing in Cloud Computing Environments

High Performance Computing (HPC) applications are demanding for high performance, why the migration to virtualised Cloud setups is uncommon. Cloud computing offers flexibility of dynamically balancing application load on physical infrastructure, but decreases performance due to virtualisation and simple, memory based scheduling. This topic is looking into approaches for enabling HPC in typical Cloud computing environments. As a starting point for researching the following paper might be helpful.

Topic 10 - Scalable monitoring frameworks for IoT

Along with the evolvement of IoT the growing amount of highly distributed devices put new challenges on the monitoring environments. An arbitrary amount of sensors generate a tremendous amount of raw monitoring data by measuring any kind of system or application metric. The monitoring data needs to be stored and processed for further evaluation. The arbitrary amount of sensors and the actual monitoring data size represent the new challenges for existing monitoring environments. In the recent years time-series databases came up with the promise to fit for these challenges.

This seminar topic should give an overview of new monitoring environments for IoT with the focus on the scalability of the monitoring framework and the storage backend. A starting point could be:[1], [2]

Keywords: cloud monitoring, Iot monitoring, tsdb, time series database