Student Work

Internetkommunikation offers the opportunity to develop interesting software solutions for technical questions about internet protocols and mechanisms. For the next semester, a position is available to assist the teaching assistants for the tutorials and class project.

• Knowledge in computer networking

• Good programming skills in Python

Aeronautical applications such as satellite communications and in aircraft systems have enhanced the range of applications for 5G, bringing new opportunities and potentials.

In the new 6G era these industries are envisioned to receive even more attention due to the high coverage possibilities that they provide. Applications such as unmanned aerival vehicles, flying taxis, moving base stations are just a few to name. In that regard, to support these wide range of applications, new 6G network urge for new and more efficient architectures.

In this thesis the student shall focus on the analysis of existing archiectures for 5G/6G for aeronautical applications and shall perform a comparison, definining potentials for the development of new architectures to reduce delay and increase the network performance. To this end, a comprehensive analysis is required to define the right metrics for comparison and identifying the potentials for improvement. An initial simulator based on the defined metrics is to be created to enable the comparison of similar algorithms in the future.

• Good knowledge of simulation environments such as Matlab, Python.
• Good mathematical background.
• Knowledge about satellite communications is a plus.

5G Networks are anticipated to support the tremendous growth in the traffic demands and the heterogeneity of future applications. In that regard network slicing paves the way towards programmable and flexible networks. On the other hand, delay critical applications require an additional boost on the performance which solutions like Mobile Edge Computing (MEC) or network caching can provide. 

In this thesis the student shall focus on the algorithmic part of the joint network slicing and edge caching. A solution to efficiently manage the resources in order to provide the required performance is needed. To this aim, learning approaches could potentially be utilized for the resource allocation in order to further improve the performance.

• Good knowledge of simulation environments such as Matlab, Python.
• Good mathematical background. Basic knowledge of network slicing and optimization algorithms is a plus.

For this thesis, the student will consider different scenarios for the functional split of the 5G Core VNFs and the impact they have on the overall performance of the Mobile Core Network. 

- General knowledge about Mobile Networks (RAN & Core).

- Strong programming skills. Knowledge of Go (https://golang.org/) is a plus.

Age of Information(AoI) is defined as the elapsed time since the generation of the most recent packet. It has been used as a cross-layer metric in remote monitoring and controlling scenarios.

AoI-aware networking & protocol design requires the modification within the communication stack. To that end, our department has set up a testbed that consists of multiple software-defined radios (SDRs) programmed in GNU Radio. This enables us to develop our own solutions, e.g., MAC protocol, routing algorithms etc. to improve e.g. AoI performance at the application layer.

This tasks of this project will consist of:

• Working with the existing setup, that consists of multiple SDRs programmed with GNU Radio / C++
• Scheduling of flows over multi-hop paths between the source and the destination pairs
• Performance analysis and comparison of experimental results to analytical ones from the literature

The project requires:

• Solid C/C++ knowledge and low-level programming
• Python skills are beneficial
• Solid fundamental knowledge in wireless communications
• Having worked with practical implementations of wireless communication devices is a great benefit, such as SDRs or sensor motes (some examples are Telosb Motes, Zolertia Re-motes, ...)

The 5G cellular networks are the state-of-the-art cellular networks for the coming 10 years. One of the critical network functions in the 5G core system is the evolved packet gateway or User Plane Function (UPF). The UPF is responsible for carrying the users' packets from the base stations to the data network (like the internet). 

On the other hand, P4 is a promising language for programming packet processors. It can be used to program different networking devices (Software/FPGAs/ASICs/...).

Using P4 to implement the UPF has many advantages in terms of flexibility and scalability. In this work, the student will realize/implement the UPF in P4 language. Then, the advantages of this approach, especially in terms of performance gains, will be evaluated.

-Good programming skills

-Basic Linux knowledge

-Motivation and critical thinking

-Knowledge about LTE, 5G, or P4 is a plus.

Cloud Native deployments of the 5G Core network are gaining increasing interest and many providers are exploring these options. One of the key technologies that will be used to deploy these Networks, is Kubernetes (k8s).

In 5G, NG Application Protocol (NGAP) is used for the gNB-AMF (RAN-Core) communication. NGAP uses SCTP as a Transport Layer protocol. In order to load balance traffic coming from the gNB towards a resilient cluster of AMF instances, a L4 load balancer needs to be deployed in the Kubernetes Cluster.

The goal of this project is do develop a SCTP Load Balancer to be used in a 5G Core Network to aid the communication between the RAN and Core.
The project will be developed using the language Go (https://golang.org/).

- General knowledge about Mobile Networks (RAN & Core).
- Good knowledge of Cloud Orchestration tools like Kuberentes.
- Strong programming skills. Knowledge of Go (https://golang.org/) is a plus.

endri.goshi@tum.de

GNU Radio is a free & open-source software development toolkit that provides signal processing blocks to implement software radios. It can be used with readily-available low-cost external RF hardware to create software-defined radios, or without hardware in a simulation-like environment. It is widely used in research, industry, academia, government, and hobbyist environments to support both wireless communications research and real-world radio systems.(https://www.gnuradio.org/)

LKN has a testbed comprised of multiple feedback control loops communicating over a wireless network. The communication is done with software-defined radios (SDRs) that are programmed with the help of GNURadio.The task of this project is to conduct a detailed latency analysis of the existing testbed code implemented with GNURadio toolkit.

The current framework consists of 2 main blocks: 1) Graphical User Interface implemented in Python 2) Software for wireless communications is implemented with GNUradio in C++.

The task involves close investigation of latency contributions by different parts of the system, where are the packets buffered and how can it be optimized for the existing task., It requires getting into the details of GNURadio.

The student is asked to have:

• Experience with software development on Linux-based operating systems.
• Familiarity with common Linux system administration tasks and the command line.
• Programming ability in C, C++, Python.
• Good communication & writing skills in English
• Motivation and self-organization throughout the thesis

The following are beneficial for conducting the thesis:

• Some experience with practical hardware in the past, e.g. wireless sensor motes, SDRs.
• It is beneficial to have GNUradio experience but not mandatory.

Time Sensitive Networks aim to provide for mechanisms and methods for deterministic delay and jitter in industrial networks. Sources of delay and jitter in a TSN can be numerous, e.g., misconfigured or incorrectly dimensioned TAS schedules, congested egress ports, large clock jitter in distributed time synchronization, congestion at egress / ingress ports of the end-stations, variable switch backplane delays etc. are all possible causes of poor end-to-end performance.

In this work, an existing approach to end-to-end monitoring of transmission delay and jitter will be extended to support for quick identification of source of the anomaly in a TSN scenario (i.e., the root cause). Two or more approaches will be proposed to cater for end-to-end monitoring of TSN streams, relying on:

1) intermediate, pre-placed network TAPs;

2) hardware / software data plane agents capable of telemetry and dynamic re-programming to support the quick identification of anomaly sources for individual streams.

Any resulting overhead of the intermediary monitoring solution will be quantified for consideration in the TSN stream planning. The work will hence implement and validate the monitoring mechanisms in an existing TSN testbed that relies on a Linux-based control plane, and will optionally involve P4-based middlebox devices to serve as intermediate monitoring entities. 

[1] 802.1Qbv - Enhancements for Scheduled Traffic - http://www.ieee802.org/1/pages/802.1bv.html

[2] Improving Network Monitoring and Management with Programmable Data Planes - https://p4.org/p4/inband-network-telemetry/

- Good knowledge of networking concepts and architectures

- Good knowledge and practical experiences with Linux networking

- Good knowledge of Python, C or Rust

- Any prior experience with TSN, P4, SDN is a plus but not mandatory

ermin.sakic@siemens.com

blenk@tum.de

andreas.zirkler@siemens.com

IEEE 802.1Qbv Time-Aware Shaper (TAS) standardizes the mechanisms for TDMA-based packet transmission in future Ethernet deployments, as well as the interfaces for definition and configuration of associated transmission schedules [1].

In this work, a state-of-the-art end-to-end TAS-based scheduler will be extended with schemes enabling for data plane redundancy under consideration of worst-case delay and jitter constraints. Support for TSN streams with 1:1 replication for proactive redundancy, as well as an approach to efficient schedule reservation with reactive 'fast-failover' redundancy will be investigated, implemented, and subsequently evaluated in terms of adherence to jitter, delay, and packet loss constraints, as well as the computation complexity and acceptance rates of the approach.

The joint routing/scheduling task will first be formulated as an optimization problem and implemented using an optimization solver. The student will then extend the existing TAS scheduler relying on metaheuristics for faster execution compared to using a solver.

[1] IEEE 802.1Qbv - Enhancements for Scheduled Traffic - http://www.ieee802.org/1/pages/802.1bv.html

[2] IEEE P802.1CB – Frame Replication and Elimination for Reliability - https://1.ieee802.org/tsn/802-1cb/ 

- Good knowledge of networking concepts and architectures

- Good knowledge and practical experiences with Linux networking

- Good knowledge of Python

- Any prior experience with optimization methods and tools is a plus, but not mandatory

- Any prior experience with TSN and SDN is a plus

ermin.sakic@siemens.com

blenk@tum.de

andreas.zirkler@siemens.com

<p>The course "Data Networking" (replaces Broadband Communication Networks) of Prof. Wolfgang Kellerer teaches network-related methods of mobile communication: WIFI, 2G to 5G cellular networks, etc. In order to bridge the gap between the methods and real life, innovative teaching concepts will be applied and developed to present Data Networking in a blended learning format based on Podcasts (the students learn and experiment in short episodes about wireless communication and networking in day to day scenarios), online quizzes, feedback channels, recording of lecture, tutorial and discussions.</p>

<p>In order to setup and support the course Data Networking in WS 20/21, Prof. Kellerer is looking for students experienced in programming and in video tools for recording and other online tools (incl. moodle) to help him. Work can start in Sept./Oct 2020 already for preparations.</p>

Note: This work can also be be done in parallel to taking the course Data Networking in WS 20/21

<p>Programming skills; experience with online teaching tools, video tools and recording; knowledge of communication networks </p>

Arled Papa (arled.papa@tum.de)

Anna Prado (anna.prado@tum.de)

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The goal is to investigate the impact of topology, addressing scheme and communication pattern on the learnability of a routing protocol.

Software-Defined Radio Access Network (SD-RAN) is receiving a lot of attention in 5G networks, since it offers means for a more flexible and programmable mobile network architecture.

The heart of the SD-RAN architecture are the so called SD-RAN controllers. Currently, initial prototypes have been developed and used in commercial and academic testbeds. However, most of the solutions only contain a single SD-RAN controller. Nonetheless, a single controller becomes also a single point of failure for a system, not only due to potential controller failures but also due to a high load induced from the devices in the data plane.

To this end a multi-controller control plane often becomes a reasonable choice. However, a multi-controller control plane renders the communication among the controllers more challenging, since they need to often exchange control information with each other to keep an up to date network state. Unfortunately, currently there is no protocol available for such a communication.

The aim of this work is the development and implementation of an East/West API for SD-RAN controller communication according to 5G stardardization. The protocol should enable the exchange of infromation among the SD-RAN controllers regarding UEs, BSs, wireless channel state and allow for control plane migration among controllers.

• Experience with programming languages Python/C++.
• Experience with socket programming.
• Knowledge about SDN is a must.
• Knowledge about 4G/5G networks is a plus.

Wireless resource allocation for networked control systems. An extension of the SotA with Gilbert-Elliot Model is the aim of this work.

Goal is to implement a probabilistic graphical model to represent weighted graphs with overlapping communities.

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Das Thema dieser Bachelorthesis ist die Entwicklung, Optimierung und Evaluation des proprietären Brandmeldebussystems LSNi1 der Firma Bosch Sicherheitssysteme GmbH in Grasbrunn.

Brandmeldeanlagen sind ein bestehender notwendiger Teil der Gebaudetechnik und sollen fur neue vernetzte IoT-Dienste verwendet werden. Aufgrund immer höheren Anforderungen dieser Dienste soll die Datenrate uber den Brandmeldebus gesteigert werden. Zur Zeit wird das Bussystem zur verhaltnismäßig datenarmen Alarmabfrage und Antwort der Netzelemente verwendet. Ein wichtiger Punkt ist dabei, die Systemcharakteristika des Brandmeldesystems nicht zu verschlechtern. Solche Netzwerke sind als Sicherheitssysteme deklariert und mussen daher äußerst zuverlässig in Sachen Ausfallsicherheit und Fehlererkennung sein.

Die Aufgabe besteht darin, eine neue Übertragungstechnik mit höherer Datenrate auf der physikalischen Schicht des Busses zu finden und diese mit Hilfe eines Prototypen umzusetzen. Die Optimierung des Prototypen soll durch Berechnung und Experimentieren mit Systemelementen ausgearbeitet werden. Daraufhin werden verschiedene Testaufbauten, im firmeneigenen Labor getestet. Die dabei aufgenommenen Daten werden über ein entwickeltes Matlab-Evaluierungsprogramm ausgewertet, um eindeutige Aussagen über die Funktionalitat des Systems zu geben. Eine besondere Herausforderung bei Systemen dieser Art sind die hohen Kabellängen und die große Anzahl an Systemelementen auf dem Bus. Mit den ausgewerteten Ergebnissen soll überpruft werden, in welchem Umfang die Datenrate auf dem Bus gesteigert werden kann.

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Flexible optical networks achieve a significant increase of network capacity by assigning as much spectrum to the demands as needed. With advances in transponders supporting software tunable channel configurations, network planners are able to select the best combination of data rate, modulation format and forward error correction (FEC) for each light-path. However, the impact of failures in these networks is higher due to the closeness between channels as well as the low OSNR margins.

Hence, in this thesis we will apply machine learning techniques to predict and detect faults based on available monitored data of a flexible optical network provided by ADVA.

In this thesis student will focus on designing and implementing a hierarchical SDN solution for industrial multi-domain TSN network.

kostas.katsalis@huawei.com

In this thesis, studnt will try to implement a simple TCP proxy with a P4 programming language.

LiFi (Light-fidelity) is becoming an increasingly important technology as the unlicensed ISM band gets overcrowded. LiFi, with its high data rates, emerges as a promising solution to provide connectivity using LED lights thereby reducing the interference with other wireless technologies. Due to the unique properties of a visible light communication system, the position of the access points/LEDs/Optical front end (OFE) has a significant effect on the network coverage and illumination level in an indoor area.

The placement of these OFEs is a 3D placement problem. This work involves optimizing the placement of the OFEs given a set of requirements eg. throughput, luminance, etc. Given these requirements the goal is to find the optimal placement such that, for example, throughput is maximized.

Related Reading:-

• H. Haas, L. Yin, Y. Wang and C. Chen, "What is LiFi?," in Journal of Lightwave Technology, vol. 34, no. 6, pp. 1533-1544, 15 March15, 2016, doi: 10.1109/JLT.2015.2510021.

• Uluturk, I., Uysal, I., & Chen, K. C. (2019, January). Efficient 3d placement of access points in an aerial wireless network. In 2019 16th IEEE Annual Consumer Communications & Networking Conference (CCNC) (pp. 1-7). IEEE.

• Python 
• Sound knowledge of Wireless Communication
• Interest to learn new communication technologies
• Experience with optimization problems is an advantage

Congestion control (CC) can help achieve the requirements of today's and future generation data center networks (DCNs): namely high bandwidth, ultra-low latency and stability. There are several state-of-the-art proposals but there is no optimal CC scheme yet. Categorizing the CC schemes into end-host control and in-network scheduling, we at Huawei Munich Research Center believe that in-network scheduling provides faster convergence of transmission rate towards the fair rate of the network as compared to end-host control. A novel in-network scheduling CC algorithm together with an optimal load balancing scheme has been designed for RoCEv2 (RDMA over Converged Ethernet version 2) transport. The proposed CC algorithm leverages in-network telemetry (INT) to estimate link load information and pace traffic accordingly, thereby, reducing congestion. It has optimal packet level scheduling and is traffic insensitive, thus fair to all flows (like that of Processor Sharing). The algorithm is also simple (in terms of simple operations on packet arrival) and can be deployed in the DCN switches. The goal of the algorithm is to minimize the FCT (flow completion time) of large flows and provide a bounded delay for short flows. The load balancing scheme built on top of the optimal scheduling scheme aims to optimize the overall network performance, achieving higher network utilization while guaranteeing the performance of individual flows. We intend to compare this algorithm by simulation in Omnet++ simulator with some state-of-the-art algorithms from which the algorithm derives its motivation.

The student will develop a benchmarking tool for P4Runtime controllers. Then the performance of ONOS controller with P4Runtime southbound protocol will be evaluated and compared to that when OpenFlow is adopted as a southbound protocol.

SDN, P4, and JAVA programming skills.

Industry 4.0 scenarios have introduced the novel requirements for dynamic device-to-device interaction without strict plan-ahead interactions (typical of Industrial Ethernet of the last two decades). For example, the use cases of work piece de-attachment and interacting Automated Guided Vehicles (AGVs) in factory automation impose the need for dynamic inter-connection of distributed industrial applications at runtime [1] without a plan-ahead schedule.

Dynamic TSN stream establishment has been proposed by IEEE802.1 to address scenarios of applications requesting real-time communication services at runtime [2, 3]. TSN schedulers capable of computing the transmission schedules with guaranteed real-time properties (upper-bound constraints on latency, jitter, and guaranteed bandwidth) have accordingly been proposed in the past, however, they have traditionally focused on one-time / offline execution [4].

Combined with the requirement for dynamic and efficient resource (de-)allocation, transmission schedules must generally be adaptable at runtime in order to provide for maximum efficiency in network resource utilization. This work will investigate the runtime adaptation of TSN control and data plane to support for the dynamic stream allocation. Algorithms for adaptation of existing TAS-based schedules with minimal impact on availability (packet loss) and QoS guarantees for running TSN streams will be proposed, implemented, and validated. Novel metrics for stream consistency conservation may need to be proposed by the approach. The resulting approach will eventually be evaluated in NeSTiNg (OMNeT++/INET) simulator and/or a small-scale physical testbed comprising multiple TSN switches and end-stations.

[1] IEC/IEEE 60802 TSN Profile for Industrial Automation - https://1.ieee802.org/tsn/iec-ieee-60802/

[2] P802.1Qdd – Resource Allocation Protocol - https://1.ieee802.org/tsn/802-1qdd/

[3] 802.1Qat - Stream Reservation Protocol -/ http://www.ieee802.org/1/pages/802.1at.html

[4] Dürr et al., No-wait Packet Scheduling for IEEE Time-sensitive Networks (TSN) - https://dl.acm.org/doi/abs/10.1145/2997465.2997494

- Very good knowledge of networking concepts and architectures

- Very good knowledge and practical experiences with Linux networking

- Good knowledge of Python, C, C++ or Rust

- Any prior experience with optimization methods and and tools and OMNeT++  is a plus

- Any prior experience with TSN is a plus

- Any prior experience with SDN is a plus

- Proficient English and/or German communication skills

- Ability to work and pursue solutions under limited supervision

ermin.sakic@siemens.com

blenk@tum.de

andreas.zirkler@siemens.com

Current SD-RAN platforms are only evaluated for small network dimensions due to expensive wireless hardware. However, in order to test the real scalability of the existing solutions a large number of devices needs to be deployed. To this end, an emulation mode for the control and data plane is seen as a potential solution. 

In this work, the student shall deploy a data plane user based simulator that is able to connect to an SD-RAN controller through a control plane channel and report user specific statistics. Considering a distributed SD-RAN control plane, the control handover becomes a crucial aspect that introduces potential delays. In this thesis, the effect on the user perfromance should be measured with respect to the control handover.

The main goal of this work is to investigate the real time deployment of an SD-RAN architecture and identify potential bottlenecks regarding the control plane signaling and its effects on the users in the data plane.

• Mandatory programming skills in Python, C++ is a plus.
• Mandatory knowledge about socket programming.
• Knowledge about mobile networks 4G/5G.
• Knowlegde about event based simulators is a plus.
• Experience with google protobuffers is a plus.

More and more devices communicate wirelessly in the cabin. This includes, seat screens, passenger devices (mobile phones, laptops), sensors and actuators. As of today, the complete unlicensed spectrum is used. In future, 5G-NR-U base station can be deployed in this scenario, to offer new connectivity possiblities. This requires new coexistence mechanisms that do not put further strain on spectrum resources.

The goal of this thesis is to extend a pre-existing enhance a pre-existing simulator (based on matlab) for 5G-NR-U signal demodulation, with the help of pre-existing matlab 5G-NR-U functions. After extending the simulator, different scenarios and channel etimation techniques should be investigated, as well as several Key Performance Indicators such as Bit Error Rate, Signal-to-Interference-to-Noise-Ratio and throughput.

The overall goal is to show that interference cancellation, the underlying concept of Rate Splitting and NOMA is viable even in a challenging environment such as an aircraft cabin where the high density of radio devices is a challenge

Tasks

• Review of related literature
• Extend our simualtion from 4G to 5G
• Compare different channel estimation techniques
• Evaluate of the simulation results

Preferred Qualifications

• Experience in matlab
• Interest in signal modeling
• Interest in new communication technologies

Related Work

Interference Cancelation
https://www.researchgate.net/profile/Cheng-Xiang_Wang/publication/
224083390_Cognitive_radio_networks/links/0fcfd50b57f883862f000000/Cognitive-radio-
networks.pdf
5G-NR-U
https://de.mathworks.com/help/5g/examples/nr-pdsch-throughput.html
Channel Estimation Techniques
https://ieeexplore.ieee.org/document/1033876
http://engold.ui.ac.ir/~sabahi/Advanced%20digital%20communication/Channel%20estimation%20for
%20wireless%20OFDM%20sysytems.pdf

In this work, the student will derive analytical equations for different performance metrics related to P4 devices. The modeling will be based on queuing theory and previously conducted measurements on P4 devices. Simulations will be used to verify the derived performance model. 

Knowledge about P4, Queuing Theory, and Matlab. 

Today's Data Center (DC) networks are facing increasing demands and a plethora of requirements. Factors for this are the rise of Cloud Computing, Virtualization and emerging high data rate applications such as distributed Machine Learning frameworks.
Recently several new architectures have been proposed that rely on reconfigurable optics to evolve the topology over time, such as Helios[3], Projector[5], c-Through[1] or RotorNet[6].
Some of these approaches learn attributes of the traffic distribution in the network to determine topology configurations, e.g., xWeaver[4] or DeepConf[2].
A different stream of research focuses on generating adversarial input to networks or networking algorithms [7,8] to identify weak spots or improve robustness and solution quality of data-driven approaches.
The goal of this thesis is to apply the latter one to reconfigurable topology designs with the main focus on the data-driven variants (xWeaver) to benchmark their performance and to improve their solution quality.
The thesis builds upon an existing flow-level simulator in Python and initial algorithms that generate adversarial inputs for networking problems.

[1] G. Wang et al., “c-Through: Part-time Optics in Data Centers,” presented at the ACM SIGCOMM, 2010, p. 12.
[2] S. Salman, C. Streiffer, H. Chen, T. Benson, and A. Kadav, “DeepConf: Automating Data Center Network Topologies Management with Machine Learning,” in Proceedings of the 2018 Workshop on Network Meets AI & ML, New York, NY, USA, 2018, pp. 8–14, doi: 10.1145/3229543.3229554.
[3] N. Farrington et al., “Helios: A Hybrid Electrical/Optical Switch Architecture for Modular Data Centers,” pp. 1–12, 2010.
[4] M. Wang et al., “Neural Network Meets DCN: Traffic-driven Topology Adaptation with Deep Learning,” Proceedings of the ACM on Measurement and Analysis of Computing Systems, vol. 2, no. 2, pp. 1–25, Jun. 2018, doi: 10.1145/3224421.
[5] M. Ghobadi et al., “ProjecToR: Agile Reconfigurable Data Center Interconnect,” 2016, pp. 216–229, doi: 10.1145/2934872.2934911.
[6] W. M. Mellette et al., “RotorNet: A Scalable, Low-complexity, Optical Datacenter Network,” 2017, pp. 267–280, doi: 10.1145/3098822.3098838.
[7] S. Lettner and A. Blenk, “Adversarial Network Algorithm Benchmarking,” in Proceedings of the 15th International Conference on emerging Networking EXperiments and Technologies, Orlando FL USA, Dec. 2019, pp. 31–33, doi: 10.1145/3360468.3366779.
[8] J. Zerwas et al., “NetBOA: Self-Driving Network Benchmarking,” in Proceedings of the 2019 Workshop on Network Meets AI & ML  - NetAI’19, Beijing, China, 2019, pp. 8–14, doi: 10.1145/3341216.3342207.

Recently, a scalable load balancing algorithm in the dataplane has been proposed that leverages P4 to estimate the utilization in the network and assign flows to the least utilized path. This approach can be interpreted as a form of Graham's List algorithm.

In this thesis, the student is tasked to investigate how a different online scheduling algorithm called IMBAL performs compared to HULA. A prototype of IMBAL should be implemented in NS3. The tasks of this thesis are:

1. Literature research and overview to online scheduling and traffic engineering in data center networks.
2. Design how IMBAL can be implemented in NS3.
3. Implementation of IMBAL in NS3.
4. Evaluation of the implementation in NS3 with production traffic traces and comparison to HULA (a HULA implementation is provided from the chair and its implementation not part of this thesis).

Next generation mobile networks are envisioned to cope with heterogeneous applications with diverse requirements. To this end, 5G is paving the way towards more scalable and higher performing deployments. This leads to a revised architecture, where the majority of the functionalities are implemented as network functions, which could be scaled up/down depending on the application requirements. 

3GPP has already released the 5G architecture overview, however there exists no actual open source deployment of RAN functionalities. This will be crucial towards the evaluation of the Core network both in terms of scalability and performance. In this thesis, the student shall understand the 5G standardization, especially the control plane communication between the RAN and 5G Core. Further, an initial RAN function compatible with the 5G standards shall be implemented and evaluation of control plane performance will be carried out. 

• Strong knowledge on programming languages Python, C++ or Java.
• Knowledge about mobile networking is necessary.
• Knowlegde about 4G/5G architecture is a plus.

Introduction to Software Defined Networking (SDN) and Network Virtualization paradigms has brought new challenges to tackle. In this environment, network switches communicate to SDN controllers through a hypervisor. Therefore, considering a network graph, three questions may come up: 1) Where to deploy SDN controllers? 2) Where to deploy SDN hypervirors? 3) How to connect network switches to the respective SDN controllers to meet the traffic dynamicity and QoS requirements?

In this work, we plan to design and evaluate an optimization framework to optimally answer the above questions.

Mathematical Optimization, Algorithms, Java / Python

amir.varasteh@tum.de

Optical core networks deploy fixed grid in order to accommodate their demands. The trend is however, migrate towards flexgrid networks able to use as much spectrum as required by the demand allowing a better use of the spectrum. However, the Routing and Wavelength Assignment (RWA) paradigm becomes more complex as it has to find the suitable spectrum of the demand.

This thesis will consider different multiplexing alternatives: space division, band division multiplexing, etc.

The objective is to compare the performance, throughput, BoM, etc. of the different alternatives for different networks and demand evolution matrices.

Java programming skills

Basic knowledge of flexible optical networks

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Increased interference is one of the main drawbacks of cell densification, which is an important strategy for 5G networks to achieve higher data rates. Function centralization has been proposed as a strategy to counter this problem, by letting the physical or scheduling functions coordinate among one another. Nevertheless, the capacity of the fronthaul network limits the feasibility of this strategy, as the throughput required to connect low level functions is very high. Fortunately, since not every function benefits in the same way from centralization, a more flexible approach can be used. Instead of centralizing all functions, only those providing the highest amount of interference mitigation can be centralized. In addition, the centralization level, or functional split, can be change during runtime according to the instantaneous network conditions. Nonetheless, it is not fully know how costly it is to deploy and operate a network implementing a dynamic functional split.

In this internship, the cost of a radio access network implementing a dynamic functional split will be evaluated. A simulator already developed at LKN will be used and extended to produce network configurations adapted to the instantaneous user position and activity. Then, off-the-shelf cost models will be improved and used to estimate the deployment and operating cost of the network under multiple scenarios. Furthermore, the conditions on which a dynamic functional split is profitable will be investigated. Improvements on the functional-split selection algorithm will be proposed, such that the operator benefits from enhanced performance without operating at exceedingly costly states. Finally, a model that takes into account the cost of finding and implementing a new functional split will be employed and its results compared to the previous results.

The Optical Networking Industry now aims to move into a disaggregated transport network use case, so that operators can reduce operation costs and deploy open solutions for management and control of such networks. SDN controllers based on Open Daylight TransportPCE and OpenROADM Models. 

In this internship, a student will deploy such a testbed integrated with LKN's in-house network planner and then conduct measurements to provide first insights into Online Optical Network Planinng

1. Knowledge of Optical Networks

2. Knowledge of SDN

3. Good to have working knowledge of Java.

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Network slicing is a novel approach used in 5G networks to enable the deployment and coexistence of heterogeneous network with various Quality of Service (QoS) requirements in the same physical infrastructure. In the Radio Access Network (RAN) the network slicing concept is complex is due to the stochastic nature of wireless channels and scarce resources. Vast of ongoing research deal with optimization approaches for RAN slicing, however most of the focus is on the downlink scenario. Nonethess, a joint optimization of downlink and uplink scenarios can render the problem more complex, but on the other hand can procude better results for the overal system behavior.

In this master's thesis the student will focus on a combined downlink/uplink scenario of a cellular system and provide a joint optimization algorithm to enhance the network performance and compare it with the separate uplink and downlink approach. 

• Basic knowledge of cellular systems 4G/5G.
• Good knowledge of programming languages Python, Matlab.
• Good mathematical background, especially on optimization techniques.
• Knowlegde of tools such as Gurobi is a plus.

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One of the advantages of the new Mobile Core Network architecture consists of leveraging the flexibility VNFs in deploying the Core Network.
In this thesis, the student will evaluate and compare different scaling mechanisms (e.g., vertical vs. horizontal, reactive vs. proactive, etc.) and their impact in the perfomance of the 5G Core.

- General knowledge about Mobile Networks (RAN & Core).

- Good knowledge of Cloud Orchestration tools like Kuberentes.

- Good programming skills. Knowledge of Go (https://golang.org/) is a plus.

The goal of this work is to predict the trajectory of a mobile user using recurrent neural networks (eg. LSTM). Having this information, one can then use this to predict, for example, in 5G, to predict when to make handovers.

The tasks involved are:-

1. Creating realistic datasets (eg. varying user speeds) from the SLAW mobility model and extracting useful features.
2. Using an optimized LSTM architecture to predict the trajectory and to verify how far in the future the trajectory can be predicted. 
3. Check how transferrable this architecture is to other mobility models.

Related Work:

Lee, K., Hong, S., Kim, S.J., Rhee, I. and Chong, S., 2009, April. Slaw: A new mobility model for human walks. In IEEE INFOCOM 2009 (pp. 855-863). IEEE.

Gebrie, H., Farooq, H. and Imran, A., 2019, May. What machine learning predictor performs best for mobility prediction in cellular networks?. In 2019 IEEE International Conference on Communications Workshops (ICC Workshops) (pp. 1-6). IEEE.

• Python knowledge
• Knowledge of machine learning algorithms (especially recurrent neural networks)
• Interest in learning about mobility models

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• yle="color: black; mso-margin-top-alt: auto; mso-margin-bottom-alt: auto; mso-list: l0 level1 lfo1; tab-stops: list 36.0pt;">Characterization of Coherent optical high speed modems
• yle="color: black; mso-margin-top-alt: auto; mso-margin-bottom-alt: auto; mso-list: l0 level1 lfo1; tab-stops: list 36.0pt;">Flexible bit rates of 100 Gbps to 600 Gbps with respect to possible standardization of these interfaces

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Today's Data Center (DC) networks are facing increasing demands and a plethora of requirements. Factors for this are the rise of Cloud Computing, Virtualization and emerging high data rate applications such as distributed Machine Learning frameworks.
Recently, several new architectures have been proposed that rely on topologies that can be reconfigured during run-time with the goal to account for changing demands.
One example is Solstice [1] which proposes a scheduling algorithm for hybrid networks with electrical packet switch parts and optical circuit switches.
It specifically considers the non-trivial switching times of optical circuit switches while also accounting for limited bandwidth on electrical packet switches.
The goal of this research internship is to re-implement and evaluate Solstice in an existing flow-level simulator, to verify the original results and compare it to other topologies and identify pontetial weak spots in terms of traffic patterns that are not well handled by Solstice's approach.

[1]H. Liu et al., “Scheduling techniques for hybrid circuit/packet networks,” in Proceedings of the 11th ACM Conference on Emerging Networking Experiments and Technologies - CoNEXT ’15, Heidelberg, Germany, 2015, pp. 1–13, doi: 10.1145/2716281.2836126.

In electronics and telecommunication, jitter is a significant and an undesired factor. The effect of jitter on the signal depends on the nature of the jitter. It is important to sample jitter and noise sources when the clock frequency is especially prone to jitter or when one is debugging failure sources in the transmission of high speed serial signals. Managing jitter is of utmost importance and the methods of jitter decomposition have changed comparably over the past years.

yle="background-image: initial; background-position: initial; background-size: initial; background-repeat: initial; background-origin: initial; background-clip: initial;"> 

yle="background-image: initial; background-position: initial; background-size: initial; background-repeat: initial; background-origin: initial; background-clip: initial;">In a system, jitter has many contributions and it is not an easy job to identify the contributors. It is difficult to get Random Jitter on a spectrogram. The waveforms are initially constant, but the 1/f noise and flicker noise cause a lot of disturbance when it comes to output measurement at particular frequencies in a system. 

yle="background-image: initial; background-position: initial; background-size: initial; background-repeat: initial; background-origin: initial; background-clip: initial;"> 

yle="background-image: initial; background-position: initial; background-size: initial; background-repeat: initial; background-origin: initial; background-clip: initial;">The task is to understand the difference between the jitter calculations based on a step response estimation and the dual dirac model by comparing the jitter algorithms between the R&S oscilloscope and other competition oscilloscopes. Also to understand how well the jitter decomposition and identification is there.

yle="margin-bottom: 8.0pt; line-height: 105%;"> 

yle="background-image: initial; background-position: initial; background-size: initial; background-repeat: initial; background-origin: initial; background-clip: initial;">The tasks in detail are as follows.

yle="background-image: initial; background-position: initial; background-size: initial; background-repeat: initial; background-origin: initial; background-clip: initial;">Setup a waveform simulation environment and extend to elaborate test cases

yle="background-image: initial; background-position: initial; background-size: initial; background-repeat: initial; background-origin: initial; background-clip: initial;">Run the generated waveforms through the algorithms

yle="background-image: initial; background-position: initial; background-size: initial; background-repeat: initial; background-origin: initial; background-clip: initial;">Analyze and compare the results:

yle="background-image: initial; background-position: initial; background-size: initial; background-repeat: initial; background-origin: initial; background-clip: initial;">Frequency domain

yle="background-image: initial; background-position: initial; background-size: initial; background-repeat: initial; background-origin: initial; background-clip: initial;">Statistically (histogram, etc)

yle="background-image: initial; background-position: initial; background-size: initial; background-repeat: initial; background-origin: initial; background-clip: initial;">Time domain

yle="background-image: initial; background-position: initial; background-size: initial; background-repeat: initial; background-origin: initial; background-clip: initial;">Consistency of the results

yle="background-image: initial; background-position: initial; background-size: initial; background-repeat: initial; background-origin: initial; background-clip: initial;">Evaluate the estimation of the BER (bit error rate)

yle="background-image: initial; background-position: initial; background-size: initial; background-repeat: initial; background-origin: initial; background-clip: initial;">Identify the limitations of the dual-dirac model

yle="background-image: initial; background-position: initial; background-size: initial; background-repeat: initial; background-origin: initial; background-clip: initial;">Compare dual-dirac model results with a calculation based on the step response estimation

yle="background-image: initial; background-position: initial; background-size: initial; background-repeat: initial; background-origin: initial; background-clip: initial;">Generate new waveforms based on the analysis

yle="background-image: initial; background-position: initial; background-size: initial; background-repeat: initial; background-origin: initial; background-clip: initial;">Summarize findings

As the architecture of the 5G Core has already been standardized and it is fundamentally different from the previous generations, a question rises regarding the efficiency of the communication mechanisms that will be used for the communication between Network Functions (NFs) inside the 5G Core Network.
In this project, the student will evaluate these mechanisms used in an open-source implementation of the 5G Core (https://www.free5gc.org/), and propose improvements that will increase the performance and scalability of the Core Network (e.g., serialization, protocols, etc.).

• General knowledge about Mobile Networks (RAN & Core).
• Motivated to learn more about the communication side of the Mobile Core Networks.
• Strong programming skills. Knowledge of Go (https://golang.org/) is a plus.

endri.goshi@tum.de

3GPP has already released the 5G architecture overview, however there exists no actual open source deployment of RAN functionalities. This will be crucial towards the evaluation of the Core network both in terms of scalability and performance. In this thesis, the student shall understand the 5G standardization, especially the control plane communication between the RAN and 5G Core. Further, an initial RAN function compatible with the 5G standards shall be implemented and evaluation of control plane performance will be carried out. 

• Strong knowledge on programming languages Python, Go.
• Knowledge about mobile networking is necessary.
• Knowlegde about 4G/5G architecture is a plus.

The goal of this thesis is the classification of packet-level traces using Markov- and Hidden Markov Model. The scenario is open-world: Traffic of specific web applications should be distinguished from all possible web-pages (background traffic). In addition, several pages should be differentiated. Examples include: Google Maps, Youtube, Google Search, Facebook, Google Drive, Instagram, Amazon Store, Amazon Prime Video, etc.

This research internship looks at Quanktum Key Distribution exchange in a wide area pan-European network. Different architectures, routing and spectrum allocation methods need to be considered, keeping in mind both technological and economic constraints of such a combined deployment.

This work is helpful for Optical Networking as well as satellite network providers in order to provide secure data transmissions over large region multi-national governmental organizations, banks and security agencies.

In this internship/bachelor thesis, a student will research different lightpath reconfiguration algorithms models and their applications to flexible optical networking. Then, they will create an evaluation framework and finally simulate a network planning study.  The results will be investigated to draw useful conclusions.

Must Have

• Basic knowledge of graph theory, communication networks and optical networks
• Independent worker
• Working knowledge of Python
• Willingness to learn

Good to Have

• Knowledge of Java
• Familiarity with NetConf/YANG

To apply, please send your CV and grade transcripts to kireet.patri@tum.de

Flexibility is an indispensable feature of future communication networks and technologies. Only flexible networks allow coping with the fast-changing demands of future network applications and use cases like 5G/6G. In order to quantify the flexibility of networks, we have recently presented a new flexibility measurement framework. As many problems in network communication are studied on graphs, this thesis should investigate the impact of topologies on network flexibility by applying the concepts proposed in our framework. In detail, different networking use cases (like network programmability, network failures, and network verification) should be analyzed for a variety of network topologies. As graph measures are one way to characterize network graphs, the thesis should analyze the relation between graph features and network flexibility. It will be expected that the studies will be data-intensive; hence, the student should bring preliminaries in carrying out automated and data-intensive analysis. Finally, this thesis should study the predictability of flexibility given topologies. For this, it should apply supervised machine learning models to answer the question of whether we can predict the flexibility of given problems for specific networking problems.

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The architecture of 5G radio access networks features the division of the base station (gNodeB) into a centralized unit (CU) and a distributed unit (DU). This division enables cost reduction and better user experience via enhanced interference mitigation. Recent research proposes the posibility to modify this functional split dynamically, that is, to lively change the functions that run on the CU and DU. This has interesting implications at the network operation.

In this topic, the student will employ a dedicated simulator developed by LKN to characterize the duration and transition rates of each functional split under multiple variables: population density, mitigation capabilities, mobility, etc. This characterization may be used then on traffic models to predict the network behavior.

MATLAB, some experience with mobile networks and simulators

The Wireless Sensor Networks lab offers the opportunity to develop software solutions for the wireless sensor networking system, targeting innovative applications. For the next semester, a position is available to assist the participants in learning the programming environment and during the project development phase. The lab is planned to be held on-site every Tuesday and Thursday from 15:00 to 18:00.

Solid knowledge in Wireless Communication: PHY, MAC, and network layers. Solid programming skills: C/C++. Linux knowledge. Experience with embedded systems and microcontroller programming knowledge is preferable.

The Wireless Sensor Networks lab offers the opportunity to develop software solutions for the wireless sensor networking system, targeting innovative applications. For the next semester, a position is available to assist the participants in learning the programming environment and during the project development phase. The lab is planned to be held every Tuesday from 15:00 to 18:00.

Solid knowledge in Wireless Communication: PHY, MAC, and network layers. Solid programming skills: C/C++. Linux knowledge. Experience with embedded systems and microcontroller programming knowledge is preferable.

Future IoT will need wireless links with high data rates, low latency and reliable connectivity despite the limited radio spectrum. Connected lighting is an interesting infrastructure for IoT services because it enables visible light communication (VLC), i.e. a wireless communication using unlicensed light spectrum. This work will aim at developing a tool to perform an economic evaluation of the proposed solution in the particular case of a smart office.

For that purpose, the following tasks will have to be performed:

• Definition of a high-level framework specifying the different modules that will be implemented as well as the required inputs and the expected outputs of the tool.
• Development of a cost evaluation Excel-VBA tool. This tool will allow to evaluate different variations of the selected case study and if possible, to compare different alternative models (e.g., dimensioning) or scenarios (e.g., building types).

- Excel and VBA

Networked Control Systems, i. e. the interconnection of a control system over a communication network, are a fundamental building block of future industrial automation systems. To study NCS, the NCSbench platform [1,2] was developed allowing performance measurements of a real NCS. The platform is built using Lego, is developed in python, communicates over standard IP network interfaces and is fully open-source.

In order to further develop the platform, a working position is available.

[1] https://github.com/tum-lkn/NCSbench/wiki

[2] S. Zoppi, O. Ayan, F. Molinari; Z. Music, S. Gallenmüller, G. Carle, W. Kellerer, NCSbench: Reproducible Benchmarking Platform for Networked Control Systems. IEEE Consumer Communications & Networking Conference, 2020

This work will consist of a significant amount of programming and also of processing the measurement data.

Requirements:

• Good knowledge of wireless systems and protocols (WLAN, WSN).
• Basic knowledge of LTI control systems.
• Strong C and Python programming skills.
• Experience with Linux systems is recommended.
• Experience with python data processing tools is beneficial.

Network Function Virtualization (NFV) is becoming a promissing technology in modern networks. A challenging problem is determining the placement of Virtual Network Functions (VNFs). In this work, we plan to implement existing algorithms for embedding VNFs chains in NFV-enabled networks. 

Experience in Python or Java, object oriented programming

amir.varasteh@tum.de

The lecture Broadband Communication Networks (Prof. Wolfgang Kellerer) teaches network-related methods of mobile communication: WIFI, 2G to 5G cellular networks, etc. In order to bridge the gap between the methods and real life, innovative teaching concepts shall be developed in form of short podcasts where the students learn in short episodes about wireless communication and networking in day to day scenarios. In the podcasts the student should also be introduced to short exercises they can perform on their own.

In order to support designing these podcasts Pro. Kellerer is looking for a student experienced in programming and maybe in podcasts to help him.

Very good programming skills; experience with podcasts; experience with app programming (on android/ios)

The yle="color: #333333; font-family: Arial, sans-serif; font-size: 14px;">Software-Defined Networking (SDN) lab offers the opportunity to work with real hardware on interesting and entertaining projects related to the SDN network paradigm. For the next semester, a position is available to assist the teaching assistants for the lab (definition and preparation of the assignments, preparation of the hardware, etc.).

yle="list-style-type: square; margin-left: 0px; padding-left: 20px; color: #333333; font-family: Arial, sans-serif; font-size: 14px;">
• yle="padding-left: 0.3em;">Solid knowledge in computer networking (TCP/IP, SDN)
• yle="padding-left: 0.3em;">Solid knowledge of networking tools and Linux (iperf, ssh, etc)
• yle="padding-left: 0.3em;">Good programming skills: C/C++, Python