Topics (WS 22/23)

If you are interested to do your seminar on one of the topics offered by LKN, kindly contact the respective supervisor to show your interest (including the motivation to select this topic). If you reach an agreement with the respective supervisor before 20th October and the supervisor informs us, then the topic will be assigned to you. The remaining topics will be available for assignment based on a lottery system in the Kick-off meeting for the seminar on 21nd October, 2022. Only students with assigned topics will be accepted to our seminar.

List of Topics:

1) Semantic Communication: Feedback (Available)
Supervisor: Alexander Griessel (alexander.griessel@tum.de)
Description: Semantic Communication is considered a paradigm shift in communications. Rather than focus on the value of information in bits, semantic communication focuses on the value of information by the meaning
of the information encoded in bits. On a networking level, this introduces the problem of defining feedback mechanisms with difficult-to-quantify metrics.

References:

[1] Jincheng Dai, Ping Zhang, Kai Niu, Sixian Wang, Zhongwei Si, and Xiaoqi Qin. Semantic coded transmission: Architecture, methodology, and challenges. arXiv preprint arXiv:2112.03093, 2021.

[2] Peiwen Jiang, Chao-Kai Wen, Shi Jin, and Geoffrey Ye Li. Wireless semantic communications for video conferencing. arXiv preprint arXiv:2204.07790, 2022.

[3] Emilio Calvanese Strinati and Sergio Barbarossa. 6g networks: Beyond shannon towards semantic and goal-oriented communications. Computer Networks, 190:107930, 2021.

[4] Elif Uysal, Onur Kaya, Anthony Ephremides, James Gross, Marian Codreanu, Petar Popovski, Mohamad Assaad, Gianluigi Liva, Andrea Munari, Touraj Soleymani, et al. Semantic communications in networked systems. arXiv preprint arXiv:2103.05391, 2021.

2) Mobility-aware resource allocation and offloading decisions in a MEC-enabled 6G network (Available)
Supervisor: Alba Jano (alba.jano@tum.de)
Description: Mobile Edge Computing (MEC) enabled 6G network support low latency applications running in energy-constrained and computational limited devices, especially IoT devices. Using the task offloading concept, the devices offload the incoming tasks fully or partially to MEC depending on the device and network side's communication and computation resource availability. Since the 6G networks are oriented towards Digital Twin (DT) concept, the offloading decisions and allocation of resources is enhanced with the context awareness. As part of device context awareness, mobility plays an important role in affecting the decisions and the fulfillment of quality of service requirements. Even though most IoT devices are accounted for as static devices, there are use cases in NR-Light where devices obtain mobility.

In this topic, the student will focus on finding the relevant state of the art, comparing the used approaches and the achieved results, to conclude with a suitable solution for these types of devices.

References:

[1] Hu, H., Song, W., Wang, Q., Zhou, F., & Hu, R. Q. (2020, December). Mobility-aware offloading and resource allocation in MEC-enabled IoT networks. In 2020 16th International Conference on Mobility, Sensing and Networking (MSN) (pp. 554-560). IEEE.

[2] Jahandar, S., Kouhalvandi, L., Shayea, I., Ergen, M., Azmi, M. H., & Mohamad, H. (2022). Mobility-Aware Offloading Decision for Multi-Access Edge Computing in 5G Networks. Sensors, 22(7), 2692.

3) Techno-economic analysis of data centers (Assigned, Not Available!)
Supervisor: Shakthivelu Janardhanan (shakthivelu.janardhanan@tum.de)
Description: Data centers are the pillars of the Information Age. They are continuously evolving to suit the traffic demands of the world. With the meteoric rise in the number of data centers, several steps have been taken to reduce the cost of installation and operation of data centers. The tasks in this topic are as follows:

1. Identify how the cost of a data center is calculated.
2. Identify the most influential cost drivers.
3. Case study on the CAPEX of a data center

References:

[1] Patel, C.D. and Shah, A.J., 2005. Cost model for planning, development and operation of a data center. Hewlett-Packard Laboratories Technical Report, 107, pp.1-36.

[2] Reyes, R.R. and Bauschert, T., 2018, September. Infrastructure cost comparison of intra-data centre network architectures. In 2018 IEEE 29th Annual International Symposium on Personal, Indoor and Mobile Radio Communications (PIMRC) (pp. 1-7). IEEE.

4) Survivability in multi-domain optical networks (Assigned, not Available!)
Supervisor: Maria Samonaki (maria.samonaki@tum.de)
Description: Due to their high capacity, optical networks are vulnerable to the loss of large amounts of traffic caused by an unmanaged failure. Therefore, a significant amount of research activities focus on the survivability of such networks in general. In multi-domain networks, providing survivability becomes even more challenging; due to scalability and confidentiality issues, service providers are reluctant to exchange their domain-specific information regarding the original topology and available resources. Meanwhile, sufficient information is required to keep network activities running successfully in multi-domain applications. In the survivable routing problem, the objective is to find a pair of disjoint paths with minimum total cost, whereas in the case the two paths share common links or nodes, the objective can be to minimize the risk of simultaneous failure.

The goal of this topic is to provide an overview on how to approach survivable routing in multi-domain optical networks, and compare different methods in terms of cost and effectiveness.

References:
[1] Chengyi Gao, Hakki C. Cankaya, and Jason P. Jue. Survivable inter-domain routing based on topology aggregation with intra-domain disjointness information in multi-domain optical networks. Journal of Optical Communications and Networking, 6(7):619–628, 2014.

[2] Riti Gour, Jian Kong, Genya Ishigaki, Ashkan Yousefpour, Sangjin Hong, and Jason P. Jue. Survivable routing in multi-domain optical networks with geographically correlated failures. In GLOBECOM 2017 - 2017 IEEE Global Communications Conference, pages 1–6, 2017.

5) Transfer learning for multi-topology failure detection and identification in optical networks (Available)
Supervisor: Saquib Amjad (saquib.amjad@tum.de)
Description:Optical network reliability is an essential domain to ensure seamless and efficient communication. In this context, maintaining the quality-of-service and reliable operation can only be achieved with effective fault management. Machine Learning has emerged as a promising field for Optical network failure management (ONFM). In order to reduce retraining time and implementation of multiple topology dependent AI models, the authors in this paper use transfer learning as a medium. 

The goal of this seminar is to provide an overview of the emerging techniques, including transfer learning, for domain adaptation in soft failure management in optical networks.

References:
[1] Francesco Musumeci, Virajit Garbhapu Venkata, Yusuke Hirota, Yoshinari Awaji, Sugang Xu, Masaki Shiraiwa, Biswanath Mukherjee, and Massimo Tornatore. Domain adaptation and transfer learning for failure detection and failure-cause identification in optical networks across different lightpaths [invited]. Journal of Optical Communications and Networking, 14(2):A91–A100, 2022.

6) Availability analysis of Freespace Optical (FSO) Links for High-Throughput Satellite Communications (Available)
Supervisor: Mario Wenning (mario.wenning@tum.de)
Description: For increasing the coverage of access to the internet, satellite networks have recently gained attention. Progress in the field of adaptive optics potentially allows for high-throughput space-air-ground communications. However, the dependency on cloud conditions and atmospheric turbulences is high. Besides FSO links, radiofrequency-based (RF) connections can be potentially used for communication. RF links are more robust against weather changes and atmospheric turbulence, they provided the base for communication throughout the last years. Due to the longer presence, many ground stations are available and well distributed. The downside of this technology is that the data rates are lower by magnitude.

The goal of this seminar is to analyze state-of-the-art availability and throughput surveys based on FSO links. Additionally, different fallback options, e.g. multiple RF links, need to be considered to complete the view on possible technologies. The mapping of services and use cases suited to the analyzed infrastructure completes the survey.

References:
[1] Nicolas Perlot, Thomas Dreischer, Carl M. Weinert, and Josep Perdigues. Optical geo feeder link design. In 2012 Future Network Mobile Summit (FutureNetw), pages 1–8, 2012.

7) Control plane overload detection, mitigation and prevention mechanisms (Assigned, not Available!)
Supervisor: Cristian Bermudez Serna (cristian.bermudez-serna@tum.de)
Description: Software-Defined Networking (SDN) is a network paradigm where control and data planes are decoupled. The control plane consists on a controller, which manages network functionality and can be deployed in one or multiple servers. The data plane consists on forwarding devices which are instructed by the controller on how to forward traffic. SDN provides a mechanism to re-actively handle changes in the data plane, in which forwarding entities send unmanaged flow requests to the controller to decide on how to process them. However, SDN reactive configuration mechanism can expose the control plane to an overload situation, where a malicious/malfunctioning end-station sends a large amount of spoofed flow requests, and thus consume all processing resources in the control plane. Overloading the processing resources in the control plane of a SDN network can lead to an unforeseen behaviour in the data plane and a potential connection disruption.

The goal of this topic is to provide an overview on control plane overload detection, mitigation and prevention mechanisms. 
 

References:
[1] Tilman Wolf and Jingrui Li. Denial-of-service prevention for software-defined network controllers. In 2016 25th International Conference on Computer Communication and Networks (ICCCN), pages 1–10, 2016.

[2] Kuan-Yin Chen, Sen Liu, Yang Xu, Ishant Kumar Siddhrau, Siyu Zhou, Zehua Guo, and H. Jonathan Chao. Sdnshield: Nfv-based defense framework against ddos attacks on sdn control plane. IEEE/ACM Transactions on Networking, 30(1):1–17, 2022.

[3] Namita Ashodia and Kishan Makadiya. Detection and mitigation of ddos attack in software defined networking: A survey. In 2022 International Conference on Sustainable Computing and Data Communication Systems (ICSCDS), pages 1175–1180, 2022.