One of the aspects not covered by 5G networks are multi-domain networks, comprising one or more campus networks. There are private networks, including the Radio Access Network and Core Network, not owned by the cellular operators like within a university, hospital, etc. There will be scenarios in which the transmitter is within a different campus network from the receiver, and the data would have to traverse networks operated by different entities.

Given the different operators managing the “transmitter” and “receiver” networks, providing any end-to-end performance guarantees in terms of latency and reliability can pose significant challenges in multi-domain networks. For example, if there is a maximum latency that a packet can tolerate in the communication cycle between the transmitter and receiver, the former experiencing given channel conditions would require a given amount of RAN resources to meet that latency. The receiver, on the other end of the communication path, will most probably experience different channel conditions. Therefore, it will require a different amount of resources to satisfy the end-to-end latency requirement. Finding an optimal resource allocation approach across different networks that would lead to latency and reliability guarantees in a multi-domain network will be the topic of this thesis.     

The approach used to solve these problems will rely on queueing theory. A good knowledge of any programming language is required.

5G networks brought significant performance improvements for different service types like augmented reality, virtual reality, online gaming, live video streaming, robotic surgeries, etc., by providing higher throughput, lower latency, higher reliability as well as the possibility to successfully serve a large number of users. However, these improvements do not come without any costs. The main consequence of satisfying the stringent traffic requirements of the aforementioned applications is excessive energy consumption.

Therefore, making the cellular networks sustainable, i.e., constraining their power consumption, is of utmost importance in the next generation of cellular networks, i.e., 6G. This goal is of interest mostly to cellular network operators. Of course, while achieving network sustainability, the satisfaction of all traffic requirements, which is of interest to cellular users, must be ensured at all times. While these are opposing goals, a certain balance has to be achieved.

In this thesis, the focus is on the type of services known as eMBB (enhanced mobile broadband). These are services that are characterized as latency-tolerant to a certain extent, but sensitive to the throughput and its stability. Live video streaming is a use case falling into this category. For these applications, on the one side, higher data rates imply higher energy consumption. On the other side, the users can be satisfied with slightly lower throughput as long as the provided data rate is constant, which corresponds to the flexibility that the network operator can exploit. Hence, the question that needs to be answered in this thesis is what is the optimal trade-off between the data rate and the energy consumption in a cellular network with eMBB users? To answer this question, the entire communication process will be encompassed, i.e., from the transmitting user through the base station and core network to the receiving end. The student will need to formulate an optimization problem to address the related problem, which they will then solve through exact optimization solvers, but also through proposing simpler algorithms (heuristics) that reduce the solution time while not considerably deteriorating the system performance.

• Good knowledge of any programming language
• Good mathematical and analytical thinking skills
• High level of self-engagement and motivation

In future communication systems such as 6G, in-network computing will play a crucial role. In particular, processing units within the network enable to run applications such as digital twins close to the end user, leading to lower latencies and overall better performance.

 In this thesis, the task is to develop and evaluate an approach to dimension networking resources such as networking devices and processing units depending on the envisioned medical applications to be executed. This work is in cooperation with our partners at MITI (Hospital „Rechts der Isar“).

 The result will be an approach to dimension and plan networks for future medical applications. 

·       Motivation

·       Ideally some experience in optimization problems

·       Basic networking knowledge

·       Basic programming skills

In future communication systems such as 6G, in-network computing will play a crucial role. In particular, processing units within the network enable to run applications such as digital twins close to the end user, leading to lower latencies and overall better performance.

 In this thesis, the task is to develop and evaluate an approach to optimize the availability  of medical applications, i.e., modular application functions (MAFs), when executed in the network. For that, suitable real use cases are identified together with our partners at MITI (Hospital "Rechts der Isar"). The optimizing approach then leads to a specified distribution of the processing and networking resources, satisfying the minimum needs of critical applications while considering the needed availability.

 The result will be an evaluated placement approach for applications in the medical environment considering the availability.

·       Motivation

·       Ideally some experience in solving optimization problems

·       Basic networking knowledge

·       Basic programming skills

In future communication systems such as 6G, in-network computing will play a crucial role. In particular, processing units within the network enable to run applications such as digital twins close to the end user, leading to lower latencies and overall better performance.

 In this thesis, the task is to develop and evaluate an approach to minimize the power consumptions  of medical applications, i.e., modular application functions (MAFs), when executed in the network. For that, suitable real use cases are identified together with our partners at MITI (Hospital "Rechts der Isar"). The optimizing approach then leads to a specified distribution of the processing and networking resources, satisfying the minimum needs of critical applications while considering the power consumption.

 The result will be an evaluated power minimizing approach for applications in the medical environment.

·       Motivation

·       Ideally some experience in solving optimization problems

·       Basic networking knowledge

·       Basic programming skills

In future communication systems such as 6G, in-network computing will play a crucial role. In particular, processing units within the network enable to run applications such as digital twins close to the end user, leading to lower latencies and overall better performance.

 In this thesis, the task is to place medical applications, i.e., modular application functions (MAFs), in the networking considering various parameters similar to [1]. For that, suitable real use cases are identified together with our partners at MITI (Hospital "Rechts der Isar"). The optimizing approach then leads to a specified distribution of the processing and networking resources, considering various important parameters.

 The result will be an evaluated placement approach for applications in the medical environment.

[1] A. Hentati, A. Ebrahimzadeh, R. H. Glitho, F. Belqasmi and R. Mizouni, "Remote Robotic Surgery: Joint Placement and Scheduling of VNF-FGs," 2022 18th International Conference on Network and Service Management (CNSM), Thessaloniki, Greece, 2022, pp. 205-211, doi: 10.23919/CNSM55787.2022.9964591.

·       Motivation

·       Ideally some experience in solving optimization problems

·       Basic networking knowledge

·       Basic programming skills

In future communication systems such as 6G, in-network computing will play a crucial role. In particular, processing units within the network enable to run applications such as digital twins close to the end user, leading to lower latencies and overall better performance. However, these processing resources are usually shared among many applications, which potentially leads to worse performance in terms of execution time, throughput, etc. . This is especially critical for applications such as autonomous driving, telemedicine or smart operations. Hence, the processing of more critical applications must be prioritized.

 In this thesis, the task is to develop and evaluate a priorization approach for chains  of modular medical applications, i.e., modular application functions (MAFs). Hereby, this work extends an already existing work, focusing on the placement of only single MAFs with prioritization. In this work, suitable real use cases are identified together with our partners at MITI (Hospital "Rechts der Isar"). The priorization approach then leads to a specified distribution of the processing and networking resources, satisfying the minimum needs of critical applications.

 The result will be an evaluated priorization approach for applications in the medical environment.

·       Motivation

·       Ideally some experience in solving optimization problems

·       Basic networking knowledge

·       Basic programming skills