Processing Priorization in the Medical Context
Beschreibung
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 applications. However, not only technical aspects will play a role for the priorization, but also ethical, i.e. in this case medical aspects. This is especially important, if applications are equally critical. For this, 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.
Voraussetzungen
Motivation, basic networking knowledge, basic programming knowledge
Kontakt
nicolai.kroeger@tum.de
Betreuer:
Mobility Management for Computation-Intensive Tasks in Cellular Networks with SD-RAN
Beschreibung
In the previous generations of cellular networks, both data plane and control plane operations were conducted jointly in Radio Access Networks (RANs). With the emergence of Software Defined Networks (SDNs), and their adaptation in RANs, known as SD-RAN, for the first time the separation of control from data plane operations became possible in 5G RAN, as a paradigm shift on how the assignment of network resources is handled in particular, and how cellular networks operate in general. The control is shifted to centralized units, which are known as SD-RAN controllers. This brings considerable benefits into the cellular network because it detaches the monolithic RAN control and enables co-operation among different RAN components, i.e., Base Stations (BSs), improving this way network performance along multiple dimensions. Depending on the current spread of users (UEs) across BSs, and their channel conditions for which UEs periodically update their serving BSs, and BSs forward that information to the SD-RAN controller, the latter can reallocate resources to BSs accordingly. BSs then perform the resource allocation across their corresponding UEs. Consequently, exploiting the wide network knowledge leads to an overall improved performance as it allows for optimal allocation decisions.
This increased level of flexibility, which arises from having a broader view of the network, can be exploited in improving the mobility management in cellular networks. This comes into play even more with 6G networks in which in-network computing is envisioned to be integral part. Namely, users will be sending computationally-intensive tasks to edge clouds (through their BSs) and would be waiting some results as a response. However, as it will take some time until these tasks are run on the cloud, the user might be changing the serving BS. As a result, handover will have to be managed. However, while the task is being uploaded, performing handovers would not be good as then the task would need to be sent to another edge cloud. Consequently, having a centralized knowledge of all the network (which the SD-RAN controller has), to avoid frequent handovers, the controller has an extra degree of freedom by increasing the number of frequency blocks that can be assigned to a user while uploading the task and while downloading results.
In this thesis the goal would be to increase the overall network utility by deciding which tasks to serve (each task has its own utility), given the limited network resources in terms of the upload bandwidth, download bandwidth, storage in edge clouds, and finite computational capacity. Users besides sending tasks and receiving results are assumed to run other applications, with given service requirements. The student will formulate optimization problems and solve them either analytically or using an optimization solver, like Gurobi, CVX, etc. The other task would be to conductt realistic simulations and showing the advantages the developed algorithms offer against benchmarks.
Voraussetzungen
Good knowledge of Python and interest to learn about mobility management in 5G
Betreuer:
Optimal resource allocation for utility maximization in 5G networks
Beschreibung
The slice dimensioning for the three types of traffic in 5G(eMBB, URLLC, and mMTC) would be the focus of this thesis. Each user, depending on the type of traffic, is characterized by a weight. This could be e.g., the gain of the operator by serving a given user. We assume that the more stringent the traffic requirement is, the higher the gain for the operator is. In this way, mMTC users weight would be the lowest, whereas the URRLC’s the highest. Also, users have different channel conditions, which needs to be taken into account. For each admitted user, the traffic requirement would have to be satisfied. The problem would then reduce to deciding what sizes of network slices are to be allocated to each service type, and the corresponding number of users within the slice, so that the utility for the operator is maximized.
Three policies are to be analyzed. The first is motivated by the finite number of PhysicalResource Blocks (PRBs) each cell has, so that a brute-force solution is found. The computational complexity of this policy has to be obtained as well. The second, less complex policy, is the one in which resources are reserved beforehand (i.e., it is a static policy), based depending on the ratio between the weight and the resources needed for a user of the given service type. Finally, the third policy, which would be based on a heuristic, would decide onthefly on how to dimension RAN slice sizes.
Voraussetzungen
A good knowledge of any programming language is required.
Kontakt
fidan.mehmeti@tum.de
Betreuer:
Enhanced Mobility Management in 5G Networks with SD-RAN
Beschreibung
In pre-5G networks, both the data plane and control plane operations were performed jointly in Radio Access Networks (RANs). With the emergence of Software Defined Networks (SDNs), and its adaptation in RANs, known as SD-RAN, for the first time the separation of control from data plane became possible 5G RAN, as a paradigm shift on how the assignment of network resources is handled in particular, and how cellular networks operate in general. The control is transferred to centralized units, which are known as SD-RAN controllers. This brings considerable benefits into the mobile network since it detaches the monolithic RAN control and enables co-operation among different RAN components, i.e., Base Stations (BSs), improving the network performance along several dimensions. To that end, depending on the current spread of the users (UEs) across BSs, and their channel conditions for which the UEs periodically update their serving BSs, and BSs send that information to the SD-RAN controller, the latter can reallocate resources to BSs accordingly. BSs then perform the resource allocation across their corresponding UEs. As a consequence, exploiting the wide network knowledge leads to an overall improved performance as it allows for optimal allocation decisions.
This increased level of flexibility, which arises from having a broader view of the network, can be exploited in improving the mobility management in cellular networks. In the previous generations of cellular networks, each BS has its own set of frequencies at which it could transmit. Given that each user would receive service by only one BS, depending on the channel conditions the users would have with the serving BS and the number of users within the same sell, the user would decide on whether she would need a handover or it would be better to remain within the same serving area (i.e., receiving service from the same BS) . Currently, conditional handovers are being the most serious candidate for 5G. However, every handover involves a considerable cost, due to the preparations that need to be performed to hand a user over from one BS to another one. These will unavoidably lead to reductions in data rates and network resources for other users. On the other hand, having a centralized knowledge of all the network (which the SD-RAN controller has), to avoid frequent handovers, the controller has an extra degree of freedom by increasing the number of frequency blocks that can be assigned to a user experiencing bad channel conditions. This of course depends on the topology of the users in that moment.
In this thesis, the focus will be on jointly deciding on the resource allocation policy for each user across the entire area of the controller and when to perform the handover in order to optimize different performance aspects (e.g., provide proportional fairness). To that end, the student will formulate optimization problems and solve them either analytically or using an optimization solver, like Gurobi, CVX, etc. The other part would be conducting realistic simulations and showing the advantages the developed algorithms offer against state of the art.
Voraussetzungen
Good knowledge of Python and interest to learn about mobility management in 5G
Betreuer:
Joint power and PRB allocation in SD-RAN environments in Beyond-5G networks
5G NR, SD-RAN, joint optimization
Beschreibung
In the previous generations of cellular networks, in Radio Access Networks (RANs) both the data plane and control plane operations were performed jointly. With the emergence of Software Defined Networks (SDNs), and its adaptation in RANs, known as SD-RAN, the separation of control from data plane became possible for the first time in RANs of 5G networks, as a paradigm shift on how the assignment of network resources is handled in particular, and how cellular networks operate in general. The control is transferred to centralized units known as SD-RAN controllers. This brings a lot of benefits into the mobile network since it detaches the monolithic RAN control and enables co-operation among RAN components, i.e., Base Stations (BSs), improving the network performance along different dimensions.
This increased level of flexibility arises from having a broader view of the network, which is provided by the centralized SD-RAN approach. In that way, depending on the current spread of the users (UEs) across BSs, and their channel conditions for which the UEs periodically update their serving BSs, and BSs send that information to the SD-RAN controller, the latter can reallocate resources to BSs accordingly. BSs then perform the resource allocation across their corresponding UEs. As a consequence, exploiting the wide network knowledge leads to an overall improved performance as it allows for optimal allocation decisions. As opposed to SD-RAN, in a classical RAN approach, each BS has its own fixed set of resources, and allocates them to the UEs within its operational area.
So far, the research in SD-RAN has focused only on allocating the resource blocks (i.e., frequencies) adaptively to the BSs. In this thesis, the focus will be on the joint allocation of both the resource blocks and transmission power to BSs within the area of the controller, in order to optimize different performance aspects. To that end, the student will formulate optimization problems and solve them either analytically or using an optimization solver, like Gurobi, CVX, etc. The other part would be conducting measurements for different allocation policies in OperAirInterface.
Voraussetzungen
- Good C/C++ experience
- Knowledge on OFDMA
Kontakt
serkut.ayvasik@tum.de
fidan.mehmeti@tum.de
Betreuer:
Optimally scheduling packets with MPTCP for Wireless Heterogeneous Networks
LiFi, Multipath, Optimization, Scheduling
Beschreibung
In order to fully utilize the capabilities of a LiFi-RF Heterogeneous network, the client devices should be capable of using multiple network interfaces simultaneously. Thanks to multipath solutions like MPTCP, this is possible.
The challenge in a MPTCP-enabled heterogeneous network lies in designing a policy to schedule data packets onto the multiple paths with heterogeneous characteristics (eg. delay, packet loss).
This work involves
- Designing an MPTCP scheduler that schedules packets optimally to minimize network delay and handle the dynamicity of heterogeneous links
- Implementing the scheduler in the Linux kernel
- Performing extensive evaluations with Mininet and hardware
Related Reading:Yang, Wenjun, et al. "Loss-aware throughput estimation scheduler for multi-path TCP in heterogeneous wireless networks." IEEE Transactions on Wireless Communications 20.5 (2021): 3336-3349.
If you are interested in this work, please send an email with a short introduction of yourself along with your CV and grade transcript.
Voraussetzungen
- Strong Python and C++ programming skills
- Experience with optimization problems
- Experience with Linux networking
Kontakt
hansini.vijayaraghavan@tum.de
Betreuer:
Learning to Proactively allocate Communication Resources
LiFi, Multipath, Reinforcement Learning, Task Offloading
Beschreibung
The goal of the thesis would be to build an Anticipatory or Proactive Wireless Resource Allocation Framework to optimize Multi-hop, Multi-path networks.
The approach is to develop an optimization problem to allocate network resources to users by looking into window of time in the future and to solve this problem using Reinforcement Learning.
By knowing the channel quality of the users in the future, a better, more optimal allocation of resources is made possible.
Related Reading:
Dastgheib, Mohammad Amir, et al. "Mobility-aware resource allocation in VLC networks using T-step look-ahead policy." Journal of Lightwave Technology 36.23 (2018): 5358-5370.
If you are interested in this work, please send me an email with a short introduction of yourself along with your CV and grade transcript.
Voraussetzungen
- Strong Python programming skills
- Strong foundation on wireless communications
- Experience with Reinforcement Learning
Kontakt
hansini.vijayaraghavan@tum.de
Betreuer:
Optimal and Proactive Communication Resource Allocation
LiFi, Multipath, Optimization, Task Offloading
Beschreibung
The goal of the thesis would be to build an Anticipatory or Proactive Wireless Resource Allocation Framework to optimize Multi-hop, Multi-path networks.
The approach is to develop and solve an optimization problem to allocate network resources to users by looking into window of time in the future. By knowing the channel quality of the users in the future, a better, more optimal allocation of resources is made possible.
Related Reading:
Dastgheib, Mohammad Amir, et al. "Mobility-aware resource allocation in VLC networks using T-step look-ahead policy." Journal of Lightwave Technology 36.23 (2018): 5358-5370.
If you are interested in this work, please send me an email with a short introduction of yourself along with your CV and grade transcript.
Voraussetzungen
- Strong Python programming skills
- Strong foundation on wireless communications
- Experience with optimization problems
Kontakt
hansini.vijayaraghavan@tum.de
Betreuer:
Modeling and implementing a simulator for multi-domain wireless networks
Beschreibung
Emerging applications such as telemedicine put stringent requirements on the underlying communication network. Furthermore, communication is expected to happen also across different domains. As this cannot be fulfilled easily and efficiently, the new communication network generation (6G) is currently being researched. 6G follows a holistic networking approach, i.e., not only across individual domains, but also across the entire network, with the focus to provide end-to-end performance guarantees. The overall network consists of several network types, different in the used devices and technologies (such as molecular networks, quantum networks, satellite networks, campus networks, etc.)
In order to develop new concepts and estimate their performance, it is essential to see practical results. However, obtaining measurement results from a complete testbed setup for every case is infeasible. In comparison, using a simulation allows to vary a broad variety of parameters such as the topology or device parameters and still achieve results in a reasonable amount of time. Another important aspect is performing analytic modeling.
The goal in this Master Thesis is to implement a packet-based simulator (preferably) in C/C++ and evaluate the functionality of multi-domain networks. Also, the achievable performance guarantees should be provided.
Betreuer:
Working Student for Testbed on 5G/6G RAN
Beschreibung
The results expected from this work are the enhancement of the 5G/6G tested setup with additional features on the Radio Access Network (RAN) and Core Network (CN). The work is focused on the OpenAirInterface (OAI) [1] platform, which forms the basis of the testbed setup. The expected outcome is to have improvements in wireless resource scheduling, focused on the uplink (UL), power management, and core network function management.
[1] N.Nikaein, M.K. Marina, S. Manickam, A.Dawson, R. Knopp and C.Bonnet, “OpenAirInterface: A flexible platform for 5G research,” ACM SIGCOMM Computer Communication Review, vol. 44, no. 5, 2014.
Voraussetzungen
- Good C/C++ experience
- Good Python knowledge
- RAN and CN architecture understanding is a plus
Kontakt
alba.jano@tum.de, yash.deshpande@tum.de
Betreuer:
Dimensioning a German Train IP-Optical Network with Integer Linear Programming
ILP, optical communicaitons
This thesis consists in modeling and solving the dimensioning problem for a train IP-Optical network using Integer Linear Programming (ILP).
Beschreibung
Background
Network operators are confronting continuously increasing QoS (Quality of Service) requirements. The need for Internet bandwidth and low latency is getting more demanding. Thus, network operators must make appropriate network equipment upgrades to serve the user traffic. A german train IP-Optical network faces similar challenges. The network operators of a railway company must stand up to the challenge of the rising traffic requested from the passengers. They must develop a mechanism to quantify the nature of the new needed equipment (i.e. dimensioning) while leveraging the current advances in the Coherent Pluggable Transceivers (CPT) modules.
Problem Description
In the context of this thesis, you are called to model and solve the dimensioning problem for a train IP-Optical network using Integer Linear Programming (ILP). More specifically, the thesis consists of the following steps:
- literature research on RMSA (Routing, Modulation and Spectrum Assignment) and CPT market
- adaptation of a given ILP model to the current scenario
- parametric study
- evaluation and visualization
Acquired Knowledge and Skills
In this thesis you will enrich your knowledge of IP-optical networks and ILP, a general methodology to find optimum solutions to linear problems. You will get an insight into core networking, network services, and modern challenges. Finally, you will learn how to run a parametric sweep simulation and evaluate the results.
Voraussetzungen
Basic knowledge in:
- Communication Networks Architecture and Design
- Programming Experience
- Julia Language
Kontakt
Please send your CV and transcript of records to:
- cristian.bermudez-serna@tum.de
- filippos.christou@ikr.uni-stuttgart.de
Betreuer:
Working Student for Network Delay Measurements
Beschreibung
Communication Networks must fulfill a strict set of requirements in the Industrial Area. The Networks must fulfill strict latency and bandwidth requirements to allow trouble-free operation. Typically, the industry relies on purpose build solutions that can satisfy the requirements.
Recently, the industry is moving towards using Ethernet-based Networks for their use case. This enables us to use common of the shelf hardware to communicate within the network. However, this hardware still will execute industrial applications and therefore has the same strict requirements as the network. In this project, we consider Linux-based hosts that run the industrial applications. We consider different networking hardware and configurations of the system to see how it affects performance. The goal is to investigate the overhead of the host.
Your tasks within the project are :
- Measure the Host Latency with different NICs
- Measure the Host Latency with different Hardware Offloads
- Tune, configure, and measure the Linux Scheduler to improve performance
You will gain:
- Experience with Networking Hardware
- Experience with Hardware Measurements
- Experience with Test Automation
Please send a short intro of yourself with your CV and transcript of records to us. We are looking forward to meeting you.
Voraussetzungen
- Familiarity with Linux Console
- Python
- C (not required, but a plus)
Kontakt
philip.diederich@tum.de
Betreuer:
Adaptive regenerator location selection in EON using reinforcement learning
Optical network planning, 3R regeneration, Reinforcement learning
Beschreibung
Elastic Optical Networks (EON) provide flexibility in bandwidth allocation, leading to improvement in spectrum utilization. The signal transmission capability is also improved, as lightpaths with better configurations of higher datarate and better modulation schemes can be deployed. The reach of the optical signal is controlled by the receivers' capability to receive the signal successfully, subjected to the received OSNR. This reach can be extended by using regeneration. Existing works use simple heuristics to find the locations for regeneration. The challenge is to update/ increase the regeneration locations based on the current network state. The optimal placement of regenerators and assignment of regeneration locations should aid in improving spectrum efficiency.
In this work, the student is expected to
- Designing and implementing an adaptive regeneration location selection algorithm, which considers the current network state, available spectrum, and available routing scenario, using reinforcement learning.
- Evaluating the performance of the algorithm in realistic topologies.
Interested students, please send an email with a short introduction of yourself along with your CV and grade transcript.
Voraussetzungen
- Strong Python and Java programming skills
- Experience in ML techniques (including reinforcement learning)
- Knowledge of optimization problems and classical methods is preferable
Kontakt
Saquib Amjad (saquib.amjad@tum.de)
Betreuer:
Working Student for the Implementation of a Medical Testbed
Communication networks, programming
Your goal is to implement a network for critical medical applications based on an existing open-access 5G networking framework as well as the adaptation of this network according to the needs of our research.
Beschreibung
Future medical applications put stringent requirements on the underlying communication networks in terms of highest availability, maximal throughput, minimal latency, etc. Thus, in the context of the 6G-life project, new networking concepts and solutions are being developed.
For the research of using 6G for medical applications, the communication and the medical side have joined forces: While researchers from the MITI group (Minimally invasive Interdisciplinary Therapeutical Intervention), located at the hospital "Rechts der Isar", focus on the requirements of the medical applications and collecting needed parameters of patients, it is the task of the researchers at LKN to optimize the network in order to satisfy the applications' demands. The goal of this joint research work is to have working testbeds for two medical testbeds located in the hospital to demonstrate the impact and benefits of future 6G networks and concepts for medical applications.
Your task during this work is to implement the communcation network for those testbeds. Based on an existing open-access 5G network implementation, you will implement changes according to the progress of the current research. The results of your work, working 6G medical testbeds, will enable researchers to validate their approaches with real-world measurements and allow to demonstrate future 6G concepts to research, industry and politics.
In this project, you will gain a deep insight into how communication networks, especially the Radio Access Network (RAN), work and how different aspects are implemented. Additionally, you will understand the current limitations and weaknesses as well as concepts for improvement. Also, you will get some insights into medical topics if interested. As in such a broad topic there are many open research questions, you additionally have the possibility to also write your thesis or complete an internship.
Voraussetzungen
- Most important: Motivation and willingness to learn unknown things.
- C/C++ and knowledge about how other programming languages work (Python, etc.) and/or the willingness to work oneself into such languages.
- Preferred: Knowledge about communication networks (exspecially the RAN), 5G concepts, the P4 language, SDN, Linux.
- Initiative to bring in own ideas and solutions.
- Ability to work with various partners (teamwork ability).
Please note: It is not necessary to know about every topic aforementioned, much more it is important to be willing to read oneself in.
Kontakt
Betreuer:
P4Update Improvement
Beschreibung
References:
[1] P4Update: Fast and Locally Verifiable Consistent Network Updates in the P4 Data Plane
Voraussetzungen
Kontakt
Zikai Zhou
Betreuer:
Intrusion Detection using Stochastic Block Models
communication networks ,machine learning, cyber security
Beschreibung
Communication networks are already key in the everyday life of most people. From social interaction to controlling vital infrastructure, communication networks constitute one of the enabling technologies for the modern world. But this importance comes with challenges. Among others, it makes communication networks the target of attacks. Such attacks can take a variety of forms. Two prominent examples are denial of service and the gain of unauthorized access to machines/data. To securely operate a communication network it is of great importance to detect and mitigate attacks as early as possible.
In this context, the proposed project focuses on the collection and analysis of network traffic. The gained insights should then be utilized to detect malicious behavior. As a first step, your task is to implement an environment where known attacks can be carried out in a secure and observable manner. This especially includes:
-
setup of virtual machines that can be used as a target.
-
setup of virtual machines with attack capabilities.
-
architecture for collecting ground-truth data during the attack phase.
As a second step, your task is to evaluate methods for identifying traffic patterns of different attacks. In this context, a special focus lies on the research question of how so-called Stochastic Block Models (SBMs) can be used to detect specific forms of attacks.
Within this project, you will gain a broad overview of network security, which is a valuable asset for your future career. You will help us to develop mitigation strategies and thus directly contribute towards the improvement of network security. Of course, it is possible to do a student thesis within the scope of this project.
Please send a short intro of yourself together with your CV and transcript of record to us. We are looking forward to meeting you.
Voraussetzungen
- Basic knowledge of Linux
- Basic Python programming skills
-
General understanding of communication networks (especially on packet level; protocols: IP, TCP/UDP)
Kontakt
maximilian.stephan@tum.de
Betreuer:
Design and evaluation of conditional device paging DRX
5G, IIoT, energy efficiency, DRX
Beschreibung
Energy Efficiency (EE) has become a key performance indicator for sustainable 5G networks due to the growth of next-generation mobile devices connected to the network and applications with the requirements to preserve energy resources. The relevance of EE increases for Industrial Internet of Things (IIoT) devices, which run on limited energy supported by the batteries not replaced over the lifetime.
Therefore, the development of methods to increase the energy efficiency on the device side has received the attention of academia and industry research. Reducing the continuous monitoring of the PDCCH channels is considered a key factor in increasing the device energy efficiency, especially considering the limited resources.
In this thesis, the student shall focus on the implementation and evaluation of a conditional device paging DRX mechanism to reduce the PDCCH channel monitoring. The mechanism will be evaluated through a 5G based simulator.
Voraussetzungen
- Good knowledge of Python and Matlab.
- Knowledge of mobile networks.