@inproceedings{Hofe2305:Circular,

title = {Circular Frame Buffer to Enhance Map Synchronization in Edge Assisted SLAM},

author = {Johannes {Hofer} and Peter {Sossalla} and Justus {Rischke} and Christian Leonard {Vielhaus} and Martin {Reisslein} and Frank H. P. {Fitzek}},

doi = {10.1109/ICC45041.2023.10278556},

year  = {2023},

date = {2023-05-28},

urldate = {2023-05-01},

booktitle = {International Conference on Communications (ICC)},

pages = {210-215},

publisher = {IEEE},

address = {Rome, Italy},

keywords = {},

pubstate = {published},

tppubtype = {inproceedings}

}

@inproceedings{Soss2301:Offloading,

title = {Offloading Visual SLAM Processing to the Edge: An Energy Perspective},

author = {Peter {Sossalla} and Johannes {Hofer} and Christian Leonard {Vielhaus} and Justus {Rischke} and Frank H. P. {Fitzek}},

doi = {10.1109/ICOIN56518.2023.10048921},

year  = {2023},

date = {2023-01-01},

urldate = {2023-01-01},

booktitle = {2023 International Conference on Information Networking (ICOIN) (ICOIN 

2023)},

address = {Bangkok, Thailand},

keywords = {},

pubstate = {published},

tppubtype = {inproceedings}

}

@inproceedings{Busch2023,

title = {Deep Reinforcement Learning for the Joint Control of Traffic Light Signaling and Vehicle Speed Advice},

author = {Johannes V. S. {Busch} and Robert {Voelckner} and Peter {Sossalla} and Christian Leonard {Vielhaus} and Roberto {Calandra} and Frank H. P. {Fitzek}},

year  = {2023},

date = {2023-01-01},

urldate = {2023-01-01},

journal = {IEEE International Conference on Machine Learning and Applications (ICMLA)},

publisher = {IEEE},

keywords = {},

pubstate = {published},

tppubtype = {inproceedings}

}

@inproceedings{jiajing2023HORA,

title = {HORA: Joint Handover and Resource Allocation on 3D Networks for Industrial IoT},

author = {Jiajing {Zhang} and Christian {Hartmann} and Peter {Sossalla} and Giang T. {Nguyen} and Frank H. P. {Fitzek}},

year  = {2023},

date = {2023-01-01},

urldate = {2023-01-01},

booktitle = {European Wireless (EW)},

address = {Rome, Italy},

keywords = {},

pubstate = {published},

tppubtype = {inproceedings}

}

@inproceedings{Soss2212:Optimizing,

title = {Optimizing Edge SLAM: Judicious Parameter Settings and Parallelized Map Updates},

author = {Peter {Sossalla} and Johannes {Hofer} and Justus {Rischke} and Johannes V. S. {Busch} and Giang T. {Nguyen} and Martin {Reisslein} and Frank H. P. {Fitzek}},

doi = {10.1109/GLOBECOM48099.2022.10001128},

year  = {2022},

date = {2022-12-01},

urldate = {2022-12-01},

booktitle = {2022 IEEE Global Communications Conference: IoT and Sensor Networks 

(Globecom 2022 IoTSN)},

address = {Rio de Janeiro, Brazil},

keywords = {},

pubstate = {published},

tppubtype = {inproceedings}

}

@inproceedings{Risc2211:Comparison,

title = {Comparison of UPF acceleration technologies and their tail-latency for URLLC},

author = {Justus {Rischke} and Christian Leonard {Vielhaus} and Peter {Sossalla} and Junyue {Wang} and Frank H. P. {Fitzek}},

doi = {10.1109/NFV-SDN56302.2022.9974798},

year  = {2022},

date = {2022-11-14},

urldate = {2022-11-14},

booktitle = {2022 IEEE Conference on Network Function Virtualization and Software 

Defined Networks (NFV-SDN) (NFV-SDN'22)},

address = {Phoenix, USA},

abstract = {The industry is striving to deploy private cellular networks in their 

factories. 

The envisioned use cases, such as industrial automation, require 

Ultra-Reliable and Low-Latency Communications (URLLC). 

In 5G, the User Plane Function (UPF) handles user traffic and hence 

significantly influences the performance in terms of latency and 

throughput. 

However, present UPFs are often user-space applications running on 

commercial off-the-shelf (COTS) servers introducing computational delays 

that follow long-tailed distributions. 

In this work, we compare modern packet processing acceleration technologies 

such as XDP, DPDK, and P4 and their respective tail-latency performance. 

Our results demonstrate the clear advantage of hardware-based P4 

implementations in terms of reduced tail-latency of about 6 μs at a 

percentile of 99.999% for small packets. 

Furthermore, we also demonstrate that software-based frameworks can compete 

with hardware-based approaches. 

For example, DPDK achieves tail-latencies of approximately 23 μs at a 

percentile of 99.999%. 

Based on our findings, we illustrate the trade-offs between low-cost 

software- and high-performant hardware-based packet processing systems.},

keywords = {},

pubstate = {published},

tppubtype = {inproceedings}

}

@inproceedings{Soss2206:5GMobile,

title = {Private 5G Solutions for Mobile Industrial Robots: A Feasibility Study},

author = {Peter {Sossalla} and Justus {Rischke} and Fabian {Baier} and Sebastian A. W. {Itting} and Giang T. {Nguyen} and Frank H. P. {Fitzek}},

doi = {10.1109/ISCC55528.2022.9912791},

year  = {2022},

date = {2022-10-19},

urldate = {2022-06-30},

booktitle = {27th IEEE Symposium on Computers and Communications (ISCC 2022)},

address = {Rhodes island, Greece},

abstract = {Mobile robots are an essential part of the vision of flexible production in a smart factory. To monitor and connect the robots, reliable and low latency communication is necessary. In this work, we conduct packet-based active measurements to evaluate the performance of a state-of-the-art 5G standalone system in a production environment. The focus is on whether 5G connections can meet the requirements specified by 3GPP in terms of delay and reliability. The results indicate that without cross-traffic, the requirement of a delay of less than 10 ms for 99.9 % of the packets can be met for the remote control and fleet management of mobile robots. However, as soon as cross-traffic is injected, especially in the uplink, the upper percentiles of the delay increase significantly, thus failing to hold the reliability requirements.},

keywords = {},

pubstate = {published},

tppubtype = {inproceedings}

}