@inproceedings{Viel2210:Handover,

title = {Handover Predictions as an Enabler for Anticipatory Service Adaptations in Next-Generation Cellular Networks},

author = {Christian Leonard {Vielhaus} and Johannes V. S. {Busch} and Philipp {Geuer} and Alexandros {Palaios} and Justus {Rischke} and Daniel Fabian {K\"{u}lzer} and Vincent {Latzko} and Frank H. P. {Fitzek}},

doi = {https://doi.org/10.1145/3551660.3560913},

year  = {2022},

date = {2022-10-24},

urldate = {2022-10-01},

booktitle = {The 20th ACM International Symposium on Mobility Management and Wireless 

Access (ACM MobiWac 2022)},

address = {Montreal, Canada},

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}

}

@inproceedings{Risc2206:Empirical,

title = {Empirical Study of 5G Downlink \& Uplink Scheduling and its Effects on Latency},

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

doi = {10.1109/WoWMoM54355.2022.00017},

year  = {2022},

date = {2022-06-14},

urldate = {2022-06-14},

booktitle = {2022 IEEE 23rd International Symposium on a World of Wireless, Mobile and 

Multimedia Networks (WoWMoM) (WoWMoM 2022)},

address = {Belfast, United Kingdom (Great Britain)},

abstract = {5G campus networks, whose advantages include 

flexible deployment, can be a promising candidate for production 

plants to complement existing Wifi-based networks. Toward 

that goal, 5G has to satisfy strict requirements about real-time 

communication to facility novel use cases. However, the realtime- 

capability of 5G is not well understood yet. In this work, we 

deliver insights into the functioning of 5G NR RAN Release 

15, which includes actual one-way delay and Round-Trip Time 

(RTT) measurements for Downlink and Uplink in a private 5G 

Standalone campus network. The extensive measurement results 

reveal that these delays are correlated, and the corresponding 

RTT, i.e. the sum of Downlink and Uplink delays, is discreetly 

clustered, ranging between 12ms and 40ms. The measurements 

also show that the distribution of RTTs is mainly dependent on 

the packet rates and their inter-arrival times. Our study helps 

expand the current understanding of 5G used for latency-critical 

applications. We make the code and the measurement data traces 

publicly available as the IEEE DataPort 5G Campus Networks: 

Measurement Traces dataset (DOI 10.21227/xe3c-e968).},

keywords = {},

pubstate = {published},

tppubtype = {inproceedings}

}

@inproceedings{Soss2201:OWD,

title = {Enhanced One-Way Delay Monitoring with OpenFlow},

author = {Peter {Sossalla} and Justus {Rischke} and Frank H. P. {Fitzek}},

doi = { 10.1109/ICOIN53446.2022.9687289},

year  = {2022},

date = {2022-01-12},

urldate = {2022-01-12},

booktitle = {2022 IEEE 36th International Conference on Information Networking (ICOIN 2022)},

address = {Jeju Island, Korea},

abstract = {Network monitoring is an important task in future networks to mitigate outages, guarantee low latency and high throughput, and quickly adapt to changes of network conditions. Software-Defined Networking (SDN) enables dynamic adaptation to changing network environments through the ability to program network behavior. However, to react properly to changing environments, precise and credible information about performance metrics such as latency is necessary. Recent research activities exploited OpenFlow, an SDN protocol, to measure delays inside the network, without the need for additional hard- or software. In this paper, we propose an improved method to measure one-way delays, which can handle asymmetrical delays between the SDN controller and the switches. We implemented our approach in a hardware testbed to evaluate it in a setup with asymmetrical delays and traffic loads. The results show that we are able to measure asymmetrical delays in the network. Additionally, the proposed solution is capable of discovering the network topology and therefore gives together with the performance metrics the information for efficient routing decisions. In addition, we make the source code of our implementation publicly available.},

keywords = {},

pubstate = {published},

tppubtype = {inproceedings}

}

@inproceedings{Sossalla2201:Offloading,

title = {Offloading Robot Control with 5G},

author = {Peter {Sossalla} and Justus {Rischke} and Giang T. {Nguyen} and Frank H. P. {Fitzek}},

doi = { 10.1109/CCNC49033.2022.9700709},

year  = {2022},

date = {2022-01-08},

urldate = {2022-01-08},

booktitle = {2022 IEEE 19th Annual Consumer Communications \& Networking Conference 

(CCNC) (CCNC 2022)},

address = {Las Vegas, USA},

abstract = {Simultaneous Localization and Mapping (SLAM), among other critical 

functions of mobile robots, such as navigation, are computationally 

expensive. When deployed at the robot, those functions demand high energy 

consumption and result in shorter operation time. Offloading SLAM to an 

Edge Cloud (EC) can significantly reduce the robot's computing demand and 

resources, subsequently reducing energy consumption. We offload 

intelligence of mobile robot control functionality, i.e., navigation, 

localization, and control to an EC. The EC processes sensor data and sends 

the robot the directional velocities. Meanwhile, a 5G wireless connection 

ensures the necessary low latencies and high throughputs. We demonstrate 

the feasibility of offloading SLAM and navigation in an EC based on a use 

case in automotive production. Additionally, we developed a digital twin of 

the robot and visualized its current sensor data.},

keywords = {},

pubstate = {published},

tppubtype = {inproceedings}

}

@inproceedings{Sossalla21:EdgeSLAM,

title = {Evaluating the Advantages of Remote SLAM on an Edge Cloud},

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

year  = {2021},

date = {2021-09-07},

booktitle = {2021 IEEE International Conference on Emerging Technologies and Factory Automation (ETFA 2021)},

keywords = {},

pubstate = {published},

tppubtype = {inproceedings}

}