Simula Research Laboratory /
Center for Resilient Networks and Applications /
NorNet
Homepage of Thomas Dreibholz /
HiPerConTracer Homepage
HiPerConTracer
High-Performance Connectivity Tracer
Simula Research Laboratory /
Center for Resilient Networks and Applications /
NorNet
Homepage of Thomas Dreibholz /
HiPerConTracer Homepage
The new HiPerConTracer version 2.0.0 major release is now available!
After some significant delay, the new HiPerConTracer version 2.0 is soon to be released. The release candidate sources have just been merged into the master branch (from the version 2.0 branch dreibh/udpping), ready-to-use packages are available in the Ubuntu Launchpad and Fedora COPR PPAs! See the SoftCOM 2023 research paper and demo paper for details on the new features!
Looking for even more features? Take a look at the experimental version 3.0+ branch "TARTAN"!
Our new paper Β«Optimizing Network Latency: Unveiling the Impact of Reflection Server TuningΒ» with measurement results using the upcoming HiPerConTracer 2.0 (development branch "dreibh/udpping" in the HiPerConTracer Git repository) will be presented on April 18 at the 6th International Workshop on Recent Advances for Multi-Clouds and Mobile Edge Computing (M2EC 2024), to be held in conjunction with the 38th International Conference on Advanced Information Networking and Applications (AINA 2024) in Kitakyushu (εδΉε·εΈ), Japan! For more details, see the paper announcement here!
High-Performance Connectivity Tracer (HiPerConTracer) is a Ping/Traceroute measurement framework.
HiPerConTracer denotes the actual measurement tool. It performs regular Ping and Traceroute runs among sites, featuring:
Furthermore, the HiPerConTracer Framework provides additional tools for helping to obtain, process, collect, store, and retrieve measurement data:
The complete BibTeX references in a single file can be found here!
Dreibholz, Thomas: ``Cloud and Fog: How and Where is My Data Flowing? Obtaining Insights into Data Privacy in Today's Applications´´ (PDF, 14384 KiB, π¬π§), Invited Talk at Copenhagen Business School (CBS), Fredriksberg/Denmark, April 26, 2024, [BibTeX, XML].
Keywords: Cloud, Fog, Privacy, Networking, Routing, Traceroute, HiPerConTracer
Abstract: In today's applications, network access is almost ubiquitous: While users interact with their applications on the smartphone β anywhere and anytime β many tasks are actually offloaded to cloud/fog systems for processing somewhere else, mostly unknown by the users. So, a lot of user data continuously flows around the world, between cities, countries and continents. This talk intends to provide some interesting insights into privacy-relevant networking aspects of cloud/fog applications, without requiring detailed computer networking knowledge.
URL: https://web-backend.simula.no/sites/default/files/2024-04/CBSTalk2024.pdf
MD5: a1e26306386ce8ef176e278dfbcca44c
Evang, Jan Marius and Dreibholz, Thomas: ``Optimizing Network Latency: Unveiling the Impact of Reflection Server Tuning´´ (PDF, 422 KiB, π¬π§), in Proceedings of the 6th International Workshop on Recent Advances for Multi-Clouds and Mobile Edge Computing (M2EC) in conjunction with the 38th International Conference on Advanced Information Networking and Applications (AINA), pp. 374β384, DOI 10.1007/978-3-031-57942-4_3, ISBN 978-3-031-57942-4, Kitakyushu, Fukuoka/Japan, April 18, 2024, [BibTeX, XML].
Keywords: Latency, Kernel Tuning, HiPerConTracer
Abstract: This study investigates the dynamics of network latency optimizations, with a focus on the role of reflection server tuning. In an era marked by the demand for precise and low-latency network measurements, our exploration unveils the interplay of diverse parameters in achieving optimal performance. Notably, the implementation of a tuned profile on Linux emerges as a standout strategy, showcasing significant rewards in network efficiency. We highlight the importance of early acceptance of latency-critical traffic in the firewall chain and emphasize the cumulative impact of various optimizations. These findings have practical implications for network administrators and system architects, providing valuable insights for the deployment of efficient and low-latency network infrastructures, essential in the landscape of emerging technologies such as 5G networks and edge computing solutions.
URL: https://web-backend.simula.no/sites/default/files/2024-02/M2EC2024.pdf
MD5: b77b88c046472082a9fb635befcda1bd
Dreibholz, Thomas: ``A Live Demonstration of HiPerConTracer 2.0´´ (PDF, 1909 KiB, π¬π§), in Proceedings of the 31st International Conference on Software, Telecommunications and Computer Networks (SoftCOM), Split, Dalmacija/Croatia, September 22, 2023, [BibTeX, XML].
Keywords: Internet, Round-Trip Time, Traceroute, Measurement, Tools, HiPerConTracer
Abstract: HiPerConTracer is an open source tool for large-scale, long-term, high-frequency Ping and Traceroute measurements. Using such measurements, it is possible to obtain information about latency in the network, as well as about the actual routing. This proposed live demo provides an overview over the tool and its features, as well as an introduction of how to use it for performing measurements, storing the results, querying selected results, and post-processing them for visualisation.
URL: https://web-backend.simula.no/sites/default/files/2023-10/SoftCOM2023-Demo_0.pdf
MD5: ab326fd72248f5fcbeb717c5a7095283
Dreibholz, Thomas: ``High-Precision Round-Trip Time Measurements in the Internet with HiPerConTracer´´ (PDF, 12474 KiB, π¬π§), in Proceedings of the 31st International Conference on Software, Telecommunications and Computer Networks (SoftCOM), DOI 10.23919/SoftCOM58365.2023.10271612, ISBN 979-8-3503-0107-6, Split, Dalmacija/Croatia, September 22, 2023, [BibTeX, XML].
Keywords: Internet, Round-Trip Time, Packet Timestamping, Measurement, Tools, HiPerConTracer
Abstract: Accurately measuring Round-Trip Times (RTT) for Internet communications is important for various research topics, ranging from protocol performance and congestion control to routing and network security. Unix systems, particularly Linux and FreeBSD, provide some features to obtain network packet timing information, but there is a lack of documentation for these. With High-Performance Connectivity Tracer (HiPerConTracer), there is already an open source tool for running large-scale, long-running and high-frequency ICMP Ping and Traceroute measurements. However, it lacks support of high-precision timing. As part of this paper, first the network packet timestamping features of Unix systems are analysed and introduced, to provide the reader with a detailed overview over the available methods, their usage, as well as their limitations. Then, enhancements to HiPerConTracer are presented for adding high-precision timestamping support, as well as a UDP module to also perform UDP Ping and Traceroute measurements. Finally, the newly added features are demonstrated in a proof-of-concept analysis.
URL: https://web-backend.simula.no/sites/default/files/2023-10/SoftCOM2023-Timestamping.pdf
MD5: 99b0c36bb661d436dfc2c7fadc81c7d1
Mazumdar, Somnath and Dreibholz, Thomas: ``Towards a Privacy Preserving Data Flow Control via Packet Header Marking´´ (PDF, 2009 KiB, π¬π§), in Proceedings of the 24th IEEE International Conference on High Performance Computing, Data, and Analytics (HPCC), pp. 1509β1516, DOI 10.1109/HPCC-DSS-SmartCity-DependSys57074.2022.00232, ISBN 979-8-3503-1993-4, Chengdu, Sichuan/People's Republic of China, December 18, 2022, [BibTeX, XML].
Keywords: Cloud, Data, Fog, P4, Packets, Privacy, Routing
Abstract: Computing infrastructure is becoming ubiquitous thanks to the advancement in computing and the network domain. Reliable network communication is essential to offer good quality services, but it is not trivial. There are privacy concerns. Metadata may leak user information even if traffic is encrypted. Some countries have data privacy preserving-related regulations, but end-users cannot control through which path, networks, and hardware their data packets should travel. Even worse, the user cannot declare their privacy preferences. This paper presents an approach to tackle such privacy issues through data privacy-aware routing. The user can specify their preferences for packet routing using marking and filtering. Routing can work according to such specifications. It is implemented by P4, allowing a vendor-independent realisation with standard off-the-shelf hardware and open-source software components. We presented the initial experimental results of a proof-of-concept run on a unified cloud/fog research testbed.
URL: https://web-backend.simula.no/sites/default/files/publications/files/hpcc2022.pdf
MD5: e4736c18f80bee8084c75a587f6c7e0a
Mazumdar, Somnath and Dreibholz, Thomas: ``Secure Embedded Living: Towards a Self-contained User Data Preserving Framework´´ (PDF, 336 KiB, π¬π§), in IEEE Communications Magazine, vol. 60, pp. 74β80, DOI 10.1109/MCOM.001.2200165, ISSN 0163-6804, November 11, 2022, [BibTeX, XML].
Keywords: IoTs, Cloud, Blockchain, Data, Security, User
Abstract: Smart living represents the hardware-software co-inhabiting with humans for better living standards and improved well-being. Here, hardware monitors human activities (by collecting data) specific to a context. Such data can be processed to offer context-specific valuable insights. Such insights can be used for optimising the well-being, living experience and energy cost of smart homes. This paper proposes a Secure Embedded Living Framework (SELF) that enforces a privacy-preserving data control mechanism by integrating multiple technologies, such as Internet-of-thing, cloud/fog platform, machine learning and blockchain. The primary aim of the SELF is to allow the user to retain more control of its data.
URL: https://web-backend.simula.no/sites/default/files/publications/files/commmag2022.pdf
MD5: aee5a6a9043799f00b9836ce7cafd8d4
Dreibholz, Thomas and Mazumdar, Somnath: ``Find Out: How Do Your Data Packets Travel?´´ (PDF, 7239 KiB, π¬π§), in Proceedings of the 18th IEEE International Conference on Network and Service Management (CNSM), pp. 359β363, DOI 10.23919/CNSM55787.2022.9965091, ISBN 978-3-903176-51-5, Thessaloniki, Greece, November 1, 2022, [BibTeX, XML].
Keywords: Internet, Connectivity, Routing, Data, Packets, Traffic Paths
Abstract: In today's communication-centric world, users generate and exchange a massive amount of data. The Internet helps user data to travel from one part of the world to another, via a complex set of network systems. These systems are intelligent, heterogeneous, and non-transparent to users. This paper presents an extensive, trace-driven study of user data traffic covering five years of observations, six large ISPs, 22 different autonomous systems, and a total of 12 countries. This work aims to make users aware of how their data travels in the Internet, as the interests of ISPs majorly influence the data traffic path. Although data traffic should prefer to travel through countries that share land borders, we found that the shortest land distance between the two countries does not impact data path selection.
URL: https://web-backend.simula.no/sites/default/files/publications/files/cnsm2022.pdf
MD5: 1a49b8096e6f7d92d50d2ff98836db4c
Michelinakis, Foivos Ioannis; Pujol-Roig, Joan SebastiΓ ; Malacarne, Sara; Xie, Min; Dreibholz, Thomas; Majumdar, Sayantini; Poe, Wint Yi; Patounas, Georgios; Guerrero, Carmen; Elmokashfi, Ahmed Mustafa and Theodorou, Vasileios: ``AI Anomaly Detection for Cloudified Mobile Core Architectures´´ (PDF, 9658 KiB, π¬π§), in Transactions on Network and Service Management (TNSM), IEEE Computer Society, DOI 10.1109/TNSM.2022.3203246, ISSN 1932-4537, Los Alamitos, California/U.S.A., August 31, 2022, [BibTeX, XML].
Keywords: Anomaly Detection, Autoencoders, Deep Learning, 5G, AI, Smart Networks, Mobile Networks
Abstract: IT systems monitoring is a crucial process for managing and orchestrating network resources, allowing network providers to rapidly detect and react to most impediment causing network degradation. However, the high growth in size and complexity of current operational networks (2022) demands new solutions to process huge amounts of data (including alarms) reliably and swiftly. Further, as the network becomes progressively more virtualized, the hosting of nfv on cloud environments adds a magnitude of possible bottlenecks outside the control of the service owners. In this paper, we propose two deep learning anomaly detection solutions that leverage service exposure and apply it to automate the detection of service degradation and root cause discovery in a cloudified mobile network that is orchestrated by ETSI OSM. A testbed is built to validate these AI models. The testbed collects monitoring data from the OSM monitoring module, which is then exposed to the external AI anomaly detection modules, tuned to identify the anomalies and the network services causing them. The deep learning solutions are tested using various artificially induced bottlenecks. The AI solutions are shown to correctly detect anomalies and identify the network components involved in the bottlenecks, with certain limitations in a particular type of bottlenecks. A discussion of the right monitoring tools to identify concrete bottlenecks is provided.
URL: https://web-backend.simula.no/sites/default/files/publications/files/tnsm2022.pdf
MD5: 47e525a56f9c1cfd27c249601bdb8c3b
Dreibholz, Thomas: ``HiPerConTracer - A Versatile Tool for IP Connectivity Tracing in Multi-Path Setups´´ (PDF, 4898 KiB, π¬π§), in Proceedings of the 28th IEEE International Conference on Software, Telecommunications and Computer Networks (SoftCOM), pp. 1β6, DOI 10.23919/SoftCOM50211.2020.9238278, ISBN 978-953-290-099-6, Hvar, Dalmacija/Croatia, September 17, 2020, [BibTeX, XML].
Keywords: HiPerConTracer, Traceroute, Ping, Multi-Path Transport, NorNet, NorNet Core
Abstract: Nowadays, we see a steadily increasing number of Internet devices with connections to multiple networks. For example, every smartphone provides mobile broadband and Wi-Fi connectivity. Multi-path transport protocols, like MPTCP, CMT-SCTP or Multipath-QUIC, allow for utilising all connected networks simultaneously. However, while there is a lot of research on the Transport Layer aspects of multi-path transport, there is not much work on the Network Layer perspective, yet. In this paper, we introduce our Open Source tool HiPerConTracer (High-Performance Connectivity Tracer) for efficient, parallelised, long-term measurements of the path connectivity characteristics among multi-homed Internet systems. HiPerConTracer is now running as a permanent feature in the NorNet Core infrastructure, which is used for research on multi-homed systems, and in particular for research on multi-path transport. Based on the HiPerConTracer data collected in NorNet Core so far, we finally present some interesting results from the analysis of the inter-continental site connectivity between China and Norway in January 2020.
URL: https://web-backend.simula.no/sites/default/files/2024-06/SoftCOM2020-HiPerConTracer.pdf
MD5: 676791cf458caa2e9f21688227fc6219
Golkar, Forough; Dreibholz, Thomas and Kvalbein, Amund: ``Measuring and Comparing Internet Path Stability in IPv4 and IPv6´´ (PDF, 436 KiB, π¬π§), in Proceedings of the 5th IEEE International Conference on the Network of the Future (NoF), pp. 1β5, DOI 10.1109/NOF.2014.7119767, ISBN 978-1-4799-7531-0, Paris/France, December 4, 2014, [BibTeX, XML]. Awarded with the Best Paper Award.
Keywords: NorNet Core, Internet, IPv4, IPv6, Path Stability, Resilience, Robustness
Abstract: In just about 4 years, IPv6 will celebrate its 20th anniversary. While the protocol itself is already quite old, its deployment has only recently picked up speed. Not so many Internet service providers offer direct IPv6 connectivity to their customers, yet. Clearly, when IPv6 is available to customers, they expect that IPv6 offers at least the same β or even better β stability of connections in comparison to IPv4. The main goal of this paper is to investigate whether this is true today. In our paper, we present up-to-date measurement results on the stability of IPv4 and IPv6 paths in the real Internet, based on machines that are distributed over a large geographical area, as part of the NorNet Core testbed infrastructure for multi-homed systems. The measurements not only cover high-speed research networks, but also consumer-grade ADSL connections β i.e. the ISP connection types of "normal" end-users β as well as a broad range of different ISPs. The measurements show that IPv6 paths are less stable than corresponding IPv4 paths. We also find that the use of load balancing is more prevalent in IPv6 than in IPv4.
URL: https://web-backend.simula.no/sites/default/files/publications/Simula.simula.3048.pdf
MD5: e94bfd5f13ed1ab81ac86b90fc1bbfe1
Please use the issue tracker at https://github.com/dreibh/hipercontracer/issues to report bugs and issues!
For ready-to-install Ubuntu Linux packages of HiPerConTracer, see Launchpad PPA for Thomas Dreibholz!
sudo apt-add-repository -sy ppa:dreibh/ppa sudo apt-get update sudo apt-get install hipercontracer
For ready-to-install Fedora Linux packages of HiPerConTracer, see COPR PPA for Thomas Dreibholz!
sudo dnf copr enable -y dreibh/ppa sudo dnf install hipercontracer
For ready-to-install FreeBSD packages of HiPerConTracer, it is included in the ports collection, see FreeBSD ports tree index of benchmarks/hipercontracer/!
pkg install hipercontracer
Alternatively, to compile it from the ports sources:
cd /usr/ports/benchmarks/hipercontracer make make install
HiPerConTracer is released under the GNU General Public Licence (GPL).
Please use the issue tracker at https://github.com/dreibh/hipercontracer/issues to report bugs and issues!
The Git repository of the HiPerConTracer sources can be found at https://github.com/dreibh/hipercontracer:
git clone https://github.com/dreibh/hipercontracer cd hipercontracer cmake . make
Contributions:
Issue tracker: https://github.com/dreibh/hipercontracer/issues.
Please submit bug reports, issues, questions, etc. in the issue tracker!
Pull Requests for HiPerConTracer: https://github.com/dreibh/hipercontracer/pulls.
Your contributions to HiPerConTracer are always welcome!
CI build tests of HiPerConTracer: https://github.com/dreibh/hipercontracer/actions.
Coverity Scan analysis of HiPerConTracer: https://scan.coverity.com/projects/dreibh-hipercontracer.
The tarball has been signed with my GnuPG key 21412672518D8B2D1862EFEF5CD5D12AA0877B49. Its authenticity and integrity can be verified by:
gpg --keyserver hkp://keyserver.ubuntu.com --recv-keys 21412672518D8B2D1862EFEF5CD5D12AA0877B49 gpg --verify hipercontracer-<VERSION>.tar.xz.asc hipercontracer-<VERSION>.tar.xz
The tarballs have been signed with my GnuPG key 21412672518D8B2D1862EFEF5CD5D12AA0877B49. Its authenticity and integrity can be verified by:
gpg --keyserver hkp://keyserver.ubuntu.com --recv-keys 21412672518D8B2D1862EFEF5CD5D12AA0877B49 gpg --verify hipercontracer-<VERSION>.tar.xz.asc hipercontracer-<VERSION>.tar.xz
Β©οΈ 20.12.2024 Thomas Dreibholz, Simula Research Laboratory / Center for Resilient Networks and Applications / NorNet
