Implementation and Deployment of a Distributed Network Topology Discovery Algorithm

In the past few years, the network measurement community has been interested in the problem of internet topology discovery using a large number (hundreds or thousands) of measurement monitors. The standard way to obtain information about the internet topology is to use the traceroute tool from a small number of monitors. Recent papers have made the case that increasing the number of monitors will give a more accurate view of the topology. However, scaling up the number of monitors is not a trivial process. Duplication of effort close to the monitors wastes time by reexploring well-known parts of the network, and close to destinations might appear to be a distributed denial-of-service (DDoS) attack as the probes converge from a set of sources towards a given destination. In prior work, authors of this report proposed Doubletree, an algorithm for cooperative topology discovery, that reduces the load on the network, i.e., router IP interfaces and end-hosts, while discovering almost as many nodes and links as standard approaches based on traceroute. This report presents our open-source and freely downloadable implementation of Doubletree in a tool we call traceroute@home. We describe the deployment and validation of traceroute@home on the PlanetLab testbed and we report on the lessons learned from this experience. We discuss how traceroute@home can be developed further and discuss ideas for future improvements

How Students Manage Peer Feedback Through a Collaborative Activity in a CS1 Course

[EN] In order to boost students’ motivation in practicing their problem-solving skills and give them opportunities to get feedback, we broke our CS1 course routine with a disruptive cross-skilling activity. It relies on collaboration between teams of students where peer feedback (using rubric) stands as the cornerstone to design and build a solution responding to a given problem.This paper aims at formally assessing the peer feedback process across three activity sessions. It also highlights the different success factors supporting peer feedback in that context through a cause and effect diagram. We show that peer feedback fosters primary problem-solving foundations. We also discuss its limitations, namely due to an insufficient granularity in the provided checklist as well as a lack of transversal skills from students, making them less comfortable with peer feedback. Although, by repeating the activity, students could manage it better and better and take more advantage of peer feedback.Brieven, G.; Leduc, L.; Donnet, B. (2023). How Students Manage Peer Feedback Through a Collaborative Activity in a CS1 Course. Editorial Universitat Politècnica de València. 211-219. https://doi.org/10.4995/HEAd23.2023.1614221121

Retouched Bloom Filters: Allowing Networked Applications to Flexibly Trade Off False Positives Against False Negatives

Where distributed agents must share voluminous set membership information, Bloom filters provide a compact, though lossy, way for them to do so. Numerous recent networking papers have examined the trade-offs between the bandwidth consumed by the transmission of Bloom filters, and the error rate, which takes the form of false positives, and which rises the more the filters are compressed. In this paper, we introduce the retouched Bloom filter (RBF), an extension that makes the Bloom filter more flexible by permitting the removal of selected false positives at the expense of generating random false negatives. We analytically show that RBFs created through a random process maintain an overall error rate, expressed as a combination of the false positive rate and the false negative rate, that is equal to the false positive rate of the corresponding Bloom filters. We further provide some simple heuristics and improved algorithms that decrease the false positive rate more than than the corresponding increase in the false negative rate, when creating RBFs. Finally, we demonstrate the advantages of an RBF over a Bloom filter in a distributed network topology measurement application, where information about large stop sets must be shared among route tracing monitors.Comment: This is a new version of the technical reports with improved algorithms and theorical analysis of algorithm

MSTG: A Flexible and Scalable Microservices Infrastructure Generator

The last few years in the software engineering field has seen a paradigm shift from monolithic application towards architectures in which the application is split in various smaller entities (i.e., microservices) fueled by the improved availability and ease of use of containers technologies such as Docker and Kubernetes. Those microservices communicate between each other using networking technologies in place of function calls in traditional monolithic software. In order to be able to evaluate the potential, the modularity, and the scalability of this new approach, many tools, such as microservices benchmarking, have been developed with that objective in mind. Unfortunately, many of these tend to focus only on the application layer while not taking the underlying networking infrastructure into consideration. In this paper, we introduce and evaluate the performance of a new modular and scalable tool, MicroServices Topology Generator (MSTG), that allows to simulate both the application and networking layers of a microservices architecture. Based on a topology described in YAML format, MSTG generates the configuration file(s) for deploying the architecture on either Docker Composer or Kubernetes. Furthermore, MSTG encompasses telemetry tools, such as Application Performance Monitoring (APM) relying on OpenTelemetry. This paper fully describes MSTG, evaluates its performance, and demonstrates its potential through several use cases

uTNT: Unikernels for Efficient and Flexible Internet Probing

The last twenty years have seen the development and popularity of network measurement infrastructures. Internet measurement platforms have become common and have demonstrated their relevance in Internet understanding and security observation. However, despite their popularity, those platforms lack of flexibility and reactivity, as they are usually used for longitudinal measurements. As a consequence, they may miss detecting events that are security or Internet-related. During the same period, operating systems have evolved to virtual machines (VMs) as self-contained units for running applications, with the recent rise of unikernels, ultra-lightweight VMs tailored for specific applications, eliminating the need for a host OS. In this paper, we advocate that measurement infrastructures could take advantage of unikernels to become more flexible and efficient. We propose uTNT, a proof-of-concept unikernel-based implementation of TNT, a traceroute extension able to reveal MPLS tunnels. This paper documents the full toolchain for porting TNT into a unikernel and evaluates uTNT performance with respect to more traditional approaches. The paper also discusses a use case in which uTNT could find a suitable usage. uTNT source code is publicly available on Gitlab.Comment: 10 pages, 11 figures, IFIP extended-abstrac

Path Similarity Evaluation using Bloom Filters

The performance of several Internet applications often relies on the measurability of path similarity between different participants. In particular, the performance of content distribution networks mainly relies on the awareness of content sources topology information. It is commonly admitted nowadays that, in order to ensure either path redundancy or efficient content replication, topological similarities between sources is evaluated by exchanging raw traceroute data, and by a hop by hop comparison of the IP topology observed from the sources to the several hundred or thousands of destinations. In this paper, based on real data we collected, we advocate that path similarity comparisons between different Internet entities can be much simplified using lossy coding techniques, such as Bloom filters, to exchange compressed topology information. The technique we introduce to evaluate path similarity enforces both scalability and data confidentiality while maintaining a high level of accuracy. In addition, we demonstrate that our technique is scalable as it requires a small amount of active probing and is not targets dependent

On the Quality of BGP Route Collectors for iBGP Policy Inference

peer reviewedA significant portion of what is known about Internet routing stems out from public BGP datasets. For this reason, numerous research efforts were devoted to (i) assessing the (in)completeness of the datasets, (ii) identifying biases in the dataset, and (iii) augmenting data quality by optimally placing new collectors. However, those studies focused on techniques to extract information about the AS-level Internet topology. In this paper, we show that considering different metrics influences the conclusions about biases and collector placement. Namely, we compare AS-level topology discovery with \iac inference. We find that the same datasets exhibit significantly diverse biases for these two metrics. For example, the sensitivity to the number and position of collectors is noticeably different. Moreover, for both metrics, the marginal utility of adding a new collector is strongly localized with respect to the proximity of the collector. Our results suggest that the ``optimal'' position for new collectors can only be defined with respect to a specific metric, hence posing a fundamental trade-off for maximizing the utility of extensions to the BGP data collection infrastructure

Increasing the Coverage of a Cooperative Internet Topology Discovery Algorithm

peer reviewedRecently, Doubletree, a cooperative algorithm for large-scale topology discovery at the IP level, was introduced. Compared to classic probing systems, Doubletree discovers almost as many nodes and links while strongly reducing the quantity of probes sent. This paper examines the problem of the nodes and links missed by Doubletree. In particular, this paper's first contribution is to carefully describe properties of the nodes and links that Doubletree fails to discover. We explain incomplete coverage as a consequence of the way Doubletree models the network: a tree-like structure of routes. But routes do not strictly form trees, due to load balancing and routing changes. This paper's second contribution is the Windowed Doubletree algorithm, which increases Doubletree's coverage up to 16% without increasing its load. Compared to classic Doubletree, Windowed Doubletree does not start probing at a fixed hop distance from each monitor, but randomly picks a value from a range of possible values

Revealing Middlebox Interference with Tracebox

peer reviewedMiddleboxes such as firewalls, NAT, proxies, or Deep Packet Inspection play an increasingly important role in various types of IP networks, including enterprise and cellular networks. Recent studies have shed the light on their impact on real traffic and the complexity of managing them. Network operators and researchers have few tools to understand the impact of those boxes on any path. In this paper, we propose tracebox, an extension to the widely used traceroute tool, that is capable of detecting various types of middlebox interference over almost any path. tracebox sends IP packets containing TCP segments with different TTL values and analyses the packet encapsulated in the returned ICMP message. Further, as recent routers quote, in the ICMP message, the entire IP packet that they received, \tracebox is able to detect any modification performed by upstream middleboxes. In addition, tracebox can often pinpoint the network hop where the middlebox interference occurs. We evaluate tracebox with measurements performed on PlanetLab nodes. Our analysis reveals various types of middleboxes that were not expected on such an experimental testbed supposed to be connected to the Internet without any restriction