Publications by Patrick Thiran

Chat with Graph Search

Ask any question about EPFL courses, lectures, exercises, research, news, etc. or try the example questions below.

DISCLAIMER: The Graph Chatbot is not programmed to provide explicit or categorical answers to your questions. Rather, it transforms your questions into API requests that are distributed across the various IT services officially administered by EPFL. Its purpose is solely to collect and recommend relevant references to content that you can explore to help you answer your questions.

We consider the problem of jointly allocating chan- nel center frequencies and bandwidths for IEEE 802.11 wireless LANs (WLANs). The bandwidth used on a link affects sig- nificantly both the capacity experienced on this link and the interference produced o ...

Network Calculus is a set of recent developments, which provide a deep insight into flow problems encountered in networking. It can be viewed as the system theory that applies to computer networks. Contrary to traditional system theory, it relies on max-plus and min-plus algebra. In this paper, we show how a simple but important fixed-point theorem (residuation theorem in min-plus algebra) can be successfully applied to a number of problems in networking, such as window flow control, multimedia smoothing, a

We study the impact of interferences on the connectivity of large-scale ad-hoc networks, using percolation theory. We assume that a bi-directional connection can be set up between two nodes if the signal to noise ratio at reception is larger than some threshold. The noise is the sum of the contribution of interferences from all other nodes, weighted by a coefficient g, and of a background noise. We find that there is a critical value of g above which the network is made of disconnected clusters of nodes. We

Gossip algorithms have recently received significant attention, mainly because they constitute simple and robust algorithms for distributed information processing over networks. However for many topologies that are realistic for wireless ad-hoc and sensor networks (like grids and random geometric graphs), the standard nearest-neighbor gossip converges very slowly. A recently proposed algorithm called geographic gossip improves gossip efficiency by a

\sqrt{n / \log n}

factor for random geometric graphs, by

We are interested in inferring the set of waypoints (or intermediate destinations) of a mobility trajectory in the absence of timing information. We find that, by mining a dataset of real mobility traces, computing the entropy of conditional Markov traject ...

We study the connectivity and capacity of finite area ad hoc wireless networks, with an increasing number of nodes (dense networks). We find that the properties of the network strongly depend on the shape of the attenuation function. For power law attenuation functions, connectivity scales, and the available rate per node is known to decrease like 1/sqrt(n). On the contrary, if the attenuation function does not have a singularity at the origin and is uniformly bounded, we obtain bounds on the percolation do

Deep neural networks may easily memorize noisy labels present in real-world data, which degrades their ability to generalize. It is therefore important to track and evaluate the robustness of models against noisy label memorization. We propose a metric, ca ...

We consider a large-scale wireless network, but with a low density of nodes per unit area. Interferences are then less critical, contrary to connectivity. This paper studies the latter property for both a purely ad-hoc network and a hybrid network, where fixed base stations can be reached in multiple hops. We assume here that power constraints are modeled by a maximal distance above which two nodes are not (directly) connected. We find that the introduction of a sparse network of base stations does signific

Our goal is to design a traffic model for non congested IP backbone links, which is simple enough to be used in network operation, while being as general as possible. The proposed solution is to model the traffic at the flow level by a Poisson shot-noise process. In our model, a flow is a generic notion that must be able to capture the characteristics of any kind of data stream. We analyze the accuracy of the model with real traffic traces collected on the Sprint IP backbone network. Despite its simplicity,

Bayesian Optimization (BO) has proven to be very successful at optimizing a static, noisy, costly-to-evaluate black-box function f : S → R. However, optimizing a black-box which is also a function of time (i.e., a dynamic function) f : S ×T → R remains a challenge, since a dynamic Bayesian Optimization (DBO) algorithm has to keep track of the optimum over time. This changes the nature of the optimization problem in at least three aspects: (i) querying an arbitrary point in S × T is impossible, (ii) past obs

Monitoring systems that can detect path outages and periods of degraded performance are important for many distributed applications. Trivial pairwise probing systems do not scale well and cannot be employed in large networks. To build scalable path monitoring systems, two different approaches have been proposed in the literature. The first approach [1], which we call the continuous or analogue model, takes real measurement values and infers the performance metrics of unmeasured paths using traditional (+,)

Power-line communications are employed in home networking to provide easy and high-throughput connectivity. IEEE 1901, the MAC protocol for power-line networks, employs a CSMA/CA protocol similar to that of 802.11, but is substantially more complex, which ...

This testbed practice paper presents our efforts to validate an analytical model for fluid flow behavior in wireless mesh networks with an experimental evaluation. We have developed a fluid model for multihop communication in wireless mesh networks and ana ...

Power-line communications are employed in home networking to provide easy and high-throughput connectivity. The IEEE 1901, the MAC protocol for power-line networks, employs a CSMA/CA protocol similar to that of 802.11, but is substantially more complex, wh ...

Although recent works have brought some insights into the performance improvement of techniques used in state-of-the-art deep-learning models, more work is needed to understand their generalization properties. We shed light on this matter by linking the lo ...

We investigate, both theoretically and experimentally, the stability of CSMA-based wireless mesh networks, where a network is said to be stable if and only if the queue of each relay node remains (almost surely) finite. We identify two key factors that imp ...

Fault identification and location in optical networks is hampered by a multitude of factors: (i) the redundancy and the lack of coordination (internetworking) of the managements at the different layers (WDM, SDH/SONET, ATM, IP)

The present invention concerns a method for a communication device to transmit a data packet in a wireless communication system. The method comprises: determining (21) a first set of transmission parameters comprising a first central transmission frequency ...

Multivariate Hawkes processes (MHPs) are widely used in a variety of fields to model the occurrence of causally related discrete events in continuous time. Most state-of-the-art approaches address the problem of learning MHPs from perfect traces without no ...

Networks-on-chip provide an elegant framework to efficiently reuse predesigned cores. However, reuse of cores is jeopardized by new deep sub-micron noise effects that challenge the reliability of CMOS technology. Moreover, noise margins are further reduced as supply voltages scale down. We advocate that self-calibrating techniques will be needed to maintain an acceptable design trade-off between energy, performance, and reliability. As a result, self-calibrating techniques have to be integrated within netwo

Patrick Thiran

Chat with Graph Search

Distributed Spectrum Assignment for Home WLANs

Min-plus System Theory Applied to Communication Networks

Impact of Interferences on Connectivity in Ad Hoc Networks

Gossip along the way: order-optimal consensus through randomized path averaging

Traveling Salesman in Reverse: Conditional Markov Entropy for Trajectory Segmentation

Connectivity vs Capacity in Dense Ad Hoc Networks

Leveraging Unlabeled Data to Track Memorization

Connectivity in ad-hoc and hybrid networks

Modeling Internet backbone traffic at the flow level

This Too Shall Pass: Removing Stale Observations in Dynamic Bayesian Optimization

Binary Versus Analogue Path Monitoring in IP Networks

Analyzing and Boosting the Performance of Power-Line Communication Networks

Model validation through experimental testbed: the fluid flow behavior example

Analysis and Enhancement of CSMA/CA With Deferral in Power-Line Communications

Generalization Comparison of Deep Neural Networks via Output Sensitivity

Understanding and Tackling the Root Causes of Instability in Wireless Mesh Networks

An efficient algorithm for locating soft and hard failures in WDM networks

Csma/ca in time and frequency domains

Cumulants of Hawkes Processes are Robust to Observation Noise

Self-Calibrating Networks-On-Chip