26 papers · ranked by Valyu relevance
Stuart Marsden, Jouko Vankka
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Jian Yuan, Kevin L. Mills
Simulating and understanding traffic dynamics in large networks are difficult and challenging due to the complexity of such networks and the limitations inherent in simulation modeling. Typically, simulation models used to study traffic dynamics include substantial detail representing protocol mechanisms across several…
Maciej Besta, Marcel Schneider, Salvatore Di Girolamo, Ankit Singla + 1 more
'Torsten Hoefler'] The growing size of data center and HPC networks pose unprecedented requirements on the scalability of simulation infrastructure. The ability to simulate such large-scale interconnects on a simple PC would facilitate research efforts. Unfortunately, as we first show in this work, existing…
Pablo Vera-Soto, Javier Villegas, Sergio Fortes, José Pulido + 3 more
Aircraft are composed of many electronic systems: sensors, displays, navigation equipment and communication elements. These elements require a reliable interconnection, which is a major challenge for communication networks as high reliability and predictability requirements must be verified for safe operation. In…
Lei Shi, Zhehao Li, Xiang Bi, Lulu Liao + 1 more
In wireless network communication, in-band full-duplex technique is a useful and important technique that can enlarge the whole throughput of the wireless networks. However, its use needs harsh environment. The successive interference cancellation can make several transmitters’ data be received simultaneously by the…
Laurynas Riliskis, Evgeny Osipov
Contemporary wireless sensor networks (WSNs) have evolved into large and complex systems and are one of the main technologies used in cyber-physical systems and the Internet of Things. Extensive research on WSNs has led to the development of diverse solutions at all levels of software architecture, including protocol…
Miquel Farreras, Jordi Paillissé, Lluís Fàbrega, Pere Vilà
This paper presents a comprehensive network slicing dataset designed to empower artificial intelligence (AI), and data-based performance prediction applications, in 5G and beyond (B5G) networks. The dataset, generated through a packet-level simulator, captures the complexities of network slicing considering the three…
Carlos Güemes-Palau, Miquel Ferriol-Galmés, Jordi Paillissé, Albert López-Brescó + 2 more
'Albert López-Brescó' 'Pere Barlet‐Ros' 'Albert Cabellos‐Aparicio'] Abstract—Network simulation is pivotal in network modeling, assisting with tasks ranging from capacity planning to performance estimation. Traditional approaches such as Discrete Event Simulation (DES) face limitations in terms of computational cost…
Khandaker Akramul Haque, Leen Al Homoud, Xin Zhuang, Mariam Elnour + 2 more
Topology-Informed Assessment of Power Grid Cyber Risk Authors: ['Khandaker Akramul Haque' 'Leen Al Homoud' 'Xin Zhuang' 'Mariam Elnour' 'Ana Goulart' 'Katherine Davis'] Abstract—The shift toward more renewable energy sources and distributed generation in smart grids has underscored the significance of modeling and…
Azra Seyyedi, Mahdi Bohlouli, SeyedEhsan Nedaaee Oskoee
High connectivity and robustness are essential in distributed networks, ensuring resilience, efficient communication, and adaptability. Optimizing energy consumption is also crucial for sustaining energy-constrained networks and extending their operational lifespan. In this study, we introduce an Artificial…
Maahiya Shaik, Sung Won Kim, Naveen Chilamkurti
With the essential increase in the use of wireless sensor networks, security is a major concern in every field. Intrusions have become frequent and present a significant challenge in today’s world. It is valuable to explore the feasibility of designing and rigorously assessing intrusion detection systems within network…
Carlos Güemes-Palau, Miquel Ferriol-Galmés, Paillisse-Vilanova, Jordi + 3 more
—Machine Learning (ML)-based network models provide fast and accurate predictions for complex network behaviors but require substantial training data. Collecting such data from real networks is often costly and limited, especially for critical scenarios like failures. As a result, researchers commonly rely on simulated…
Niema Moshiri, Manon Ragonnet-Cronin, Joel O. Wertheim, Siavash Mirarab
The ability to simulate epidemics as a function of model parameters allows insights that are unobtainable from real datasets. Further, reconstructing transmission networks for fast-evolving viruses like HIV may have the potential to greatly enhance epidemic intervention, but transmission network reconstruction methods…
Carlos Güemes-Palau, Miquel Ferriol-Galmés, Albert Cabellos‐Aparicio, Pere Barlet‐Ros
In recent years, network modeling has risen in prominence as one of the most active research fields related to computer networks. Correctly designed network models can be used to simulate network configurations without risk, as it does not involve using the actual network, and try out scenarios that may be too rare or…
Andrew Stokely, Lane Votapka, Marcus Hock, Abigail Teitgen + 3 more
We present the Netsci program - an open-source scientific software package that leverages GPU acceleration and a k-nearest-neighbor algorithm in order to estimate the mutual information (MI) between data in a set. The GPU acceleration presented here, as an improvement upon existing estimators, enables calculation…
Daniel Barter, Evan Walter Clark Spotte-Smith, Nikita S. Redkar, Shyam Dwaraknath + 2 more
Chemical reaction networks (CRNs) are powerful tools for obtaining mechanistic insight into complex reactive processes. However, they are limited in their applicability where reaction mechanisms are unintuitive, and products are unknown. Here we report new methods of CRN generation and analysis that overcome these…
Marcelo C. R. Melo, Rafael C. Bernardi, Cesar de la Fuente-Nunez, Zaida Luthey-Schulten
Molecular interactions are essential for regulation of cellular processes, from the formation of multiprotein complexes, to the allosteric activation of enzymes. Identifying the essential residues and molecular features that regulate such interactions is paramount for understanding the biochemical process in question…
Alexander P. Clark, Mukti Chowkwale, Alexander Paap, Stephen Dang + 1 more
Molecular signaling networks drive a diverse range of cellular decisions, including whether to proliferate, how and when to die, and many processes in between. Such networks often connect hundreds of proteins, genes, and processes. Understanding these complex networks is aided by computational modeling, but these tools…
Benjamin Ries, Richard J Gowers, James RB Eastwood, Irfan Alibay + 4 more
Alchemical free energy campaigns can be planned using graph theory by building up networks that contain nodes representing molecules that are connected by possible transformations as edges. We introduce Konnektor, an open-source Python package, for systematically planning, modifying, and analyzing free energy…
Jakub Kubečka, Daniel Ayoubi, Zeyuan Tang, Yosef Knattrup + 3 more
The computational cost of accurate quantum chemistry (QC) calculations of large molecular systems can often be unbearably high. Machine learning offers a lower computational cost compared to QC methods while maintaining their accuracy. In this study, we employ the polarizable atom interaction neural network (PaiNN)…
Zhen Cao, Huw A. Ogilvie, Luay Nakhleh
The development of statistical methods to infer species phylogenies with reticulation (species networks) has led to many discoveries of gene flow between distinct species. However, because the dimensionality of species networks is not fixed, these methods may compensate for kinds of model misspecification, such as…
Christos Mitsanis, Nicole Fortuna, Christine Beveridge, David Kainer
Mechanistic networks that encode causal regulatory logic can predict the effects of genetic and environmental perturbations but constructing them is a bottleneck in systems biology because the relevant knowledge lies scattered across thousands of resources, untapped for both building and validating such networks. Here…
Matthew Bailey, Mark Wilson
One of the critical tools of persistent homology is the persistence diagram. We demonstrate the applicability of a persistence diagram showing the existence of topological features (here rings in a 2D network) generated over time instead of space as a tool to analyse trajectories of biological networks. We show how the…
Authors not listed
Obtaining quantitative information about residence time behavior (i.e., the residence time distribution function) in realistic experimental systems is oftentimes experimentally challenging and numerically complex. The conventional way is to conduct very simple pulse or step tracer experiments or construct elaborate…
Song Liu, Peng Wei
In-band full-duplex communication has the potential to double the wireless channel capacity. However, how to efficiently transform the full-duplex gain at the physical layer into network throughput improvement is still a challenge, especially in dynamic communication environments. This paper presents a reinforcement…
Konstantinos Giannakis, Joanna M. Chustecki, Iain G. Johnston
Mitochondria in plant cells form strikingly dynamic populations of largely individual organelles. Each mitochondrion contains on average less than a full copy of the mitochondrial DNA (mtDNA) genome. Here, we asked whether mitochondrial dynamics may allow individual mitochondria to ‘collect’ a full copy of the mtDNA…