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In this paper we propose a distributed algorithm for the estimation and control of the connectivity of ad-hoc networks in the presence of a random topology. First, given a generic random graph, we introduce a novel stochastic power…

Distributed, Parallel, and Cluster Computing · Computer Science 2015-06-17 Paolo Di Lorenzo , Sergio Barbarossa

A new vehicular traffic flow model based on a stochastic jump process in vehicle acceleration and braking is introduced. It is based on a master equation for the single car probability density in space, velocity and acceleration with an…

Other Condensed Matter · Physics 2009-11-10 K. Thomas Waldeer

This paper is a short summary of the main results in the thesis [1]. Based on the P2P paradigm we construct a stochastic model for a live media streaming content delivery network. Starting from the behavior of the out degree process of each…

Probability · Mathematics 2011-08-31 Andrea Monsellato

This work proposes to model the space environment as a stochastic dynamic network where each node is a group of objects of a given class, or species, and their relationship is represented by stochastic links. A set of stochastic dynamic…

Dynamical Systems · Mathematics 2025-05-23 Yirui Wang , Pietro De Marchi , Massimiliano Vasile

We consider transport over a strongly connected, directed graph. The scheduling amounts to selecting transition probabilities for a discrete-time Markov evolution which is designed to be consistent with certain initial and final marginals.…

Systems and Control · Computer Science 2016-03-29 Yongxin Chen , Tryphon T. Georgiou , Michele Pavon , Allen Tannenbaum

Foundation models have shown great promise in various fields of study. A potential application of such models is in computer network traffic analysis, where these models can grasp the complexities of network traffic dynamics and adapt to…

Machine Learning · Computer Science 2024-09-13 Louis Van Langendonck , Ismael Castell-Uroz , Pere Barlet-Ros

Transport systems on networks are crucial in various applications, but face a significant risk of being adversely affected by unforeseen circumstances such as disasters. The application of entropy-regularized optimal transport (OT) on graph…

Machine Learning · Computer Science 2025-05-07 Koshi Oishi , Yota Hashizume , Tomohiko Jimbo , Hirotaka Kaji , Kenji Kashima

We introduce a new framework for efficient sampling from complex probability distributions, using a combination of optimal transport maps and the Metropolis-Hastings rule. The core idea is to use continuous transportation to transform…

Computation · Statistics 2019-06-11 Matthew Parno , Youssef Marzouk

Previously, transport networks are usually treated as homogeneous networks, that is, every node has the same function, simultaneously providing and requiring resources. However, some real networks, such as power grid and supply chain…

Data Analysis, Statistics and Probability · Physics 2010-06-08 Yu-Han Chen , Bing-Hong Wang , Li-Chao Zhao , Changsong Zhou , Tao Zhou

We present a comparative study of the application of a recently introduced heuristic algorithm to the optimization of transport on three major types of complex networks. The algorithm balances network traffic iteratively by minimizing the…

Disordered Systems and Neural Networks · Physics 2007-07-12 Bogdan Danila , Yong Yu , John A. Marsh , Kevin E. Bassler

In order to maintain consistent quality of service, computer network engineers face the task of monitoring the traffic fluctuations on the individual links making up the network. However, due to resource constraints and limited access, it…

Applications · Statistics 2010-05-26 Joel Vaughan , Stilian A. Stoev , George Michailidis

Noise-assisted transport phenomena highlight the nontrivial interplay between environmental effects and quantum coherence in achieving maximal efficiency. Due to the complexity of biochemical systems and their environments, effective open…

This paper addresses the problem of estimating link flows in a road network by combining limited traffic volume and vehicle trajectory data. While traffic volume data from loop detectors have been the common data source for link flow…

Machine Learning · Computer Science 2022-06-28 Miner Zhong , Jiwon Kim , Zuduo Zheng

We consider the problem of routing in a mobile ad-hoc network (MANET) for which the planned mobilities of the nodes are partially known a priori and the nodes travel in groups. This situation arises commonly in military and emergency…

Networking and Internet Architecture · Computer Science 2017-05-25 Riten Gupta , Niyant Krishnamurthi , Uen-Tao Wang , Tejaswi Tamminedi , Mario Gerla

The ability to model and predict ego-vehicle's surrounding traffic is crucial for autonomous pilots and intelligent driver-assistance systems. Acceleration prediction is important as one of the major components of traffic prediction. This…

Machine Learning · Computer Science 2020-05-11 Jianyu Su , Peter A. Beling , Rui Guo , Kyungtae Han

An adaptive network model using SIS epidemic propagation with link-type dependent link activation and deletion is considered. Bifurcation analysis of the pairwise ODE approximation and the network-based stochastic simulation is carried out,…

Probability · Mathematics 2014-10-21 András Szabó-Solticzky , Luc Berthouze , Istvan Z. Kiss , Péter L. Simon

We consider a discrete-time model of continuous-time distributed optimization over dynamic directed-graphs (digraphs) with applications to distributed learning. Our optimization algorithm works over general strongly connected dynamic…

Optimization and Control · Mathematics 2024-03-27 Mohammadreza Doostmohammadian , Wei Jiang , Muwahida Liaquat , Alireza Aghasi , Houman Zarrabi

This paper presents a mesoscopic traffic flow model that explicitly describes the spatio-temporal evolution of the probability distributions of vehicle trajectories. The dynamics are represented by a sequence of factor graphs, which enable…

Machine Learning · Statistics 2019-09-25 Saif Eddin Jabari , Deepthi Mary Dilip , DianChao Lin , Bilal Thonnam Thodi

Research in transportation frequently involve modelling and predicting attributes of events that occur at regular intervals. The event could be arrival of a bus at a bus stop, the volume of a traffic at a particular point, the demand at a…

Machine Learning · Computer Science 2015-08-14 Narayanan U. Edakunni , Aditi Raghunathan , Abhishek Tripathi , John Handley , Fredric Roulland

The emergence of congestion is a critical phenomenon in transport systems. Transport is organized along pathways abstracted by links, which connect different nodes as regions to form the network. The modeling of traffic has so far mainly…

Physics and Society · Physics 2023-03-23 Zhidong He