Publications

2024

1. Preprint

   Community Detection on Block Models with Geometric Kernels

   Konstantin Avrachenkov, B. R. Vinay Kumar, and Lasse Leskelä

   2024

   arXiv
2. Journal

   Spatial Queues with Nearest Neighbour Shifts

   B.R. Vinay Kumar, and Lasse Leskelä

   Performance Evaluation, Nov 2024

   Abs arXiv PDF

   This work studies queues in a Euclidean space. Consider N servers that are distributed uniformly in [0,1]d. Customers arrive at the servers according to independent stationary processes. Upon arrival, they probabilistically decide whether to join the queue they arrived at, or shift to one of the nearest neighbours. Such shifting strategies affect the load on the servers, and may cause some of the servers to become overloaded. We derive a law of large numbers and a central limit theorem for the fraction of overloaded servers in the system as the total number of servers N→∞. Additionally, in the one-dimensional case (d=1), we evaluate the expected fraction of overloaded servers for any finite N. Numerical experiments are provided to support our theoretical results. Typical applications of the results include electric vehicles queueing at charging stations, and queues in airports or supermarkets.

2023

1. Conference

   Spatial Queues with Nearest Neighbour Shifts

   B. R. Vinay Kumar

   In International Teletraffic Congress 35 (ITC 35), Turin, Italy, Oct 2023

   PDF
2. Journal

   An analysis of probabilistic forwarding of coded packets on random geometric graphs

   B. R. Vinay Kumar, Navin Kashyap, and D. Yogeshwaran

   Performance Evaluation, May 2023

   arXiv PDF
3. Conference

   Multilayer Hypergraph Clustering Using the Aggregate Similarity Matrix

   Kalle Alaluusua, Konstantin Avrachenkov, B. R. Vinay Kumar, and Lasse Leskelä

   In Algorithms and Models for the Web Graph, May 2023

   Abs arXiv

   We consider the community recovery problem on a multilayer variant of the hypergraph stochastic block model (HSBM). Each layer is associated with an independent realization of a d-uniform HSBM on N vertices. Given the similarity matrix containing the aggregated number of hyperedges incident to each pair of vertices, the goal is to obtain a partition of the N vertices into disjoint communities. In this work, we investigate a semidefinite programming (SDP) approach and obtain information–theoretic conditions on the model parameters that guarantee exact recovery both in the assortative and the disassortative cases.

2021

1. Conference

   An Analysis of Probabilistic Forwarding of Coded Packets on Random Geometric Graphs

   B.R. Vinay Kumar, Navin Kashyap, and D. Yogeshwaran

   In 19th International Symposium on Modeling and Optimization in Mobile, Ad hoc, and Wireless Networks, WiOpt 2021, Virtual Conference, Oct 2021

   PDF
2. Journal

   Probabilistic Forwarding of Coded Packets on Networks

   B. R. Vinay Kumar, and Navin Kashyap

   IEEE/ACM Transactions on Networking, Oct 2021

2019

1. Conference

   Probabilistic Forwarding of Coded Packets on Networks

   B. R. Vinay Kumar, and Navin Kashyap

   In 2019 IEEE International Symposium on Information Theory (ISIT), Jul 2019

   HTML

2018

1. Conference

   The Effect of Introducing Redundancy in a Probabilistic Forwarding Protocol

   B.R. Vinay Kumar, Navin Kashyap, and Roshan Antony

   In 2018 Twenty Fourth National Conference on Communications (NCC),, Jul 2018