scispace - formally typeset
Search or ask a question
Author

József Bíró

Other affiliations: Nokia
Bio: József Bíró is an academic researcher from Budapest University of Technology and Economics. The author has contributed to research in topics: Quality of service & Generalized processor sharing. The author has an hindex of 12, co-authored 101 publications receiving 617 citations. Previous affiliations of József Bíró include Nokia.


Papers
More filters
Journal ArticleDOI
TL;DR: It is shown that minimalistic networks designed to maximize the navigation efficiency at minimal cost share basic structural properties with real networks and these skeletons are present in the Internet, metabolic, English word, US airport, Hungarian road networks, and in a structural network of the human brain.
Abstract: Connections in networks are organized to fulfil a function, and a common one is targeted transport or navigation. Here the authors use game theory to show how networks designed to maximize navigation efficiency at minimal cost share basic structural properties, which are also found in real cases.

71 citations

Proceedings ArticleDOI
08 Oct 2018
TL;DR: A stochastic model of geographically correlated link failures caused by disasters is built, in order to estimate the hazards a network may be prone to, and to understand the complex correlation between possible link failures.
Abstract: In order to evaluate the expected availability of a service, a network administrator should consider all possible failure scenarios under the specific service availability model stipulated in the corresponding service-level agreement. Given the increase in natural disasters and malicious attacks with geographically extensive impact, considering only independent single link failures is often insufficient. In this paper, we build a stochastic model of geographically correlated link failures caused by disasters, in order to estimate the hazards a network may be prone to, and to understand the complex correlation between possible link failures. With such a model, one can quickly extract information, such as the probability of an arbitrary set of links to fail simultaneously, the probability of two nodes to be disconnected, the probability of a path to survive a failure, etc. Furthermore, we introduce a pre-computation process, which enables us to succinctly represent the joint probability distribution of link failures. In particular, we generate, in polynomial time, a quasilinear-sized data structure, with which the joint failure probability of any set of links can be computed efficiently.

33 citations

Journal ArticleDOI
TL;DR: To the best of the knowledge, this is the first time that an algorithm is proposed, which is not only able to find a minimal representation in polynomial time, but also assures link weight integrality.
Abstract: Lately, it has been proposed to use shortest path first routing to implement Traffic Engineering in IP networks. The idea is to set the link weights so that the shortest paths, and the traffic thereof, follow the paths designated by the operator. Clearly, only certain shortest path representable path sets can be used in this setting, that is, paths which become shortest paths over some appropriately chosen positive, integer-valued link weights. Our main objective in this paper is to distill and unify the theory of shortest path representability under the umbrella of a novel flow-theoretic framework. In the first part of the paper, we introduce our framework and state a descriptive necessary and sufficient condition to characterize shortest path representable paths. Unfortunately, traditional methods to calculate the corresponding link weights usually produce a bunch of superfluous shortest paths, often leading to congestion along the unconsidered paths. Thus, the second part of the paper is devoted to reducing the number of paths in a representation to the bare minimum. To the best of our knowledge, this is the first time that an algorithm is proposed, which is not only able to find a minimal representation in polynomial time, but also assures link weight integrality. Moreover, we give a necessary and sufficient condition to the existence of a one-to-one mapping between a path set and its shortest path representation. However, as revealed by our simulation studies, this condition seems overly restrictive and instead, minimal representations prove much more beneficial.

32 citations

Journal ArticleDOI
TL;DR: In this paper, the authors revisited the idea of in-packet Bloom filters and source routing and built a Bloom filter by enclosing limited information about the structure of the tree.
Abstract: Large-scale information dissemination in multicast communications has been increasingly attracting attention, be it through uptake in new services or through recent research efforts. In these, the core issues are supporting increased forwarding speed, avoiding state in the forwarding elements, and scaling in terms of the multicast tree size. This paper addresses all these challenges---which are crucial for any scalable multicast scheme to be successful---by revisiting the idea of in-packet Bloom filters and source routing. As opposed to the traditional in-packet Bloom filter concept, we build our Bloom filter by enclosing limited information about the structure of the tree. Analytical investigation is conducted and approximation formulas are provided for optimal-length Bloom filters, in which we got rid of typical Bloom filter illnesses such as false-positive forwarding. These filters can be used in several multicast implementations, which are demonstrated through a prototype. Thorough simulations are conducted to demonstrate the scalability of the proposed Bloom filters compared to its counterparts.

32 citations

Proceedings ArticleDOI
01 Dec 2012
TL;DR: This paper revisits the idea of in-packet Bloom filters and source routing by enclosing limited information about the structure of the tree, namely its stage decomposition, which helps to get rid of typical Bloom filter illnesses as infinite loops and false positive forwarding.
Abstract: Large-scale information distribution has been increasingly attracting attention, be it through uptake in new services or through recent research efforts in fields like information-centric networking. The core issue to be addressed is the more efficient distribution of information to a large set of receivers. Avoiding state in the forwarding elements is crucial for any scheme to be successful. This paper addresses this challenge by revisiting the idea of in-packet Bloom filters and source routing. As opposed to the traditional in-packet Bloom filter concept which represent the trees flatly as sets, we build our filter by enclosing limited information about the structure of the tree, namely its stage decomposition, which helps to get rid of typical Bloom filter illnesses as infinite loops and false positive forwarding. Our analytical and simulation results show that by using this information we obtain more succinct tree representation while still maintaining forwarding efficiency.

29 citations


Cited by
More filters
Proceedings ArticleDOI
22 Jan 2006
TL;DR: Some of the major results in random graphs and some of the more challenging open problems are reviewed, including those related to the WWW.
Abstract: We will review some of the major results in random graphs and some of the more challenging open problems. We will cover algorithmic and structural questions. We will touch on newer models, including those related to the WWW.

7,116 citations

Journal ArticleDOI
Yu. A. Malkov1, D. A. Yashunin
TL;DR: Hierarchical Navigable Small World (HNSW) as mentioned in this paper is a fully graph-based approach for approximate K-nearest neighbor search without any need for additional search structures (typically used at the coarse search stage of most proximity graph techniques).
Abstract: We present a new approach for the approximate K-nearest neighbor search based on navigable small world graphs with controllable hierarchy (Hierarchical NSW, HNSW). The proposed solution is fully graph-based, without any need for additional search structures (typically used at the coarse search stage of the most proximity graph techniques). Hierarchical NSW incrementally builds a multi-layer structure consisting of a hierarchical set of proximity graphs (layers) for nested subsets of the stored elements. The maximum layer in which an element is present is selected randomly with an exponentially decaying probability distribution. This allows producing graphs similar to the previously studied Navigable Small World (NSW) structures while additionally having the links separated by their characteristic distance scales. Starting the search from the upper layer together with utilizing the scale separation boosts the performance compared to NSW and allows a logarithmic complexity scaling. Additional employment of a heuristic for selecting proximity graph neighbors significantly increases performance at high recall and in case of highly clustered data. Performance evaluation has demonstrated that the proposed general metric space search index is able to strongly outperform previous opensource state-of-the-art vector-only approaches. Similarity of the algorithm to the skip list structure allows straightforward balanced distributed implementation.

776 citations

Journal ArticleDOI
TL;DR: This Review surveys important aspects of communication dynamics in brain networks and proposes that communication dynamics may act as potential generative models of effective connectivity and can offer insight into the mechanisms by which brain networks transform and process information.
Abstract: Neuronal signalling and communication underpin virtually all aspects of brain activity and function. Network science approaches to modelling and analysing the dynamics of communication on networks have proved useful for simulating functional brain connectivity and predicting emergent network states. This Review surveys important aspects of communication dynamics in brain networks. We begin by sketching a conceptual framework that views communication dynamics as a necessary link between the empirical domains of structural and functional connectivity. We then consider how different local and global topological attributes of structural networks support potential patterns of network communication, and how the interactions between network topology and dynamic models can provide additional insights and constraints. We end by proposing that communication dynamics may act as potential generative models of effective connectivity and can offer insight into the mechanisms by which brain networks transform and process information.

592 citations

Journal ArticleDOI
TL;DR: It is highlighted by highlighting some possible future trends in the further development of weighted small-worldness as part of a deeper and broader understanding of the topology and the functional value of the strong and weak links between areas of mammalian cortex.
Abstract: It is nearly 20 years since the concept of a small-world network was first quantitatively defined, by a combination of high clustering and short path length; and about 10 years since this metric of complex network topology began to be widely applied to analysis of neuroimaging and other neuroscience data as part of the rapid growth of the new field of connectomics. Here, we review briefly the foundational concepts of graph theoretical estimation and generation of small-world networks. We take stock of some of the key developments in the field in the past decade and we consider in some detail the implications of recent studies using high-resolution tract-tracing methods to map the anatomical networks of the macaque and the mouse. In doing so, we draw attention to the important methodological distinction between topological analysis of binary or unweighted graphs, which have provided a popular but simple approach to brain network analysis in the past, and the topology of weighted graphs, which retain more b...

532 citations