Network topology

About: Network topology is a research topic. Over the lifetime, 52259 publications have been published within this topic receiving 1006627 citations.

Interference-Aware Channel Assignment in Multi-Radio Wireless Mesh Networks

Abstract: The capacity problem in wireless mesh networks can be alleviated by equipping the mesh routers with multiple radios tuned to non-overlapping channels However, channel assignment presents a challenge because co-located wireless networks are likely to be tuned to the same channels The resulting increase in interference can adversely affect performance This paper presents an interference-aware channel assignment algorithm and protocol for multi-radio wireless mesh networks that address this interference problem The proposed solution intelligently assigns channels to radios to minimize interference within the mesh network and between the mesh network and co-located wireless networks It utilizes a novel interference estimation technique implemented at each mesh router An extension to the conflict graph model, the multi-radio conflict graph, is used to model the interference between the routers We demonstrate our solution’s practicality through the evaluation of a prototype implementation in a IEEE 80211 testbed We also report on an extensive evaluation via simulations In a sample multi-radio scenario, our solution yields performance gains in excess of 40% compared to a static assignment of channels

A Survey of Interconnection Networks

Abstract: Concurrent processing depends on interconnection networks for communication among processors and memory modules. Various network topologies and switching strategies are covered here.

ASCENT: Adaptive Self-Configuring sEnsor Network Topologies

Abstract: Advances in microsensor and radio technology enable small but smart sensors to be deployed for a wide range of environmental monitoring applications. The low-per node cost allows these wireless networks of sensors and actuators to be densely distributed. The nodes in these dense networks coordinate to perform the distributed sensing and actuation tasks. Moreover, as described in this paper, the nodes can also coordinate to exploit the redundancy provided by high density so as to extend overall system lifetime. The large number of nodes deployed in this systems preclude manual configuration, and the environmental dynamics precludes design-time preconfiguration. Therefore, nodes have to self-configure to establish a topology that provides communication under stringent energy constraints. ASCENT builds on the notion that, as density increases, only a subset of the nodes is necessary to establish a routing forwarding backbone. In ASCENT, each node assesses its connectivity and adapts its participation in the multihop network topology based on the measured operating region. This paper motivates and describes the ASCENT algorithm and presents analysis, simulation, and experimental measurements. We show that the system achieves linear increase in energy savings as a function of the density and the convergence time required in case of node failures while still providing adequate connectivity.

The effect of network topology on the spread of epidemics

Abstract: Many network phenomena are well modeled as spreads of epidemics through a network. Prominent examples include the spread of worms and email viruses, and, more generally, faults. Many types of information dissemination can also be modeled as spreads of epidemics. In this paper we address the question of what makes an epidemic either weak or potent. More precisely, we identify topological properties of the graph that determine the persistence of epidemics. In particular, we show that if the ratio of cure to infection rates is larger than the spectral radius of the graph, then the mean epidemic lifetime is of order log n, where n is the number of nodes. Conversely, if this ratio is smaller than a generalization of the isoperimetric constant of the graph, then the mean epidemic lifetime is of order e/sup na/, for a positive constant a. We apply these results to several network topologies including the hypercube, which is a representative connectivity graph for a distributed hash table, the complete graph, which is an important connectivity graph for BGP, and the power law graph, of which the AS-level Internet graph is a prime example. We also study the star topology and the Erdos-Renyi graph as their epidemic spreading behaviors determine the spreading behavior of power law graphs.

Network topology of the interbank market

Abstract: We provide an empirical analysis of the network structure of the Austrian interbank market based on Austrian Central Bank (OeNB) data. The interbank market is interpreted as a network where banks are nodes and the claims and liabilities between banks define the links. This allows us to apply methods from general network theory. We find that the degree distributions of the interbank network follow power laws. Given this result we discuss how the network structure affects the stability of the banking system with respect to the elimination of a node in the network, i.e. the default of a single bank. Further, the interbank liability network shows a community structure that exactly mirrors the regional and sectoral organization of the current Austrian banking system. The banking network has the typical structural features found in numerous other complex real-world networks: a low clustering coefficient and a short average path length. These empirical findings are in marked contrast to the network structures th...