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9 pages, 369 KB

Open AccessFeature PaperArticle

LTDA-MAC v2.0: Topology-Aware Unsynchronized Scheduling in Linear Multi-Hop UWA Networks

by Nils Morozs, Paul D. Mitchell and Yuriy Zakharov

Network 2021, 1(1), 2-10; https://doi.org/10.3390/network1010002 - 25 May 2021

Cited by 2 | Viewed by 3559

This paper investigates the use of underwater acoustic sensor networks (UASNs) for subsea asset monitoring. In particular, we focus on the use cases involving the deployment of networks with line topologies, e.g., for monitoring oil and gas pipelines. The Linear Transmit Delay Allocation MAC (LTDA-MAC) protocol facilitates efficient packet scheduling in linear UASNs without clock synchronization at the sensor nodes. It is based on the real-time optimization of a packet schedule for a given network deployment. In this paper, we present a novel greedy algorithm for real-time optimization of LTDA-MAC schedules. It produces collision-free schedules with significantly shorter frame duration, and is 2–3 orders of magnitude more computationally efficient than our previously proposed solution. Simulations of a subsea pipeline monitoring scenario show that, despite no clock synchronization, LTDA-MAC equipped with the proposed schedule optimization algorithm significantly outperforms Spatial TDMA. Full article

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25 pages, 360 KB

Open AccessArticle

Methods for Distributed Compressed Sensing

by Dennis Sundman, Saikat Chatterjee and Mikael Skoglund

J. Sens. Actuator Netw. 2014, 3(1), 1-25; https://doi.org/10.3390/jsan3010001 - 23 Dec 2013

Cited by 16 | Viewed by 7966

Abstract

Compressed sensing is a thriving research field covering a class of problems where a large sparse signal is reconstructed from a few random measurements. In the presence of several sensor nodes measuring correlated sparse signals, improvements in terms of recovery quality or the requirement for a fewer number of local measurements can be expected if the nodes cooperate. In this paper, we provide an overview of the current literature regarding distributed compressed sensing; in particular, we discuss aspects of network topologies, signal models and recovery algorithms. Full article

(This article belongs to the Special Issue Feature Papers)

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21 pages, 890 KB

Open AccessArticle

The Street Network Evolution of Crowdsourced Maps: OpenStreetMap in Germany 2007–2011

by Pascal Neis, Dennis Zielstra and Alexander Zipf

Future Internet 2012, 4(1), 1-21; https://doi.org/10.3390/fi4010001 - 29 Dec 2011

Cited by 233 | Viewed by 47917

Abstract

The OpenStreetMap (OSM) project is a prime example in the field of Volunteered Geographic Information (VGI). Worldwide, several hundred thousand people are currently contributing information to the “free” geodatabase. However, the data contributions show a geographically heterogeneous pattern around the globe. Germany counts as one of the most active countries in OSM; thus, the German street network has undergone an extensive development in recent years. The question that remains is this: How does the street network perform in a relative comparison with a commercial dataset? By means of a variety of studies, we show that the difference between the OSM street network for car navigation in Germany and a comparable proprietary dataset was only 9% in June 2011. The results of our analysis regarding the entire street network showed that OSM even exceeds the information provided by the proprietary dataset by 27%. Further analyses show on what scale errors can be reckoned with in the topology of the street network, and the completeness of turn restrictions and street name information. In addition to the analyses conducted over the past few years, projections have additionally been made about the point in time by which the OSM dataset for Germany can be considered “complete” in relative comparison to a commercial dataset. Full article

(This article belongs to the Special Issue NeoGeography and WikiPlanning)

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15 pages, 224 KB

Open AccessArticle

Symmetry in Complex Networks

by Angel Garrido

Symmetry 2011, 3(1), 1-15; https://doi.org/10.3390/sym3010001 - 10 Jan 2011

Cited by 23 | Viewed by 9389

Abstract

In this paper, we analyze a few interrelated concepts about graphs, such as their degree, entropy, or their symmetry/asymmetry levels. These concepts prove useful in the study of different types of Systems, and particularly, in the analysis of Complex Networks. A System can be defined as any set of components functioning together as a whole. A systemic point of view allows us to isolate a part of the world, and so, we can focus on those aspects that interact more closely than others. Network Science analyzes the interconnections among diverse networks from different domains: physics, engineering, biology, semantics, and so on. Current developments in the quantitative analysis of Complex Networks, based on graph theory, have been rapidly translated to studies of brain network organization. The brain's systems have complex network features—such as the small-world topology, highly connected hubs and modularity. These networks are not random. The topology of many different networks shows striking similarities, such as the scale-free structure, with the degree distribution following a Power Law. How can very different systems have the same underlying topological features? Modeling and characterizing these networks, looking for their governing laws, are the current lines of research. So, we will dedicate this Special Issue paper to show measures of symmetry in Complex Networks, and highlight their close relation with measures of information and entropy. Full article

(This article belongs to the Special Issue Symmetry Measures on Complex Networks)

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12 pages, 1657 KB

Open AccessReview

Functional Evolution of Bacterial Histone-Like HU Proteins

by Anne Grove

Curr. Issues Mol. Biol. 2011, 13(1), 1-12; https://doi.org/10.21775/cimb.013.001 - 20 May 2010

Cited by 10 | Viewed by 1651

Abstract

Bacterial histone-like HU proteins are critical to maintenance of the nucleoid structure. In addition, they participate in all DNA-dependent functions, including replication, repair, recombination and gene regulation. In these capacities, their function is typically architectural, inducing a specific DNA topology that promotes assembly of higher-order nucleo-protein structures. Although HU proteins are highly conserved, individual homologs have been shown to exhibit a wide range of different DNA binding specificities and affinities. The existence of such distinct specificities indicates functional evolution and predicts distinct in vivo roles. Emerging evidence suggests that HU proteins discriminate between DNA target sites based on intrinsic flexure, and that two primary features of protein binding contribute to target site selection: The extent to which protein-mediated DNA kinks are stabilized and a network of surface salt-bridges that modulate interaction between DNA flanking the kinks and the body of the protein. These features confer target site selection for a specific HU homolog, they suggest the ability of HU to induce different DNA structural deformations depending on substrate, and they explain the distinct binding properties characteristic of HU homologs. Further divergence is evidenced by the existence of HU homologs with an additional lysine-rich domain also found in eukaryotic histone H1. Full article

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