The Emerging Scholarly Brain

It is now a commonplace observation that human society is becoming a coherent super-organism, and that the information infrastructure forms its emerging brain. Perhaps, as the underlying technologies are likely to become billions of times more powerful than those we have today, we could say that we are now building the lizard brain for the future organism.Comment: to appear in Future Professional Communication in Astronomy-II (FPCA-II) editors A. Heck and A. Accomazz

Keep it fresh: Reducing the age of information in V2X networks

The freshness of information is of the utmost importance in many contexts, including V2X networks and applications. One measure of this metric is the Age of Information (AoI), a notion recently introduced and explored by several authors, often with specific reference to vehicular networks. With this work, we explore the possibility of reducing the AoI of multi-hop information flooding in V2X networks exploiting the properties of the Eigenvector Centrality (EvC) of nodes in the topology, and the possibility that each node computes it exploiting only local information and very easy computations, so that each node can autonomously adapt its own networking parameters to redistribute information more efficiently. Starting from theoretical bounds and results, we explore how they hold in urban-constrained topologies and compare the AoI achieved exploiting EvC with the AoI achievable without this optimization of the nodes' behavior. Simulation results show a meaningful improvement without using additional resources and without the need of any global coordination

Infective flooding in low-duty-cycle networks, properties and bounds

Flooding information is an important function in many networking applications. In some networks, as wireless sensor networks or some ad-hoc networks it is so essential as to dominate the performance of the entire system. Exploiting some recent results based on the distributed computation of the eigenvector centrality of nodes in the network graph and classical dynamic diffusion models on graphs, this paper derives a novel theoretical framework for efficient resource allocation to flood information in mesh networks with low duty-cycling without the need to build a distribution tree or any other distribution overlay. Furthermore, the method requires only local computations based on each node neighborhood. The model provides lower and upper stochastic bounds on the flooding delay averages on all possible sources with high probability. We show that the lower bound is very close to the theoretical optimum. A simulation-based implementation allows the study of specific topologies and graph models as well as scheduling heuristics and packet losses. Simulation experiments show that simple protocols based on our resource allocation strategy can easily achieve results that are very close to the theoretical minimum obtained building optimized overlays on the network

Understanding information centric layer of adaptive collaborative caching framework in mobile disconnection-prone networks

Smart networks and services leverage in-network caching to improve transmission efficiency and support large amount of content sharing, decrease high operating costs and handle disconnections. In this paper, we investigate the complex challenges related to content popularity weighting process in collaborative caching algorithm in heterogeneous mobile disconnection prone environments. We describe a reputation-based popularity weighting mechanism built in information-centric layer of our adaptive collaborative caching framework CafRepCache which considers a realistic case where caching points gathering content popularity observed by nodes differentiates between them according to node's reputation and network's connectivity. We extensively evaluate CafRepCache with competitive protocols across three heterogeneous real-world mobility, connectivity traces and use YouTube dataset for different workload and content popularity patterns. We show that our collaborative caching mechanism CafRepCache balances the trade-off that achieves higher cache hit ratio, efficiency and success ratios while keeping lower delays, packet loss and caching footprint compared to competing protocols across three traces in the face of dynamic mobility of publishers and subscribers

Heterogeneous node responses to multi-type epidemics on networks

Having knowledge of the contact network over which an infection is spreading opens the possibility of making individualized predictions for the likelihood of different nodes to become infected. When multiple infective strains attempt to spread simultaneously we may further ask which strain, or strains, are most likely to infect a particular node. In this article we investigate the heterogeneity in likely outcomes for different nodes in two models of multi-type epidemic spreading processes. For models allowing co-infection we derive message-passing equations whose solution captures how the likelihood of a given node receiving a particular infection depends on both the position of the node in the network and the interaction between the infection types. For models of competing epidemics in which co-infection is impossible, a more complicated analysis leads to the simpler result that node vulnerability factorizes into a contribution from the network topology and a contribution from the infection parameters

@Houstonpolice: an exploratory case of Twitter during Hurricane Harvey

Abstract Purpose The purpose of this paper is to examine the Houston Police Department (HPD)’s public engagement efforts using Twitter during Hurricane Harvey, which was a large-scale urban crisis event. Design/methodology/approach This study harvested a corpus of over 13,000 tweets using Twitter’s streaming API, across three phases of the Hurricane Harvey event: preparedness, response and recovery. Both text and social network analysis (SNA) techniques were employed including word clouds, n-gram analysis and eigenvector centrality to analyze data. Findings Findings indicate that departmental tweets coalesced around topics of protocol, reassurance and community resilience. Twitter accounts of governmental agencies, such as regional police departments, local fire departments, municipal offices, and the personal accounts of city’s police and fire chiefs were the most influential actors during the period under review, and Twitter was leveraged as de facto a 9-1-1 dispatch. Practical implications Emergency management agencies should consider adopting a three-phase strategy to improve communication and narrowcast specific types of information corresponding to relevant periods of a crisis episode. Originality/value Previous studies on police agencies and social media have largely overlooked discrete periods, or phases, in crisis events. To address this gap, the current study leveraged text and SNA to investigate Twitter communications between HPD and the public. This analysis advances understanding of information flows on law enforcement social media networks during crisis and emergency events