Clustering-based device-to-device discovery and content delivery in wireless networks

Device-to-device (D2D) cache placement and content delivery is a recent technology that exploits idle memory capacity of mobile devices and promises to fulfill users' content needs with very low delay and without using the scarce cellular network capacity. Recent literature on D2D caching mostly concentrated on optimal cache placement and mostly disregarded the required discovery mechanisms and the accompanying overhead. In this work we propose a clustering-based procedure that is used to cache content at the helper nodes along with advertisement and discovery procedures for content delivery. We implement a Long Term Evolution (LTE)-based simulation setup to evaluate the proposed schemes. Numerical results reveal that the clustering-based user and content discovery significantly improves cellular offloading and reduces the discovery overhead with a minimal sacrifice from delay.

Challenges in gene-oriented approaches for pangenome content discovery

Given a group of genomes, represented as the sets of genes that belong to them, the discovery of the pangenomic content is based on the search of genetic homology among the genes for clustering them into families. Thus, pangenomic analyses investigate the membership of the families to the given genomes. This approach is referred to as the gene-oriented approach in contrast to other definitions of the problem that takes into account different genomic features. In the past years, several tools have been developed to discover and analyse pangenomic contents. Because of the hardness of the problem, each tool applies a different strategy for discovering the pangenomic content. This results in a differentiation of the performance of each tool that depends on the composition of the input genomes. This review reports the main analysis instruments provided by the current state of the art tools for the discovery of pangenomic contents. Moreover, unlike previous works, the presented study compares pangenomic tools from a methodological perspective, analysing the causes that lead a given methodology to outperform other tools. The analysis is performed by taking into account different bacterial populations, which are synthetically generated by changing evolutionary parameters. The benchmarks used to compare the pangenomic tools, in addition to the computational pipeline developed for this purpose, are available at https://github.com/InfOmics/pangenes-review. Contact: V. Bonnici, R. Giugno Supplementary information: Supplementary data are available at Briefings in Bioinformatics online.

The appisation of television: TV apps, discoverability and the software, device and platform ecologies of the internet era

This article examines the appisation of television: the emergence of apps as a mainstream means of delivering television services/content through smart TVs, connected devices, smartphones and tablets. Exploring the interrelationships between TV content, discovery and aggregator apps, the article demonstrates how content/software providers, device manufacturers and infrastructural platforms vie to control our access to, and experience of, television in a market underpinned by datafication, commodification and selection. This control is enacted within a multidimensional software, device and platform ecology where discoverability is central because it determines which content, services and apps are most prominent, accessible and easy to find.