Human-centric Data Dissemination in the IoP: Large-scale Modeling and Evaluation

TL;DR

This paper introduces a hybrid modeling approach to evaluate human cognitive-inspired data dissemination algorithms in large-scale IoP scenarios, demonstrating their effectiveness despite content heterogeneity.

Contribution

It presents a novel hybrid modeling methodology combining analytical and simulation models to assess cognitive data dissemination schemes at large scale.

Findings

Cognitive schemes remain effective in large-scale, heterogeneous environments.

Hybrid modeling enables scalable evaluation of data dissemination algorithms.

Results support the viability of human-centric data dissemination in IoP.

Abstract

Data management using Device-to-Device (D2D) communications and opportunistic networks (ONs) is one of the main focuses of human-centric pervasive Internet services. In the recently proposed "Internet of People" paradigm, accessing relevant data dynamically generated in the environment nearby is one of the key services. Moreover, personal mobile devices become proxies of their human users while exchanging data in the cyber world and, thus, largely use ONs and D2D communications for exchanging data directly. Recently, researchers have successfully demonstrated the viability of embedding human cognitive schemes in data dissemination algorithms for ONs. In this paper, we consider one such scheme based on the recognition heuristic, a human decision-making scheme used to efficiently assess the relevance of data. While initial evidence about its effectiveness is available, the evaluation of its behaviour in large-scale settings is still unsatisfactory. To overcome these limitations, we have developed a novel hybrid modelling methodology, which combines an analytical model of data dissemination within small-scale communities of mobile users, with detailed simulations of interactions between different communities. This methodology allows us to evaluate the algorithm in large-scale city- and country-wide scenarios. Results confirm the effectiveness of cognitive data dissemination schemes, even when content popularity is very heterogenous.