A social cognitive heuristic for adaptive data dissemination in mobile Opportunistic Networks

Abstract

It is commonly agreed that data (and data-centric services) will be one of the cornerstones of Future Internet systems. In this context, mobile Opportunistic Networks (OppNets) are one of the key paradigms to e ciently support, in a self-organising and decentralised manner, the growth of data generated by localized interactions between users mobile devices, and between them and nearby smart devices such as IoT nodes. In OppNets scenarios, the spontaneus collaboration among mobile devices is exploited to disseminate data toward interested users. However, the limited resources and knowledge available at each node, and the vast amount of data available in the network, make it di cult to devise e cient schemes to accomplish this task. Recent solutions propose to equip each device with data filtering methods derived from human information processing schemes, known as Cognitive Heuristics. They are very e⇤ective methods used by human brains to quickly drop useless information and keep only the most relevant information. Altought cognitive-based OppNet solutions proved to be e cient (with limited overheads), they can become less e⇤ective when facing dynamic scenarios or situations where nodes cannot fully collaborate with each other, as we show in this paper. One of the reasons is that the solutions proposed so far do not take take into account the social structure of the environment where the nodes are moving in. In order to be more e⇤ective, the selection of information performed by each node should take into consideration not only the relevance of content for the local device, but also for other devices will encounter in the future due to mobility. To this end, in this paper we propose a social-based data dissemination scheme, based on a cognitive heuristic, known as the Social Circle Heuristic. This heuristic is an evaluation method that exploits the structure of the social environment to make inferences about the relevance of discovered information. We show how the Social Circle Heuristic, coupled with a cognitive-based community detection scheme, can be exploited to design an e⇤ective data dissemination algorithm for OppNets. We provide a detailed analysis of the performance of the proposed solution via simulation.

The Internet of People: A human and data-centric paradigm for the Next Generation Internet

“…Cognitive heuristics have also been applied to provide cost effective algorithms for solving several other problems emerging in the cyber-physical world. Cognitive heuristics and models of dynamic memory structures have been used in [M15] for crowdsourcing in smart city environments, while in [MPC17] the social circle heuristic [PRH05] is exploited to develop a dissemination policy for opportunistic networks where each node stores data items that are relevant for itself and for other nodes in its social context.…”

Modeling Human Behavior Part II -- Cognitive approaches and Uncertainty

“…Additionally, researchers have used heuristics to represent how information diffusion occurs in a network of individuals [4,11,[78][79][80].…”

Corpus for Development of Routing Algorithms in Opportunistic Networks

“…In environments where traditional networks do not perform well or, even worse, cannot operate, OppNets may provide a feasible solution for communication. Among the challenging environments, research highlights the following as areas where OppNets may perform well: Cellular network offloading [9], communication in challenged areas [9], censorship circumvention [10], mobile ad hoc social networks [2], offline social networks [2], Internet of Vehicles [11], information-centric networking [12], and proximity-based applications [2], among others.…”