It is commonly agreed that data (and data-centric services) will be one of the cornerstones of FutureInternet systems. In this context, mobile Opportunistic Networks (OppNets) are one of the key paradigms toefficiently support, in a self-organising and decentralised manner, the growth of data generated by localizedinteractions between users mobile devices, and between them and nearby smart devices such as IoT nodes.In OppNets scenarios, the spontaneous collaboration among mobile devices is exploited to disseminate datatoward interested users. However, the limited resources and knowledge available at each node, and the vastamount of data available in the network, make it dicult to devise effcient schemes to accomplish this task.Recent solutions propose to equip each device with data ltering methods derived from human informationprocessing schemes, known as Cognitive Heuristics. They are very effective methods used by human brainsto quickly drop useless information and keep only the most relevant information. Althought cognitive-basedOppNet solutions proved to be effcient (with limited overheads), they can become less effective when facingdynamic scenarios or situations where nodes cannot fully collaborate with each other, as we show in thispaper. One of the reasons is that the solutions proposed so far do not take take into account the socialstructure of the environment where the nodes are moving in. In order to be more effective, the selectionof information performed by each node should take into consideration not only the relevance of content forthe local device, but also for other devices will encounter in the future due to mobility. To this end, inthis paper we propose a social-based data dissemination scheme, based on a cognitive heuristic, known asthe Social Circle Heuristic. This heuristic is an evaluation method that exploits the structure of the socialenvironment to make inferences about the relevance of discovered information. We show how the SocialCircle Heuristic, coupled with a cognitive-based community detection scheme, can be exploited to design aneffective data dissemination algorithm for OppNets. We provide a detailed analysis of the performance ofthe proposed solution via simulation.

A Social Cognitive Heuristic for Adaptive Data Dissemination in Mobile Opportunistic Networks

M Mordacchini;A Passarella;M Conti
2017

Abstract

It is commonly agreed that data (and data-centric services) will be one of the cornerstones of FutureInternet systems. In this context, mobile Opportunistic Networks (OppNets) are one of the key paradigms toefficiently support, in a self-organising and decentralised manner, the growth of data generated by localizedinteractions between users mobile devices, and between them and nearby smart devices such as IoT nodes.In OppNets scenarios, the spontaneous collaboration among mobile devices is exploited to disseminate datatoward interested users. However, the limited resources and knowledge available at each node, and the vastamount of data available in the network, make it dicult to devise effcient schemes to accomplish this task.Recent solutions propose to equip each device with data ltering methods derived from human informationprocessing schemes, known as Cognitive Heuristics. They are very effective methods used by human brainsto quickly drop useless information and keep only the most relevant information. Althought cognitive-basedOppNet solutions proved to be effcient (with limited overheads), they can become less effective when facingdynamic scenarios or situations where nodes cannot fully collaborate with each other, as we show in thispaper. One of the reasons is that the solutions proposed so far do not take take into account the socialstructure of the environment where the nodes are moving in. In order to be more effective, the selectionof information performed by each node should take into consideration not only the relevance of content forthe local device, but also for other devices will encounter in the future due to mobility. To this end, inthis paper we propose a social-based data dissemination scheme, based on a cognitive heuristic, known asthe Social Circle Heuristic. This heuristic is an evaluation method that exploits the structure of the socialenvironment to make inferences about the relevance of discovered information. We show how the SocialCircle Heuristic, coupled with a cognitive-based community detection scheme, can be exploited to design aneffective data dissemination algorithm for OppNets. We provide a detailed analysis of the performance ofthe proposed solution via simulation.
2017
Istituto di informatica e telematica - IIT
Cognitive heuristics
Data Dissemination
Opportunistic Networks
Self-Organising
Social
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/20.500.14243/354220
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