Impact of Human Behavior on Social Opportunistic Forwarding

The current Internet design is not capable to support communications in environments characterized by very long delays and frequent network partitions. To allow devices to communicate in such environments, delay-tolerant networking solutions have been proposed by exploiting opportunistic message forwarding, with limited expectations of end-to-end connectivity and node resources. Such solutions envision non-traditional communication scenarios, such as disaster areas and development regions. Several forwarding algorithms have been investigated, aiming to offer the best trade-off between cost (number of message replicas) and rate of successful message delivery. Among such proposals, there has been an effort to employ social similarity inferred from user mobility patterns in opportunistic routing solutions to improve forwarding. However, these research effort presents two major limitations: first, it is focused on distribution of the intercontact time over the complete network structure, ignoring the impact that human behavior has on the dynamics of the network; and second, most of the proposed solutions look at challenging networking environments where networks have low density, ignoring the potential use of delay-tolerant networking to support low cost communications in networks with higher density, such as urban scenarios. This paper presents a study of the impact that human behavior has ∗This is the author’s pre-print version. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotion or for creating new collective works for resale or for redistribution to thirds must be obtained from the copyright owner. The camera-ready version of this work is being published at Elsevier Ad Hoc Networks, 2014 and is property of Elsevier B.V. Email address: [email protected] (Waldir Moreira) Preprint submitted to Ad Hoc Networks July 1, 2014 on opportunistic forwarding. Our goal is twofold: i) to show that performance in low and high density networks can be improved by taking the dynamics of the network into account; and ii) to show that the delay-tolerant networking can be used to reduce communication costs in networks with higher density by taking the behavior of the user into account.