Impact of Human Behavior on Social Opportunistic Forwarding

TL;DR

This paper investigates how human behavior influences social opportunistic forwarding, demonstrating that considering user dynamics can enhance performance in both low and high density networks, and reduce costs in urban scenarios.

Contribution

It highlights the importance of human behavior in designing effective opportunistic forwarding algorithms, addressing limitations of previous approaches that ignored user dynamics and network density.

Findings

Human behavior significantly impacts network dynamics.

Considering user mobility improves forwarding performance.

Delay-tolerant networking reduces costs in urban environments.

Abstract

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 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.