Using Social Information for Flow Allocation in MANETs

TL;DR

This paper proposes a novel flow allocation method in MANETs that leverages social and behavioral trust to improve network performance, especially under mobility, by using social relationship data to initialize trust metrics.

Contribution

The paper introduces a social trust-based framework for flow allocation in MANETs, combining social network data with behavioral observations for enhanced trust assessment.

Findings

Social trust improves detection rate and packet delivery ratio.

Social trust is crucial during node mobility.

Trust initialization from social data accelerates trust computation.

Abstract

Adhoc networks enable communication between distributed, mobile wireless nodes without any supporting infrastructure. In the absence of centralized control, such networks require node interaction, and are inherently based on cooperation between nodes. In this paper, we use social and behavioral trust of nodes to form a flow allocation optimization problem. We initialize trust using information gained from users' social relationships (from social networks) and update the trusts metric over time based on observed node behaviors. We conduct analysis of social trust using real data sets and used it as a parameter for performance evaluation of our frame work in ns-3. Based on our approach we obtain a significant improvement in both detection rate and packet delivery ratio using social trust information when compared to behavioral trust alone. Further, we observe that social trust is critical in the event of mobility and plays a crucial role in bootstrapping the computation of trust.