Enhancing Marine Data Transmission with Socially-Aware Resilient Vessel Networks

TL;DR

This paper introduces a resilient vessel network that leverages social network analysis to improve marine data transmission, achieving lower costs and reliable delivery over opportunistic vessel-to-vessel connections.

Contribution

The paper proposes a novel community-based routing method using social network analysis to enhance marine data transmission in vessel networks.

Findings

Community-based routing reduces transmission costs

Achieves comparable delivery ratios to existing methods

Utilizes vessel interaction history for routing decisions

Abstract

With the multi-dimensional exploration towards oceans, enormous sensing data has been generated with significant volume, velocity, variety and heterogeneity. The resulted Big Marine Data (BMD) thus issue unprecedented architectural challenges on existing marine communication systems. Current dominant marine communication technologies, e.g., shore-based cellular stations, high frequency radio, and expensive satellites, extremely suffer from short coverage, low bandwidth, insecurity, and unavailable cross-domain transmission. In this paper, Resilient Vessel Network (RVN) is proposed to fundamentally enhance BMD transmission. RVNs with widespread self-organized vessels and opportunistic connections reveal advantages of ubiquity, resilience, low cost and cross-domain transmission. To efficiently manage opportunistic vessel-to-vessel (V2V) connections for optimal routing, Social Network Analysis (SNA) on historical vessel interactions is applied for vessel familiarity measurement and community detection. The performance of the proposed community-based routing (CBR) is comprehensively evaluated with real datasets of fishing vessel trajectories. It is demonstrated that CBR achieves much lower transmission cost with comparable delivery ratio compared to typical routing algorithms.