In the quest to bridge the digital divide, researchers Salah Abdeljabar, Marco Zennaro, and Mohamed-Slim Alouini have proposed an innovative solution that leverages existing public transportation systems to extend internet connectivity to rural areas. Abdeljabar is a researcher at the King Abdullah University of Science and Technology (KAUST), while Zennaro and Alouini are affiliated with the same institution, with Alouini serving as a professor of electrical and computer engineering. Their work, published in the journal IEEE Transactions on Mobile Computing, introduces a Delay Tolerant Networking (DTN) framework that utilizes informal public transport, such as minibus taxis, as mobile data mules to enhance connectivity in underserved regions.
The researchers developed a probabilistic model to capture the unpredictable nature of vehicle mobility, including travel times and contact durations at bus stops. This model is crucial for understanding how data can be effectively transmitted and relayed through these moving networks. The study focuses on key performance metrics, including the average data transmission rate and Peak Age of Information (PAoI), which measures how up-to-date the information is. An analytical approximation for the Mean PAoI (MPAoI) was derived and validated through simulations, providing a robust framework for evaluating the system’s performance.
Case studies from real-world datasets in Nouakchott, Accra, and Addis Ababa demonstrate the practical applicability and scalability of the proposed framework. The findings indicate that leveraging existing transportation networks can significantly bridge the digital divide by providing reliable internet-like connectivity to remote areas. This approach not only enhances connectivity but also offers a cost-effective solution by utilizing already existing infrastructure.
For the energy sector, this research highlights the potential for integrating communication networks with transportation systems to improve data transmission in remote areas. This can be particularly beneficial for monitoring and managing energy infrastructure in rural locations, where traditional internet connectivity is often limited. By utilizing mobile data mules, energy companies can ensure timely data collection and transmission, leading to more efficient and reliable energy distribution. Additionally, this framework can support smart grid applications, enabling better coordination and management of energy resources in underserved regions.
This article is based on research available at arXiv.