Evaluating the Impact of Scheduling Algorithms on Performance and Reliability in Delay-Tolerant Networks

Abstract

Delay-Tolerant Networks (DTNs) are designed to support communication in environments where network connectivity is intermittent and unpredictable. Efficient scheduling algorithms are critical for optimizing the network's performance, ensuring data delivery, and reducing latency. This paper provides an in-depth evaluation of two widely-used scheduling algorithms—the Timely-Throughput Optimal (TTO) Algorithm and the Bundle Lifetime Criteria-based policy. Using a comprehensive set of simulation experiments, we analyze how these algorithms perform under various network conditions, including mobility, node density, and varying traffic loads. Our results demonstrate that the TTO algorithm maximizes throughput and data delivery in stable networks, while the Bundle Lifetime Criteria-based policy significantly improves reliability in highly dynamic and mobile environments. The insights derived from this analysis are vital for designing adaptive scheduling solutions that enhance both performance and reliability in DTN applications such as disaster recovery, vehicular networks, and space communications.