Tekin, NazliDedeturk, Bilge KaganGungor, Vehbi Cagri2025-09-252025-09-2520241389-12861872-7069https://doi.org/10.1016/j.comnet.2024.110778https://hdl.handle.net/20.500.12573/4122Tekin, Nazli/0000-0002-4275-8544Recently, with the advancement of Internet of Things (IoT) technology, IoT-enabled Smart Grid (SG) applications have gained tremendous popularity. Ensuring reliable communication in IoT-based SG applications is challenging due to the harsh channel environment often encountered in the power grid. Error Control (EC) techniques have emerged as a promising solution to enhance reliability. Nevertheless, ensuring network reliability requires a substantial amount of energy consumption. In this paper, we formulate a Mixed Integer Programming (MIP) model which considers the energy dissipation of EC techniques to maximize IoT network lifetime while ensuring the desired level of IoT network reliability. We develop meta-heuristic approaches such as Artificial Bee Colony (ABC) and Particle Swarm Optimization (PSO) to address the high computation complexity of large-scale IoT networks. Performance evaluations indicate that the EC-Node strategy, where each IoT node employs the most energy-efficient EC technique, yields a minimum of 8.9% extended lifetimes compared to the EC-Net strategies, where all IoT nodes employ the same EC method for a communication. Moreover, the PSO algorithm reduces the computational time by 77% while exhibiting a 2.69% network lifetime decrease compared to the optimal solution.eninfo:eu-repo/semantics/closedAccessInternet of ThingsError ControlSmart GridNetwork LifetimeArticle10.1016/j.comnet.2024.1107782-s2.0-85203865062