Directional Antenna Based Scheduling Protocol for IoT Networks

Abstract

Contemporary communication networks are the Internet of Things (IoT) networks that can potentially connect millions of devices. However, as these networks expand, issues such as power consumption, throughput, and interference are much more important. In this paper, we present the Directional Scheduling protocol for the constrained 6TiSCH-IoT networks in order to enhance the performance of the network due to the use of directional antennas. The proposed protocol is different from other conventional omnidirectional antenna-based systems, which have low spatial reuse and high interference; it allows multiple nodes to transmit data simultaneously, reducing interference and enhancing throughput. The protocol is decentralized, so every IoT node can locally decide about the time for the next transmission based on local knowledge and thus exclude head-of-line blocking. This paper presents a detailed description of the proposed system model with a focus on the antenna configuration aspect, energy consumption, and the scheduling policy that aims at minimizing power consumption while at the same time achieving high network throughput and low end-to-end delay. Simulation results demonstrate up to 5× higher throughput, 30% reduced end-to-end delay, and a 25% reduction in energy consumption with directional antennas (beam widths of 90 ^∘ and 45 ^∘ ) compared to omnidirectional configurations, highlighting the enhanced performance and energy efficiency of 6TiSCH for IoT communication. The conclusion reveals that this approach is useful to solve the two main challenges large-scale and IoT networks face, namely, scalability and interference. Further research may examine the application of artificial intelligence techniques to enhance the scheduling and resource allocation functions, in addition to advances in the design of dual-configuration antenna systems, where better performance and lower hardware complexity are sought.

Received: 30 November 2024 | Revised: 24 March 2025 | Accepted: 7 May 2025

Conflicts of Interest

The authors declare that they have no conflicts of interest to this work.

Data Availability Statement

Data sharing is not applicable to this article as no new data were created or analyzed in this study.

Author Contribution Statement

Anil Carie: Conceptualization, Methodology, Software, Validation, Formal analysis, Investigation, Resources, Data curation, Writing – original draft, Writing – review & editing, Visualization, Supervision, Project administration. Abdur Rashid Sangi: Conceptualization, Methodology, Software, Validation, Formal analysis, Investigation, Resources, Data curation, Writing – original draft, Writing – review & editing, Visualization, Supervision, Project administration, Funding acquisition. Satish Anamalamudi: Conceptualization, Methodology, Software, Validation, Formal analysis, Investigation, Resources, Data curation, Writing – original draft, Writing – review & editing, Visualization, Supervision, Project administration. Murali Krishna Enduri: Conceptualization, Methodology, Software, Validation, Formal analysis, Investigation, Resources, Data curation, Writing – original draft, Writing – review & editing, Visualization, Supervision, Project administration. Baha Ihnaini: Conceptualization, Methodology, Software, Validation, Formal analysis, Investigation, Resources, Data curation, Writing – original draft, Writing – review & editing, Visualization, Supervision, Project administration, Funding acquisition. Hemn Barzan Abdalla: Conceptualization, Methodology, Software, Validation, Formal analysis, Investigation, Resources, Data curation, Writing – original draft, Writing – review & editing, Visualization, Supervision, Project administration.