A buffer-aware dynamic UAV trajectory design for data collection in resource-constrained IoT frameworks. (May 2022)

• Record Type: Journal Article
• Authors: Mazumdar, Nabajyoti; Roy, Saugata; Nag, Amitava; Singh, Jyoti Prakash
• Is Part Of: Computers & electrical engineering. Volume 100(2022)
• Publication Date: 2022-05
• Subjects: Ant colony optimization (ACO) -- Buffer aware -- Data collector -- Internet of things (IoT) -- IoT node (IN) -- Unmanned aerial vehicle (UAV); Computer engineering -- Periodicals; Electrical engineering -- Periodicals; Electrical engineering -- Data processing -- Periodicals; Ordinateurs -- Conception et construction -- Périodiques; Électrotechnique -- Périodiques; Électrotechnique -- Informatique -- Périodiques; Computer engineering; Electrical engineering; Electrical engineering -- Data processing; Periodicals; Electronic journals; 621.302854
• DOI: 10.1016/j.compeleceng.2022.107934
• Languages: English
• ISSNs: 0045-7906

Abstract

Abstract: The emergence of unmanned aerial vehicle (UAV)-enabled technology in the Internet of Things (IoT) era leads to a significant reduction in data collection delays when accumulating sensory data from ground IoT nodes (INs). As a flying data collector, the UAV hovers at a limited number of Access Points (APs) to collect data, outperforming ground data collectors in terms of transmission energy consumption, data delivery reliability, and timeliness. However, the INs have a finite amount of buffer capacity to store the data that must be collected before they overflow. As a result, the data gathering route for UAVs should be adaptable to INs' buffer deadline in order to minimize data loss. In this paper, a buffer-aware dynamic UAV trajectory design protocol is proposed for data collection from resource-constrained INs. A distributed AP nomination strategy is proposed in order to reduce UAV hovering latency. Furthermore, using machine learning approaches, a modified ant colony optimization algorithm is constructed to minimize the data loss penalty due to buffer overflow. Finally, the performance of the proposed scheme is evaluated against several state-of-the-art protocols with regards to parameters such as data loss penalty, packet delivery ratio, and network lifetime. Graphical abstract: Highlights: The UAV Access points selected ensure one-hop connectivity with IoT nodes. To reduce the data collection latency, a minimal set of Access points are nominated. A modified ACO algorithm is used to create a dynamic UAV trajectory.