Monitoring Inter-Drone Service Interference for Resilient Operations

作     者：Rizvi, Syeda Amna Bouguettaya, Athman Abusafia, Amani Lakhdari, Abdallah Srithar, Vejaykarthy 

作者机构：Univ Sydney Sch Comp Sci Sydney NSW 2006 Australia Univ Melbourne Sch Comp & Informat Syst Melbourne Vic 3010 Australia 

出 版 物：《IEEE TRANSACTIONS ON SERVICES COMPUTING》 (IEEE Trans. Serv. Comput.)

年 卷 期：2025年第18卷第3期

页      面：1573-1587页

核心收录：

学科分类：0808[工学-电气工程] 08[工学] 0835[工学-软件工程] 0812[工学-计算机科学与技术（可授工学、理学学位）] 

基　　金：Australian Research Council [LE220100078  DP220101823] 

主　　题：Drones Interference Peer-to-peer computing Batteries Quality of service Safety Energy consumption Aerodynamics Trajectory Taxonomy Drone delivery drone service skyway network inter-drone interference unmanned traffic management 

摘      要：We propose a novel service-based framework for drone service resilience. Our framework monitors inter-drone interference that may lead to drone service failure. We present a novel drone service interference taxonomy to formally identify different interference types in a skyway network. We then propose a heuristic-based approach that leverages spatio-temporal proximity analysis to detect the occurrence of inter-drone interference. In addition, we present an interference severity assessment to quantify their impact on drone services efficiency. We conduct a set of experiments using real-world datasets to evaluate the effectiveness and efficiency of our proposed approach. The results indicate that the proposed heuristic-based approach detects the occurrence of inter-drone interferences with an accuracy of 95%. In addition, the proposed method is $\approx$approximate to 70% more efficient than the baseline exhaustive approach and $\approx$approximate to 48% faster than the K-means approach.