{"title":"A priority aware local mutual exclusion algorithm for flying ad hoc networks","authors":"Guruprasad Kapilesh, Sridhar Dhanush, Venkatesan Poovazhaki Gokula Kannan, Viswasam Mary Anita Rajam","doi":"10.1007/s00607-023-01250-1","DOIUrl":null,"url":null,"abstract":"<p>In Flying Ad Hoc Networks (FANETs), the critical resource resides in an Unmanned Aerial Vehicle (UAV) and the user nodes within the UAV’s neighborhood defined by its transmission range can request for it. In Local Mutual Exclusion (LME), two nodes in the same neighborhood cannot execute the Critical Section (CS) simultaneously, but two non-neighboring nodes can be in the CS at the same time. This is a variation of traditional Mutual Exclusion (ME). The proposed Priority Aware - Request Collector Local Mutual Exclusion (PA-RCLME) algorithm ensures prioritized LME in such FANET structures. The proposed PA-RCLME algorithm is token-based and takes into account the priority of CS requests. It leverages a slow ageing technique to prevent starvation, to avoid a profusion of priority inversions, and to ensure the bounded waiting property of mutual exclusion algorithms. This algorithm introduces a neighborhood search technique that makes the token holder a secondary request collector, thereby reducing average request latency and increasing efficiency. The rapid movement of UAVs and other user nodes makes FANET topology highly dynamic and fault-prone. PA-RCLME algorithm handles it gracefully. Opportunistic Node Simulator (ONE) is used to simulate the algorithm and appropriate performance metrics have been recorded. A comparative analysis with the existing algorithm in the literature is also presented, and the proposed algorithm performs better.</p>","PeriodicalId":10718,"journal":{"name":"Computing","volume":"40 1","pages":""},"PeriodicalIF":3.3000,"publicationDate":"2024-01-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Computing","FirstCategoryId":"94","ListUrlMain":"https://doi.org/10.1007/s00607-023-01250-1","RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"COMPUTER SCIENCE, THEORY & METHODS","Score":null,"Total":0}
引用次数: 0
Abstract
In Flying Ad Hoc Networks (FANETs), the critical resource resides in an Unmanned Aerial Vehicle (UAV) and the user nodes within the UAV’s neighborhood defined by its transmission range can request for it. In Local Mutual Exclusion (LME), two nodes in the same neighborhood cannot execute the Critical Section (CS) simultaneously, but two non-neighboring nodes can be in the CS at the same time. This is a variation of traditional Mutual Exclusion (ME). The proposed Priority Aware - Request Collector Local Mutual Exclusion (PA-RCLME) algorithm ensures prioritized LME in such FANET structures. The proposed PA-RCLME algorithm is token-based and takes into account the priority of CS requests. It leverages a slow ageing technique to prevent starvation, to avoid a profusion of priority inversions, and to ensure the bounded waiting property of mutual exclusion algorithms. This algorithm introduces a neighborhood search technique that makes the token holder a secondary request collector, thereby reducing average request latency and increasing efficiency. The rapid movement of UAVs and other user nodes makes FANET topology highly dynamic and fault-prone. PA-RCLME algorithm handles it gracefully. Opportunistic Node Simulator (ONE) is used to simulate the algorithm and appropriate performance metrics have been recorded. A comparative analysis with the existing algorithm in the literature is also presented, and the proposed algorithm performs better.
期刊介绍:
Computing publishes original papers, short communications and surveys on all fields of computing. The contributions should be written in English and may be of theoretical or applied nature, the essential criteria are computational relevance and systematic foundation of results.