{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,6]],"date-time":"2026-05-06T16:29:48Z","timestamp":1778084988199,"version":"3.51.4"},"reference-count":55,"publisher":"SAGE Publications","issue":"2","license":[{"start":{"date-parts":[[2025,1,10]],"date-time":"2025-01-10T00:00:00Z","timestamp":1736467200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/journals.sagepub.com\/page\/policies\/text-and-data-mining-license"}],"content-domain":{"domain":["journals.sagepub.com"],"crossmark-restriction":true},"short-container-title":["Journal of High Speed Networks"],"published-print":{"date-parts":[[2025,5]]},"abstract":"<jats:p>\n                    \n                    \n                    Mobile ad hoc networks (MANETs) have provided the opportunity to establish a temporary mobile network with no fixed centre or support. However, it is a fact that the security of routing systems is greatly affected by the inherent features of MANETs. Ad hoc on-demand distance vector (AODV) is susceptible to attacks such as black hole, grey hole, and wormhole attacks, despite the fact that it is the most prevalent routing protocol in MANETs. This study tries to offer solutions to these issues by enhancing the security and efficiency of the routing process in MANETs through the formulation of the Reinforcement Learning (RL)\u2013Artificial Bee Colony (ABC)\u2013AODV protocol, which is a combination of RL and ABC Algorithm in AODV protocol. According to the network's behaviour, the ABC algorithm selects the optimal path from a list of choices based on a number of factors. The suggested RL\u2013ABC\u2013AODV technique also contains dynamic and adaptive aspects in which the Q-learning and the network's current state are used to adjust parameters in real-time. The RL\u2013ABC\u2013AODV protocol achieved a packet delivery ratio of 99.45%, an end-to-end delay of 0.02 s, a throughput of 250.6 Mbps, and a routing overhead of 0.8, significantly outperforming existing methods.\n                  <\/jats:p>","DOI":"10.1177\/09266801241299920","type":"journal-article","created":{"date-parts":[[2025,4,28]],"date-time":"2025-04-28T11:02:53Z","timestamp":1745838173000},"page":"123-144","update-policy":"https:\/\/doi.org\/10.1177\/sage-journals-update-policy","source":"Crossref","is-referenced-by-count":4,"title":["High-speed adaptive and efficient ad hoc on-demand distance vector for secure routing in mobile ad hoc networks using reinforcement learning and artificial bee colony optimization"],"prefix":"10.1177","volume":"31","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-5107-7356","authenticated-orcid":false,"given":"Adel A","family":"Alyoubi","sequence":"first","affiliation":[{"name":"College of Business, Department of Management Information Systems, University of Jeddah, Saudi Arabia"}]}],"member":"179","published-online":{"date-parts":[[2025,1,10]]},"reference":[{"key":"e_1_3_3_2_2","doi-asserted-by":"publisher","DOI":"10.1109\/ICICCS51141.2021.9432258"},{"key":"e_1_3_3_3_2","doi-asserted-by":"publisher","DOI":"10.3991\/ijoe.v16i05.13325"},{"key":"e_1_3_3_4_2","doi-asserted-by":"publisher","DOI":"10.1109\/OJCOMS.2022.3192040"},{"key":"e_1_3_3_5_2","doi-asserted-by":"publisher","DOI":"10.3390\/su13116187"},{"key":"e_1_3_3_6_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.cose.2023.103096"},{"key":"e_1_3_3_7_2","first-page":"8831611","article-title":"A privacy-preserving attack-resistant trust model for internet of vehicles ad hoc networks.","volume":"2020","author":"Junejo MH","year":"2020","unstructured":"Junejo MH, Ab Rahman AA-H, Shaikh RA, et\u00a0al. A privacy-preserving attack-resistant trust model for internet of vehicles ad hoc networks. Sci Program 2020; 2020: 8831611.","journal-title":"Sci Program"},{"key":"e_1_3_3_8_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.sysarc.2019.101701"},{"key":"e_1_3_3_9_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.jnca.2020.102739"},{"key":"e_1_3_3_10_2","article-title":"Improving routing disruption attack detection in MANETs using efficient trust establishment.","volume":"33","author":"Yamini KAP","year":"2022","unstructured":"Yamini KAP, Stephy J, Suthendran K, et\u00a0al. Improving routing disruption attack detection in MANETs using efficient trust establishment. 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J\u00a0Mobile Comput Commun Mobile Netw 2022; 9: 9\u201317.","journal-title":"J\u00a0Mobile Comput Commun Mobile Netw"},{"key":"e_1_3_3_15_2","first-page":"1","article-title":"Predicting malicious node behavior in wireless network using DSR protocol and network metrics.","volume":"4","author":"Ganesan A","year":"2022","unstructured":"Ganesan A, Kumar Kombaiya A. Predicting malicious node behavior in wireless network using DSR protocol and network metrics. Int J\u00a0Comput Commun Inform 2022; 4: 1\u201310.","journal-title":"Int J\u00a0Comput Commun Inform"},{"key":"e_1_3_3_16_2","doi-asserted-by":"publisher","DOI":"10.1007\/s11227-019-02945-z"},{"key":"e_1_3_3_17_2","article-title":"Improving routing disruption attack detection in MANETs using efficient trust establishment.","volume":"33","author":"Yamini KAP","year":"2022","unstructured":"Yamini KAP, Stephy J, Suthendran K, et\u00a0al. Improving routing disruption attack detection in MANETs using efficient trust establishment. 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