{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2024,10,27]],"date-time":"2024-10-27T12:10:01Z","timestamp":1730031001107,"version":"3.28.0"},"reference-count":50,"publisher":"Wiley","issue":"1","license":[{"start":{"date-parts":[[2020,10,21]],"date-time":"2020-10-21T00:00:00Z","timestamp":1603238400000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/onlinelibrary.wiley.com\/termsAndConditions#vor"}],"funder":[{"DOI":"10.13039\/501100010887","name":"Weifang University of Science and Technology","doi-asserted-by":"publisher","award":["2017BS19"],"id":[{"id":"10.13039\/501100010887","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100014103","name":"Key Technology Research and Development Program of Shandong","doi-asserted-by":"publisher","award":["2019GNC106034"],"id":[{"id":"10.13039\/100014103","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["onlinelibrary.wiley.com"],"crossmark-restriction":true},"short-container-title":["Int J Communication"],"published-print":{"date-parts":[[2021,1,10]]},"abstract":"Summary<\/jats:title>Regarding the recent information technology improvement, the fog computing (FC) emergence increases the ability of computational equipment and supplies modern solutions for traditional industrial applications. In the fog environment, Internet of Things (IoT) applications are completed by computing nodes that are intermediate in the fog, and the physical servers in data centers of the cloud. From the other side, because of resource constraints, dynamic nature, resource heterogeneity, and volatility of fog environment, resource management problems must be considered as one of the challenging issues of fog. The resource managing problem is an NP\u2010hard issue, so, in the current article, a powerful hybrid algorithm for managing resources in FC\u2010based IoT is proposed using an ant colony optimization (ACO) and a genetic algorithm (GA). GAs are computationally costly because of some problems such as the lack of guarantee for obtaining optimal solutions. Then, the precision and speed of convergence can be optimized by the ACO algorithm. Therefore, the powerful affirmative feedback pros of ACO on the convergence rate is considered. The algorithm uses GA's universal investigation power, and then it is transformed into ACO primary pheromone. This algorithm outperforms ACO and GA under equal conditions, as the simulation experiments showed.<\/jats:p>","DOI":"10.1002\/dac.4652","type":"journal-article","created":{"date-parts":[[2023,9,4]],"date-time":"2023-09-04T06:07:35Z","timestamp":1693807655000},"update-policy":"http:\/\/dx.doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":14,"title":["An energy\u2010aware approach for resource managing in the fog\u2010basedInternet of Things<\/scp>using a hybrid algorithm"],"prefix":"10.1002","volume":"34","author":[{"given":"Xiaojun","family":"Ren","sequence":"first","affiliation":[{"name":"School of Computer and Software Weifang University of Science and Technology Shouguang China"}]},{"given":"Zhijun","family":"Zhang","sequence":"additional","affiliation":[{"name":"School of Computer and Software Weifang University of Science and Technology Shouguang China"}]},{"ORCID":"http:\/\/orcid.org\/0000-0001-6901-9736","authenticated-orcid":false,"given":"Seyedeh Maryam","family":"Arefzadeh","sequence":"additional","affiliation":[{"name":"Department of Control Engineering, Bushehr Branch Islamic Azad University Bushehr Iran"}]}],"member":"311","published-online":{"date-parts":[[2020,10,21]]},"reference":[{"key":"e_1_2_9_2_1","doi-asserted-by":"publisher","DOI":"10.1108\/CW-01-2019-0008"},{"key":"e_1_2_9_3_1","doi-asserted-by":"publisher","DOI":"10.1007\/s10799-016-0270-8"},{"key":"e_1_2_9_4_1","doi-asserted-by":"publisher","DOI":"10.1002\/dac.3980"},{"key":"e_1_2_9_5_1","doi-asserted-by":"publisher","DOI":"10.1109\/JIOT.2016.2584538"},{"issue":"1","key":"e_1_2_9_6_1","first-page":"10","article-title":"Kalman filtering for estimation and prediction servers with lower traffic loads for transferring high\u2010level processes in cloud computing","volume":"23","author":"Darbandi M","year":"2017","journal-title":"Int J Technol Innov Rese"},{"key":"e_1_2_9_7_1","doi-asserted-by":"crossref","unstructured":"Stojmenovic I andWen SThe fog computing paradigm: scenarios and security issuesin 2014 federated conference on computer science and information systems (IEEE 2014) pp.1\u20108.","DOI":"10.15439\/2014F503"},{"key":"e_1_2_9_8_1","first-page":"1","article-title":"Fog computing in health management processing systems","author":"Fu C","year":"2020","journal-title":"Kybernetes"},{"key":"e_1_2_9_9_1","first-page":"e3792","article-title":"aTask scheduling approaches in fog computing: a survey","author":"Hosseinioun P","journal-title":"Trans Emerg Telecommun Technol"},{"key":"e_1_2_9_10_1","doi-asserted-by":"publisher","DOI":"10.3390\/app7121325"},{"key":"e_1_2_9_11_1","doi-asserted-by":"crossref","unstructured":"Datta S. 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