{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2024,8,6]],"date-time":"2024-08-06T02:41:19Z","timestamp":1722912079132},"reference-count":0,"publisher":"National Library of Serbia","issue":"4","license":[{"start":{"date-parts":[[2012,1,1]],"date-time":"2012-01-01T00:00:00Z","timestamp":1325376000000},"content-version":"unspecified","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by-nc-nd\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["ComSIS","COMPUT SCI INF SYST","COMPUT SCI INFORM SY","COMPUTER SCI INFORM","COMSIS J"],"published-print":{"date-parts":[[2012]]},"abstract":"<jats:p>Industrial Wireless Sensor Networks (IWSNs), a novel technique in industry\n   control, can greatly reduce the cost of measurement and control and improve\n   productive efficiency. Different from Wireless Sensor Networks (WSNs) in\n   non-industrial applications, the communication reliability of IWSNs has to be\n   guaranteed as the real-time field data need to be transmitted to the control\n   system through IWSNs. Obviously, the network architecture has a significant\n   influence on the performance of IWSNs, and therefore this paper investigates\n   the optimal node placement problem of IWSNs to ensure the network reliability\n   and reduce the cost. To solve this problem, a node placement model of IWSNs\n   is developed and formulized in which the reliability, the setup cost, the\n   maintenance cost and the scalability of the system are taken into account.\n   Then an improved adaptive mutation probability binary particle swarm\n   optimization algorithm (AMPBPSO) is proposed for searching out the best\n   placement scheme. After the verification of the model and optimization\n   algorithm on the benchmark problem, the presented AMPBPSO and the\n   optimization model are used to solve various large-scale optimal sensor\n   placement problems. The experimental results show that AMPBPSO is effective\n   to tackle IWSNs node placement problems and outperforms discrete binary\n   Particle Swarm Optimization (DBPSO) and standard Genetic Algorithm (GA) in\n   terms of search accuracy and the convergence speed with the guaranteed\n   network reliability.<\/jats:p>","DOI":"10.2298\/csis120117058w","type":"journal-article","created":{"date-parts":[[2012,12,28]],"date-time":"2012-12-28T10:31:33Z","timestamp":1356690693000},"page":"1553-1576","source":"Crossref","is-referenced-by-count":6,"title":["Optimal node placement of industrial wireless sensor networks based on adaptive mutation probability binary particle swarm optimization algorithm"],"prefix":"10.2298","volume":"9","author":[{"given":"Ling","family":"Wang","sequence":"first","affiliation":[{"name":"Shanghai Key Laboratory of Power Station Automation Technology, School of Mechatronics Engineering and Automation, Shanghai University, Shanghai, China + Center for Applied Optimization, Department of Industrial and Systems Engineering, University of Flor"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Wei","family":"Ye","sequence":"additional","affiliation":[{"name":"Shanghai Key Laboratory of Power Station Automation Technology, School of Mechatronics Engineering and Automation, Shanghai University, Shanghai, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Haikuan","family":"Wang","sequence":"additional","affiliation":[{"name":"Shanghai Key Laboratory of Power Station Automation Technology, School of Mechatronics Engineering and Automation, Shanghai University, Shanghai, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Xiping","family":"Fu","sequence":"additional","affiliation":[{"name":"Shanghai Key Laboratory of Power Station Automation Technology, School of Mechatronics Engineering and Automation, Shanghai University, Shanghai, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Minrui","family":"Fei","sequence":"additional","affiliation":[{"name":"Shanghai Key Laboratory of Power Station Automation Technology, School of Mechatronics Engineering and Automation, Shanghai University, Shanghai, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"suffix":"Muhammad","given":"Ilyas","family":"Menhas","sequence":"additional","affiliation":[{"name":"Shanghai Key Laboratory of Power Station Automation Technology, School of Mechatronics Engineering and Automation, Shanghai University, Shanghai, China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1078","container-title":["Computer Science and Information Systems"],"original-title":[],"language":"en","deposited":{"date-parts":[[2023,5,29]],"date-time":"2023-05-29T08:30:50Z","timestamp":1685349050000},"score":1,"resource":{"primary":{"URL":"https:\/\/doiserbia.nb.rs\/Article.aspx?ID=1820-02141200058W"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2012]]},"references-count":0,"journal-issue":{"issue":"4","published-print":{"date-parts":[[2012]]}},"URL":"https:\/\/doi.org\/10.2298\/csis120117058w","relation":{},"ISSN":["1820-0214","2406-1018"],"issn-type":[{"value":"1820-0214","type":"print"},{"value":"2406-1018","type":"electronic"}],"subject":[],"published":{"date-parts":[[2012]]}}}