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Our scheme aims (i) to sense environmental contextual parameters and accurately capture the spatiotemporal evolution of a certain phenomenon (e.g., fire, air contamination) and (ii) to fully automate the deployment process by letting nodes relocate, self-organize (and self-reorganize), and optimally cover the focus area. Our intention is to \u201copportunistically\u201d modify the previous placement of nodes to attain high-quality phenomenon monitoring. The required intelligence is fully distributed within the mobile sensor network so the deployment algorithm is executed incrementally by different nodes. The presented algorithm adopts the Particle Swarm Optimization technique, which yields very promising results as reported in the article (performance assessment). Our findings show that the proposed algorithm captures a certain phenomenon with very high accuracy while maintaining the networkwide energy expenditure at low levels. Random occurrences of similar phenomena put stress upon the algorithm which manages to react promptly and efficiently manage the available sensing resources in the broader setting.<\/jats:p>","DOI":"10.1145\/2882966","type":"journal-article","created":{"date-parts":[[2016,4,15]],"date-time":"2016-04-15T12:29:25Z","timestamp":1460723365000},"page":"1-59","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":20,"title":["Accurate, Dynamic, and Distributed Localization of Phenomena for Mobile Sensor Networks"],"prefix":"10.1145","volume":"12","author":[{"given":"Christos","family":"Anagnostopoulos","sequence":"first","affiliation":[{"name":"School of Computing Science, University of Glasgow, UK"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Stathes","family":"Hadjiefthymiades","sequence":"additional","affiliation":[{"name":"Department of Informatics &amp; Telecommunications, National and Kapodistrian University of Athens, Greece"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Kostas","family":"Kolomvatsos","sequence":"additional","affiliation":[{"name":"Department of Computer Science, University of Thessaly, Greece"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"320","published-online":{"date-parts":[[2016,4,15]]},"reference":[{"key":"e_1_2_1_1_1","doi-asserted-by":"publisher","DOI":"10.1109\/TMC.2008.34"},{"key":"e_1_2_1_2_1","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-642-12242-2_6"},{"volume-title":"Proceedings of the 4th IEEE International Conference on Distributed Computing in Sensor Systems (DCOSS\u201908)","author":"Bartolini N.","key":"e_1_2_1_3_1","unstructured":"N. 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