{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,5]],"date-time":"2026-06-05T04:22:37Z","timestamp":1780633357346,"version":"3.54.1"},"publisher-location":"California","reference-count":0,"publisher":"International Joint Conferences on Artificial Intelligence Organization","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2022,7]]},"abstract":"<jats:p>Long range space missions, such as Rosetta, require robust plans of data-acquisition activities and of the resulting data transfers. In this paper we revisit the problem of assigning priorities to data transfers in order to maximize safety margin of onboard memory. We propose a fast sweep algorithm to verify the feasibility of a given priority assignment and we introduce an efficient exact algorithm to assign priorities on a single downlink window. We prove that the problem is NP-hard for several windows, and we propose several randomized heuristics to tackle the general case. Our experimental results show that  the proposed approaches are able to  improve the plans computed for the real mission by the previously existing method, while the sweep algorithm yields drastic accelerations.<\/jats:p>","DOI":"10.24963\/ijcai.2022\/643","type":"proceedings-article","created":{"date-parts":[[2022,7,15]],"date-time":"2022-07-15T22:55:56Z","timestamp":1657925756000},"page":"4635-4641","source":"Crossref","is-referenced-by-count":3,"title":["An Efficient Approach to Data Transfer Scheduling for Long Range Space Exploration"],"prefix":"10.24963","author":[{"given":"Emmanuel","family":"Hebrard","sequence":"first","affiliation":[{"name":"LAAS-CNRS, Universit\u00e9 de Toulouse, CNRS, France"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Christian","family":"Artigues","sequence":"additional","affiliation":[{"name":"LAAS-CNRS, Universit\u00e9 de Toulouse, CNRS, France"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Pierre","family":"Lopez","sequence":"additional","affiliation":[{"name":"LAAS-CNRS, Universit\u00e9 de Toulouse, CNRS, France"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Arnaud","family":"Lusson","sequence":"additional","affiliation":[{"name":"LAAS-CNRS, Universit\u00e9 de Toulouse, CNRS, France"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Steve","family":"Chien","sequence":"additional","affiliation":[{"name":"Jet Propulsion Laboratory, California Institute of Technology"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Adrien","family":"Maillard","sequence":"additional","affiliation":[{"name":"Jet Propulsion Laboratory, California Institute of Technology"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Gregg","family":"Rabideau","sequence":"additional","affiliation":[{"name":"Jet Propulsion Laboratory, California Institute of Technology"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"10584","event":{"name":"Thirty-First International Joint Conference on Artificial Intelligence {IJCAI-22}","theme":"Artificial Intelligence","location":"Vienna, Austria","acronym":"IJCAI-2022","number":"31","sponsor":["International Joint Conferences on Artificial Intelligence Organization (IJCAI)"],"start":{"date-parts":[[2022,7,23]]},"end":{"date-parts":[[2022,7,29]]}},"container-title":["Proceedings of the Thirty-First International Joint Conference on Artificial Intelligence"],"original-title":[],"deposited":{"date-parts":[[2022,7,18]],"date-time":"2022-07-18T07:10:51Z","timestamp":1658128251000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.ijcai.org\/proceedings\/2022\/643"}},"subtitle":[],"proceedings-subject":"Artificial Intelligence Research Articles","short-title":[],"issued":{"date-parts":[[2022,7]]},"references-count":0,"URL":"https:\/\/doi.org\/10.24963\/ijcai.2022\/643","relation":{},"subject":[],"published":{"date-parts":[[2022,7]]}}}