{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,3,5]],"date-time":"2025-03-05T05:12:30Z","timestamp":1741151550418,"version":"3.38.0"},"reference-count":36,"publisher":"SAGE Publications","issue":"6","license":[{"start":{"date-parts":[[2012,3,7]],"date-time":"2012-03-07T00:00:00Z","timestamp":1331078400000},"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":["The International Journal of Robotics Research"],"published-print":{"date-parts":[[2012,5]]},"abstract":"<jats:p> We introduce a new geometric robot-routing problem which arises in data-muling applications where a mobile robot is charged with collecting data from stationary sensors. The objective is to compute the robot\u2019s trajectory and download sequence so as to minimize the time to collect data from all of the sensors. The total data collection time has two components:the robot\u2019s travel time and the download time. The time to download data from a sensor s is a function of the location of the robot and s: if the robot is a distance r<jats:sub> in<\/jats:sub> away from s, it can download the sensor\u2019s data in T<jats:sub> in<\/jats:sub> units of time. If the distance is greater than r<jats:sub> in<\/jats:sub> but less than r<jats:sub> out<\/jats:sub>, the download time is T<jats:sub> out<\/jats:sub> &gt; T<jats:sub> in<\/jats:sub>. Otherwise, the robot can not download the data from s. Here, r<jats:sub> in<\/jats:sub>, r<jats:sub> out<\/jats:sub>, T<jats:sub> in<\/jats:sub> and T<jats:sub> out<\/jats:sub> are input parameters. We refer to this model, which is based on recently developed experimental models for sensor network deployments, as the two-ring model, and the problem of downloading data from a given set of sensors in minimum amount of time under this model as the two-ring tour (TRT) problem. <\/jats:p><jats:p> We present approximation algorithms for the general case which uses solutions to the traveling salesperson with neighborhoods (TSPN) Problem as subroutines. We also present effcient solutions to special, but practically important versions of the problem such as grid-based and sparse deployments. The approach is validated in outdoor experiments. <\/jats:p>","DOI":"10.1177\/0278364912439429","type":"journal-article","created":{"date-parts":[[2012,3,8]],"date-time":"2012-03-08T01:46:38Z","timestamp":1331171198000},"page":"774-784","update-policy":"https:\/\/doi.org\/10.1177\/sage-journals-update-policy","source":"Crossref","is-referenced-by-count":14,"title":["Efficient data collection from wireless nodes under the two-ring communication model"],"prefix":"10.1177","volume":"31","author":[{"given":"Onur","family":"Tekdas","sequence":"first","affiliation":[{"name":"Department of Computer Science and Engineering, University of Minnesota, USA"}]},{"given":"Deepak","family":"Bhadauria","sequence":"additional","affiliation":[{"name":"Department of Computer Science and Engineering, University of Minnesota, USA"}]},{"given":"Volkan","family":"Isler","sequence":"additional","affiliation":[{"name":"Department of Computer Science and Engineering, University of Minnesota, USA"}]}],"member":"179","published-online":{"date-parts":[[2012,3,7]]},"reference":[{"key":"bibr1-0278364912439429","doi-asserted-by":"publisher","DOI":"10.1016\/j.adhoc.2003.09.010"},{"key":"bibr2-0278364912439429","doi-asserted-by":"publisher","DOI":"10.1109\/ISCC.2008.4625629"},{"key":"bibr3-0278364912439429","doi-asserted-by":"publisher","DOI":"10.1109\/WOWMOM.2007.4351776"},{"key":"bibr4-0278364912439429","doi-asserted-by":"publisher","DOI":"10.1016\/0166-218X(94)90008-6"},{"key":"bibr5-0278364912439429","doi-asserted-by":"publisher","DOI":"10.1145\/290179.290180"},{"key":"bibr6-0278364912439429","doi-asserted-by":"publisher","DOI":"10.1145\/570738.570749"},{"key":"bibr7-0278364912439429","doi-asserted-by":"publisher","DOI":"10.1002\/rob.20384"},{"key":"bibr8-0278364912439429","doi-asserted-by":"publisher","DOI":"10.1002\/wcm.584"},{"key":"bibr9-0278364912439429","doi-asserted-by":"publisher","DOI":"10.1007\/3-540-36978-3_9"},{"key":"bibr10-0278364912439429","first-page":"393","volume-title":"international conference on information processing in sensor networks","author":"Chen Y","year":"2009"},{"key":"bibr11-0278364912439429","unstructured":"Christofides N (1976) Worst-case analysis of a new heuristic for the travelling salesman problem. 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