{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,11,18]],"date-time":"2025-11-18T12:14:51Z","timestamp":1763468091979,"version":"3.41.0"},"reference-count":39,"publisher":"Association for Computing Machinery (ACM)","issue":"4","license":[{"start":{"date-parts":[[2012,12,1]],"date-time":"2012-12-01T00:00:00Z","timestamp":1354320000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.acm.org\/publications\/policies\/copyright_policy#Background"}],"funder":[{"DOI":"10.13039\/100000144","name":"Division of Computer and Network Systems","doi-asserted-by":"publisher","award":["CNS-0954039"],"award-info":[{"award-number":["CNS-0954039"]}],"id":[{"id":"10.13039\/100000144","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100003150","name":"Fonds Qu\u00e9b\u00e9cois de la Recherche sur la Nature et les Technologies","doi-asserted-by":"publisher","award":["2010-NC-131844"],"award-info":[{"award-number":["2010-NC-131844"]}],"id":[{"id":"10.13039\/501100003150","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100000038","name":"Natural Sciences and Engineering Research Council of Canada","doi-asserted-by":"publisher","award":["341823-07","STPGP 364910-08"],"award-info":[{"award-number":["341823-07","STPGP 364910-08"]}],"id":[{"id":"10.13039\/501100000038","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["dl.acm.org"],"crossmark-restriction":true},"short-container-title":["ACM Trans. Embed. Comput. Syst."],"published-print":{"date-parts":[[2012,12]]},"abstract":"<jats:p>\n            Many Cyber-Physical Systems (CPS) are composed of low-cost devices that are deeply integrated with physical environments. As a result, the performance of a CPS system is inevitably undermined by various\n            <jats:italic>physical uncertainties<\/jats:italic>\n            , which include stochastic noises, hardware biases, unpredictable environment changes, and dynamics of the physical process of interest. Traditional solutions to these issues (e.g., device calibration and collaborative signal processing) work in an open-loop fashion and hence often fail to adapt to the uncertainties after system deployment. In this article, we propose an\n            <jats:italic>adaptive<\/jats:italic>\n            system-level calibration approach for a class of CPS systems whose primary objective is to detect events or targets of interest. Through collaborative data fusion, our calibration approach features a feedback control loop that exploits system heterogeneity to mitigate the impact of aforementioned uncertainties on the system performance. In contrast to existing heuristic-based solutions, our control-theoretical calibration algorithm can ensure provable system stability and convergence. We also develop a routing algorithm for fusion-based multihop CPS systems that is robust to communication unreliability and delay. Our approach is evaluated by both experiments on a testbed of Tmotes as well as extensive simulations based on data traces gathered from a real vehicle detection experiment. The results demonstrate that our calibration algorithm enables a CPS system to maintain the optimal sensing performance in the presence of various system and environmental dynamics.\n          <\/jats:p>","DOI":"10.1145\/2362336.2362347","type":"journal-article","created":{"date-parts":[[2013,1,11]],"date-time":"2013-01-11T15:42:48Z","timestamp":1357918968000},"page":"1-25","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":12,"title":["Adaptive calibration for fusion-based cyber-physical systems"],"prefix":"10.1145","volume":"11","author":[{"given":"Rui","family":"Tan","sequence":"first","affiliation":[{"name":"Michigan State University, MI"}]},{"given":"Guoliang","family":"Xing","sequence":"additional","affiliation":[{"name":"Michigan State University, MI"}]},{"given":"Xue","family":"Liu","sequence":"additional","affiliation":[{"name":"University of Nebraska-Lincoln, Canada"}]},{"given":"Jianguo","family":"Yao","sequence":"additional","affiliation":[{"name":"Shanghai Jiao Tong University, P.R. China"}]},{"given":"Zhaohui","family":"Yuan","sequence":"additional","affiliation":[{"name":"Wuhan University, P.R. China"}]}],"member":"320","published-online":{"date-parts":[[2013,1]]},"reference":[{"volume-title":"Proceedings of the SIGMETRICS Conference on Performance Modeling and Engineering. Springer, 185--215","author":"Adbelzaher T.","key":"e_1_2_1_1_1","unstructured":"Adbelzaher , T. , Diao , Y. , Hellerstein , J. L. , Lu , C. , and Zhu , X . 2008. Introduction to control theory and its application to computing systems . In Proceedings of the SIGMETRICS Conference on Performance Modeling and Engineering. Springer, 185--215 . Adbelzaher, T., Diao, Y., Hellerstein, J. L., Lu, C., and Zhu, X. 2008. Introduction to control theory and its application to computing systems. In Proceedings of the SIGMETRICS Conference on Performance Modeling and Engineering. Springer, 185--215."},{"key":"e_1_2_1_2_1","volume-title":"Probability and Measure Theory","author":"Ash R. B.","unstructured":"Ash , R. B. and Doleans-Dade , C. A. 1999. Probability and Measure Theory , 2 nd Ed. Harcourt Science and Technology . Ash, R. B. and Doleans-Dade, C. A. 1999. Probability and Measure Theory, 2nd Ed. Harcourt Science and Technology.","edition":"2"},{"key":"e_1_2_1_3_1","doi-asserted-by":"publisher","DOI":"10.1145\/1236360.1236372"},{"volume-title":"Proceedings of the International Conference on Information Processing in Sensor Networks (IPSN'03)","author":"Bychkovsky V.","key":"e_1_2_1_4_1","unstructured":"Bychkovsky , V. , Megerian , S. , Estrin , D. , and Potkonjak , M . 2003. A collaborative approach to in-place sensor calibration . In Proceedings of the International Conference on Information Processing in Sensor Networks (IPSN'03) . ACM Press, New York. Bychkovsky, V., Megerian, S., Estrin, D., and Potkonjak, M. 2003. A collaborative approach to in-place sensor calibration. 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ACM Press, New York."},{"key":"e_1_2_1_9_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.jpdc.2004.03.020"},{"key":"e_1_2_1_10_1","unstructured":"Duda R. Hart P. and Stork D. 2001. Pattern Classification. Wiley.   Duda R. Hart P. and Stork D. 2001. Pattern Classification. Wiley."},{"key":"e_1_2_1_11_1","doi-asserted-by":"publisher","DOI":"10.1145\/1127777.1127848"},{"volume-title":"Proceedings of the International Conference on Information Processing in Sensor Networks (IPSN'05)","author":"Dutta P.","key":"e_1_2_1_12_1","unstructured":"Dutta , P. , Grimmer , M. , Arora , A. , Bibyk , S. , and Culler , D . 2005. Design of a wireless sensor network platform for detecting rare, random and ephemeral events . In Proceedings of the International Conference on Information Processing in Sensor Networks (IPSN'05) . ACM Press, New York. Dutta, P., Grimmer, M., Arora, A., Bibyk, S., and Culler, D. 2005. Design of a wireless sensor network platform for detecting rare, random and ephemeral events. In Proceedings of the International Conference on Information Processing in Sensor Networks (IPSN'05). ACM Press, New York."},{"volume-title":"Proceedings of the Conference on Sensors. IEEE.","author":"Feng J.","key":"e_1_2_1_13_1","unstructured":"Feng , J. , Megerian , S. , and Potkonjak , M . 2003. Model-Based calibration for sensor networks . In Proceedings of the Conference on Sensors. IEEE. Feng, J., Megerian, S., and Potkonjak, M. 2003. Model-Based calibration for sensor networks. In Proceedings of the Conference on Sensors. 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