{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,24]],"date-time":"2026-04-24T15:02:46Z","timestamp":1777042966528,"version":"3.51.4"},"reference-count":43,"publisher":"Association for Computing Machinery (ACM)","issue":"3","license":[{"start":{"date-parts":[[2015,2,17]],"date-time":"2015-02-17T00:00:00Z","timestamp":1424131200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.acm.org\/publications\/policies\/copyright_policy#Background"}],"funder":[{"DOI":"10.13039\/100000001","name":"National Science Foundation","doi-asserted-by":"publisher","award":["CNS 0910988"],"award-info":[{"award-number":["CNS 0910988"]}],"id":[{"id":"10.13039\/100000001","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["dl.acm.org"],"crossmark-restriction":true},"short-container-title":["ACM Trans. Sen. Netw."],"published-print":{"date-parts":[[2015,5,28]]},"abstract":"<jats:p>Energy efficiency is one of the key objectives in data gathering in wireless sensor networks (WSNs). Recent research on energy-efficient data gathering in WSNs has explored the use of Compressive Sensing (CS) to parsimoniously represent the data. However, the performance of CS-based data gathering methods has been limited since the approaches failed to take advantage of judicious network configurations and effective CS-based data aggregation procedures. In this article, a novel Hierarchical Data Aggregation method using Compressive Sensing (HDACS) is presented, which combines a hierarchical network configuration with CS. Our key idea is to set multiple compression thresholds adaptively based on cluster sizes at different levels of the data aggregation tree to optimize the amount of data transmitted. The advantages of the proposed model in terms of the total amount of data transmitted and data compression ratio are analytically verified. Moreover, we formulate a new energy model by factoring in both processor and radio energy consumption into the cost, especially the computation cost incurred in relatively complex algorithms. We also show that communication cost remains dominant in data aggregation in the practical applications of large-scale networks. We use both the real-world data and synthetic datasets to test CS-based data aggregation schemes on the SIDnet-SWANS simulation platform. The simulation results demonstrate that the proposed HDACS model guarantees accurate signal recovery performance. It also provides substantial energy savings compared with existing methods.<\/jats:p>","DOI":"10.1145\/2700264","type":"journal-article","created":{"date-parts":[[2015,2,18]],"date-time":"2015-02-18T13:24:05Z","timestamp":1424265845000},"page":"1-25","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":92,"title":["Hierarchical Data Aggregation Using Compressive Sensing (HDACS) in WSNs"],"prefix":"10.1145","volume":"11","author":[{"given":"Xi","family":"Xu","sequence":"first","affiliation":[{"name":"University of Illinois at Chicago, Chicago, IL"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Rashid","family":"Ansari","sequence":"additional","affiliation":[{"name":"University of Illinois at Chicago, Chicago, IL"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Ashfaq","family":"Khokhar","sequence":"additional","affiliation":[{"name":"University of Illinois at Chicago, Chicago, IL"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Athanasios V.","family":"Vasilakos","sequence":"additional","affiliation":[{"name":"University of Western Macedonia, Greece"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"320","published-online":{"date-parts":[[2015,2,17]]},"reference":[{"key":"e_1_2_1_1_1","unstructured":"Amtel. 2011. 8-bit Atmel Microcontroller with 128KBytes In-System Programmable Flash. Retrieved from http:\/\/www.atmel.com\/images\/doc2467.pdf.  Amtel. 2011. 8-bit Atmel Microcontroller with 128KBytes In-System Programmable Flash. Retrieved from http:\/\/www.atmel.com\/images\/doc2467.pdf."},{"key":"e_1_2_1_2_1","doi-asserted-by":"publisher","DOI":"10.1109\/MCOM.2002.1024422"},{"key":"e_1_2_1_3_1","doi-asserted-by":"publisher","DOI":"10.5555\/829523.830959"},{"key":"e_1_2_1_4_1","doi-asserted-by":"crossref","unstructured":"J. Artiola I. Pepper and M. Brusseau. 2004. Environmental Monitoring and Characterization. Elsevier Science.  J. Artiola I. Pepper and M. Brusseau. 2004. Environmental Monitoring and Characterization. Elsevier Science.","DOI":"10.1016\/B978-012064477-3\/50003-5"},{"key":"e_1_2_1_5_1","volume-title":"Proceedings of the 22nd Annual Joint Conference of the IEEE Computer and Communications (INFOCOM\u201903)","author":"Bandyopadhyay S.","unstructured":"S. Bandyopadhyay and E. J. Coyle . 2003. An energy efficient hierarchical clustering algorithm for wireless sensor networks . In Proceedings of the 22nd Annual Joint Conference of the IEEE Computer and Communications (INFOCOM\u201903) .Vol. 3. IEEE, 1713--1723. S. Bandyopadhyay and E. J. Coyle. 2003. An energy efficient hierarchical clustering algorithm for wireless sensor networks. In Proceedings of the 22nd Annual Joint Conference of the IEEE Computer and Communications (INFOCOM\u201903).Vol. 3. IEEE, 1713--1723."},{"key":"e_1_2_1_6_1","doi-asserted-by":"crossref","unstructured":"R. Barr Z. J. Haas R. van Renesse K. Tamtoro B. S. Viglietta C. Lin M. Fong and E. Cheung. 2004. JiST\/SWANS Java in Simulation Time\/Scalable Wireless Ad hoc Network Simulator. Retrieved from http:\/\/jist.ece.cornell.edu.  R. Barr Z. J. Haas R. van Renesse K. Tamtoro B. S. Viglietta C. Lin M. Fong and E. Cheung. 2004. JiST\/SWANS Java in Simulation Time\/Scalable Wireless Ad hoc Network Simulator. Retrieved from http:\/\/jist.ece.cornell.edu.","DOI":"10.1201\/9780203323687.ch19"},{"key":"e_1_2_1_7_1","doi-asserted-by":"publisher","DOI":"10.1109\/MSP.2007.4286571"},{"key":"e_1_2_1_8_1","doi-asserted-by":"publisher","DOI":"10.1109\/TIT.2010.2040894"},{"key":"e_1_2_1_9_1","unstructured":"D. Baron M. B. Wakin M. F. Duarte S. Sarvotham and R. G. Baraniuk. 2006. Distributed Compressed Sensing. Technical Report. Electrical and Computer Engineering Department Rice University.  D. Baron M. B. Wakin M. F. Duarte S. Sarvotham and R. G. Baraniuk. 2006. Distributed Compressed Sensing. Technical Report. Electrical and Computer Engineering Department Rice University."},{"key":"e_1_2_1_10_1","unstructured":"R. Barr. 2004. JiST-Java in Simulation Time User Guide. Retrieved from http:\/\/jist.ece.cornell.edu\/docs.html.  R. Barr. 2004. JiST-Java in Simulation Time User Guide. Retrieved from http:\/\/jist.ece.cornell.edu\/docs.html."},{"key":"e_1_2_1_11_1","doi-asserted-by":"publisher","DOI":"10.1109\/TIT.2006.885507"},{"key":"e_1_2_1_12_1","doi-asserted-by":"publisher","DOI":"10.1109\/TIT.2005.862083"},{"key":"e_1_2_1_13_1","doi-asserted-by":"publisher","DOI":"10.1109\/MSP.2007.914731"},{"key":"e_1_2_1_14_1","doi-asserted-by":"publisher","DOI":"10.1109\/QSHINE.2005.21"},{"key":"e_1_2_1_15_1","doi-asserted-by":"publisher","DOI":"10.1109\/TWC.2012.121412.120148"},{"key":"e_1_2_1_16_1","unstructured":"D. Ciullo G. D. Celik and E. Modiano. 2010. Minimizing transmission energy in sensor networks via trajectory control. Modeling and Optimization in Mobile Ad Hoc and Wireless Networks (May 2010) 132--141.  D. Ciullo G. D. Celik and E. Modiano. 2010. Minimizing transmission energy in sensor networks via trajectory control. Modeling and Optimization in Mobile Ad Hoc and Wireless Networks (May 2010) 132--141."},{"key":"e_1_2_1_17_1","doi-asserted-by":"publisher","DOI":"10.1006\/acha.2000.0313"},{"key":"e_1_2_1_18_1","doi-asserted-by":"publisher","DOI":"10.1109\/MC.2004.93"},{"key":"e_1_2_1_19_1","doi-asserted-by":"publisher","DOI":"10.1109\/TIT.2006.871582"},{"key":"e_1_2_1_20_1","doi-asserted-by":"publisher","DOI":"10.1109\/TIT.2011.2173241"},{"key":"e_1_2_1_21_1","unstructured":"O. C. Ghica. 2010. SIDnet-SWANS Manual. Retrieved from http:\/\/users.eecs.northwestern.edu\/ocg474\/SIDnet\/SIDnet-SWANS&percnt;20manual.pdf.  O. C. Ghica. 2010. SIDnet-SWANS Manual. Retrieved from http:\/\/users.eecs.northwestern.edu\/ocg474\/SIDnet\/SIDnet-SWANS&percnt;20manual.pdf."},{"key":"e_1_2_1_22_1","doi-asserted-by":"publisher","DOI":"10.1109\/TNET.2012.2212452"},{"key":"e_1_2_1_23_1","doi-asserted-by":"publisher","DOI":"10.1145\/2248371.2248386"},{"key":"e_1_2_1_24_1","doi-asserted-by":"publisher","DOI":"10.5555\/820264.820485"},{"key":"e_1_2_1_25_1","doi-asserted-by":"publisher","DOI":"10.5555\/820264.820485"},{"key":"e_1_2_1_26_1","volume-title":"Proceedings of IEEE INFOCOM.","author":"Kong L.","unstructured":"L. Kong , M. Xia , X. Y. Liu , M.-Y. Wu , and X. Liu . 2013. Data loss and reconstruction in sensor networks . In Proceedings of IEEE INFOCOM. L. Kong, M. Xia, X. Y. Liu, M.-Y. Wu, and X. Liu. 2013. Data loss and reconstruction in sensor networks. In Proceedings of IEEE INFOCOM."},{"key":"e_1_2_1_27_1","doi-asserted-by":"publisher","DOI":"10.1145\/1080829.1080831"},{"key":"e_1_2_1_28_1","doi-asserted-by":"publisher","DOI":"10.1145\/2461381.2461396"},{"key":"e_1_2_1_29_1","doi-asserted-by":"publisher","DOI":"10.1145\/1614320.1614337"},{"key":"e_1_2_1_30_1","doi-asserted-by":"publisher","DOI":"10.1109\/TNET.2009.2033472"},{"key":"e_1_2_1_31_1","doi-asserted-by":"crossref","unstructured":"J. Luo L. Xiang and C. Rosenberg. 2010. Does compressed sensing improve the throughput of wireless sensor networks&quest; In Proceedings of the IEEE International Conference on Communications.  J. Luo L. Xiang and C. Rosenberg. 2010. Does compressed sensing improve the throughput of wireless sensor networks&quest; In Proceedings of the IEEE International Conference on Communications.","DOI":"10.1109\/ICC.2010.5502565"},{"key":"e_1_2_1_32_1","doi-asserted-by":"publisher","DOI":"10.1007\/s10208-008-9031-3"},{"key":"e_1_2_1_33_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.acha.2008.07.002"},{"key":"e_1_2_1_34_1","doi-asserted-by":"publisher","DOI":"10.1145\/1031495.1031508"},{"key":"e_1_2_1_35_1","doi-asserted-by":"publisher","DOI":"10.1109\/MSP.2007.914729"},{"key":"e_1_2_1_36_1","volume-title":"Compressed Sensing: A Tutorial.","author":"Romberg J.","year":"2007","unstructured":"J. Romberg and M. Wakin . 2007 . Compressed Sensing: A Tutorial. Retrieved from http:\/\/users.ece.gatech.edu\/justin\/ssp2007. J. Romberg and M. Wakin. 2007. Compressed Sensing: A Tutorial. Retrieved from http:\/\/users.ece.gatech.edu\/justin\/ssp2007."},{"key":"e_1_2_1_37_1","doi-asserted-by":"publisher","DOI":"10.1109\/TNET.2011.2169424"},{"key":"e_1_2_1_38_1","doi-asserted-by":"publisher","DOI":"10.1145\/381677.381703"},{"key":"e_1_2_1_39_1","doi-asserted-by":"publisher","DOI":"10.1145\/1031495.1031518"},{"key":"e_1_2_1_40_1","doi-asserted-by":"publisher","DOI":"10.1145\/1127777.1127813"},{"key":"e_1_2_1_41_1","doi-asserted-by":"publisher","DOI":"10.1109\/TIT.2007.909108"},{"key":"e_1_2_1_42_1","volume-title":"Proceedings of the 8th Annual IEEE SECON.","author":"Xiang L.","unstructured":"L. Xiang , J. Luo , and A. V. Vasilakos . 2011. Compressed data aggregation for energy efficient wireless sensor networks . In Proceedings of the 8th Annual IEEE SECON. L. Xiang, J. Luo, and A. V. Vasilakos. 2011. Compressed data aggregation for energy efficient wireless sensor networks. In Proceedings of the 8th Annual IEEE SECON."},{"key":"e_1_2_1_43_1","doi-asserted-by":"publisher","DOI":"10.1145\/1374618.1374650"}],"container-title":["ACM Transactions on Sensor Networks"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/2700264","content-type":"unspecified","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/dl.acm.org\/doi\/pdf\/10.1145\/2700264","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,6,18]],"date-time":"2025-06-18T05:07:43Z","timestamp":1750223263000},"score":1,"resource":{"primary":{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/2700264"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2015,2,17]]},"references-count":43,"journal-issue":{"issue":"3","published-print":{"date-parts":[[2015,5,28]]}},"alternative-id":["10.1145\/2700264"],"URL":"https:\/\/doi.org\/10.1145\/2700264","relation":{},"ISSN":["1550-4859","1550-4867"],"issn-type":[{"value":"1550-4859","type":"print"},{"value":"1550-4867","type":"electronic"}],"subject":[],"published":{"date-parts":[[2015,2,17]]},"assertion":[{"value":"2013-11-01","order":0,"name":"received","label":"Received","group":{"name":"publication_history","label":"Publication History"}},{"value":"2014-11-01","order":1,"name":"accepted","label":"Accepted","group":{"name":"publication_history","label":"Publication History"}},{"value":"2015-02-17","order":2,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}]}}