{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,9,18]],"date-time":"2025-09-18T10:17:27Z","timestamp":1758190647289,"version":"3.44.0"},"reference-count":9,"publisher":"Association for Computing Machinery (ACM)","issue":"12","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Proc. VLDB Endow."],"published-print":{"date-parts":[[2020,8]]},"abstract":"<jats:p>\n            Reconstructing a high dimensional unknown signal, using lower dimensional observations is a challenging problem, known as\n            <jats:italic toggle=\"yes\">signal reconstruction problem<\/jats:italic>\n            (SRP), with diverse applications including network traffic engineering, medical image reconstruction, and astronomy. Recently the database community has shown significant advancements in solving the SRP problem efficiently, effectively, and in scale by leveraging database techniques such as similarity joins. In this demo, we demonstrate Orca-SR that highlights the benefits of signal reconstruction in scale by demonstrating real-time network traffic flow analysis on large networks that were not possible before. Orca-SR is a web application that enables a user to generate network flow and load the network for interactive analysis of the impact of different traffic patterns on signal reconstruction.\n          <\/jats:p>","DOI":"10.14778\/3415478.3415523","type":"journal-article","created":{"date-parts":[[2020,9,14]],"date-time":"2020-09-14T18:46:35Z","timestamp":1600109195000},"page":"2977-2980","source":"Crossref","is-referenced-by-count":0,"title":["Orca-SR"],"prefix":"10.14778","volume":"13","author":[{"given":"Jees","family":"Augustine","sequence":"first","affiliation":[{"name":"University of Texas at Arlington"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Suraj","family":"Shetiya","sequence":"additional","affiliation":[{"name":"University of Texas at Arlington"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Abolfazl","family":"Asudeh","sequence":"additional","affiliation":[{"name":"University of Illinois at Chicago"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Saravanan","family":"Thirumuruganathan","sequence":"additional","affiliation":[{"name":"HBKU"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Azade","family":"Nazi","sequence":"additional","affiliation":[{"name":"Google Brain"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Nan","family":"Zhang","sequence":"additional","affiliation":[{"name":"American University"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Gautam","family":"Das","sequence":"additional","affiliation":[{"name":"University of Texas at Arlington"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Divesh","family":"Srivastava","sequence":"additional","affiliation":[{"name":"AT&amp;T Labs-Research"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"320","published-online":{"date-parts":[[2020,8]]},"reference":[{"key":"e_1_2_1_1_1","volume-title":"Special Issue on 2018 ACM SIGMOD Research Highlights, 48(1):42--49","author":"Asudeh A.","year":"2019","unstructured":"A. Asudeh, J. Augustine, A. Nazi, S. Thirumuruganathan, N. Zhang, G. Das, and D. Srivastava. Efficient signal reconstruction for a broad range of applications. SIGMOD Records, Special Issue on 2018 ACM SIGMOD Research Highlights, 48(1):42--49, Nov. 2019."},{"key":"e_1_2_1_2_1","first-page":"1","volume-title":"Special Issue on best of VLDB'18","author":"Asudeh A.","year":"2019","unstructured":"A. Asudeh, J. Augustine, A. Nazi, S. Thirumuruganathan, N. Zhang, G. Das, and D. Srivastava. Scalable algorithms for signal reconstruction by leveraging similarity joins. The VLDB Journal, Special Issue on best of VLDB'18, pages 1--27, 2019."},{"doi-asserted-by":"publisher","key":"e_1_2_1_3_1","DOI":"10.14778\/3231751.3231752"},{"doi-asserted-by":"publisher","key":"e_1_2_1_4_1","DOI":"10.1109\/ICDE.2006.9"},{"doi-asserted-by":"publisher","key":"e_1_2_1_5_1","DOI":"10.1109\/GLOCOM.1995.502798"},{"doi-asserted-by":"publisher","key":"e_1_2_1_6_1","DOI":"10.14778\/1453856.1453883"},{"issue":"3","key":"e_1_2_1_7_1","first-page":"155","article-title":"Hierarchical routing for large networks performance evaluation and optimization","volume":"1","author":"Kleinrock L.","year":"1977","unstructured":"L. Kleinrock and F. Kamoun. Hierarchical routing for large networks performance evaluation and optimization. Computer Networks, 1(3):155--174, 1977.","journal-title":"Computer Networks"},{"doi-asserted-by":"publisher","key":"e_1_2_1_8_1","DOI":"10.1145\/2667522.2667536"},{"doi-asserted-by":"publisher","key":"e_1_2_1_9_1","DOI":"10.1145\/781027.781053"}],"container-title":["Proceedings of the VLDB Endowment"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/dl.acm.org\/doi\/pdf\/10.14778\/3415478.3415523","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,9,17]],"date-time":"2025-09-17T02:21:09Z","timestamp":1758075669000},"score":1,"resource":{"primary":{"URL":"https:\/\/dl.acm.org\/doi\/10.14778\/3415478.3415523"}},"subtitle":["a real-time traffic engineering framework leveraging similarity joins"],"short-title":[],"issued":{"date-parts":[[2020,8]]},"references-count":9,"journal-issue":{"issue":"12","published-print":{"date-parts":[[2020,8]]}},"alternative-id":["10.14778\/3415478.3415523"],"URL":"https:\/\/doi.org\/10.14778\/3415478.3415523","relation":{},"ISSN":["2150-8097"],"issn-type":[{"type":"print","value":"2150-8097"}],"subject":[],"published":{"date-parts":[[2020,8]]}}}