{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,6,19]],"date-time":"2025-06-19T04:22:06Z","timestamp":1750306926683,"version":"3.41.0"},"reference-count":25,"publisher":"Association for Computing Machinery (ACM)","issue":"2","license":[{"start":{"date-parts":[[2013,4,29]],"date-time":"2013-04-29T00:00:00Z","timestamp":1367193600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.acm.org\/publications\/policies\/copyright_policy#Background"}],"content-domain":{"domain":["dl.acm.org"],"crossmark-restriction":true},"short-container-title":["SIGCOMM Comput. Commun. Rev."],"published-print":{"date-parts":[[2013,4,29]]},"abstract":"<jats:p>Recent work in network measurements focuses on scaling the performance of monitoring platforms to 10Gb\/s and beyond. Concurrently, IT community focuses on scaling the analysis of big-data over a cluster of nodes. So far, combinations of these approaches have targeted flexibility and usability over real-timeliness of results and efficient allocation of resources. In this paper we show how to meet both objectives with BlockMon, a network monitoring platform originally designed to work on a single node, which we extended to run distributed stream-data analytics tasks. We compare its performance against Storm and Apache S4, the state-of-the-art open-source stream-processing platforms, by implementing a phone call anomaly detection system and a Twitter trending algorithm: our enhanced BlockMon has a gain in performance of over 2.5x and 23x, respectively. Given the different nature of those applications and the performance of BlockMon as single-node network monitor [1], we expect our results to hold for a broad range of applications, making distributed BlockMon a good candidate for the convergence of network-measurement and IT-analysis platforms.<\/jats:p>","DOI":"10.1145\/2479957.2479962","type":"journal-article","created":{"date-parts":[[2013,5,1]],"date-time":"2013-05-01T19:47:09Z","timestamp":1367437629000},"page":"29-36","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":12,"title":["Stream-monitoring with blockmon"],"prefix":"10.1145","volume":"43","author":[{"given":"Davide","family":"Simoncelli","sequence":"first","affiliation":[{"name":"University of Brescia - CNIT, Brescia, Italy"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Maurizio","family":"Dusi","sequence":"additional","affiliation":[{"name":"NEC Laboratories Europe, Heidelberg, Germany"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Francesco","family":"Gringoli","sequence":"additional","affiliation":[{"name":"University of Brescia - CNIT, Brescia, Italy"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Saverio","family":"Niccolini","sequence":"additional","affiliation":[{"name":"NEC Laboratories Europe, Heidelberg, Germany"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"320","published-online":{"date-parts":[[2013,4,29]]},"reference":[{"key":"e_1_2_1_1_1","volume-title":"Proceedings of the IEEE Infocom Conference (mini-conference)","author":"di Pietro A.","year":"2013","unstructured":"A. di Pietro , F. Huici , N. Bonelli , B. Trammell , P. Kastovsky , T. Groleat , S. Vaton , and M. Dusi . Blockmon: Toward high-speed composable network traffic measurement . In Proceedings of the IEEE Infocom Conference (mini-conference) , 2013 . A. di Pietro, F. Huici, N. Bonelli, B. Trammell, P. Kastovsky, T. Groleat, S. Vaton, and M. Dusi. Blockmon: Toward high-speed composable network traffic measurement. In Proceedings of the IEEE Infocom Conference (mini-conference), 2013."},{"key":"e_1_2_1_2_1","volume-title":"Proceeding of the Passive and Active Measurement Conference","author":"Iannaccone G.","year":"2006","unstructured":"G. Iannaccone . Fast prototyping of network data mining applications . In Proceeding of the Passive and Active Measurement Conference , 2006 . G. Iannaccone. Fast prototyping of network data mining applications. 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