{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2024,7,12]],"date-time":"2024-07-12T13:56:15Z","timestamp":1720792575353},"reference-count":18,"publisher":"Association for Computing Machinery (ACM)","issue":"5","license":[{"start":{"date-parts":[[2019,1,28]],"date-time":"2019-01-28T00:00:00Z","timestamp":1548633600000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/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":[[2019,1,28]]},"abstract":"Max-min fair is widely used in network traffic engineering to allocate available resources among different traffic transfers. Recently, as data replication technique developed, increasing systems enforce multi-source transmission to maximize network utilization. However, existing TE approaches fail to deal with multi-source transfers because the optimization becomes a joint problem of bandwidth allocation as well as flow assignment among different sources. In this paper, we present a novel allocation approach for multi-source transfers to achieve global max-min fairness. The joint bandwidth allocation and flow assignment optimization problem poses a major challenge due to nonlinearity and multiple objectives. We cope with this by deriving a novel transformation with simple equivalent canonical linear programming to achieve global optimality efficiently. We conduct data-driven simulations, showing that our approach is more max-min fair than other single-source and multi-source allocation approaches, meanwhile it outperforms others with substantial gains in terms of network throughput and transfer completion time.<\/jats:p>","DOI":"10.1145\/3310165.3310167","type":"journal-article","created":{"date-parts":[[2019,1,29]],"date-time":"2019-01-29T13:16:22Z","timestamp":1548767782000},"page":"2-8","update-policy":"http:\/\/dx.doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":5,"title":["On max-min fair allocation for multi-source transmission"],"prefix":"10.1145","volume":"48","author":[{"given":"Geng","family":"Li","sequence":"first","affiliation":[{"name":"Yale University and Tongji University"}]},{"given":"Yichen","family":"Qian","sequence":"additional","affiliation":[{"name":"Tongji University"}]},{"given":"Y. 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