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RBT-MF: a Distributed Rubber Band Technique for Maximum Flow Problem in Azure
Univ Sydney, Sch Informat Technol, Ctr Distributed & High Performance Comp, Sydney, NSW 2006, Australia..
Karlstad University, Faculty of Health, Science and Technology (starting 2013), Department of Mathematics and Computer Science. (DIStributed Systems and Communications Research Group (DISCO))ORCID iD: 0000-0001-9194-010X
Univ Sydney, Sch Informat Technol, Ctr Distributed & High Performance Comp, Sydney, NSW 2006, Australia..
2016 (English)In: PROCEEDINGS OF 2016 IEEE 18TH INTERNATIONAL CONFERENCE ON HIGH PERFORMANCE COMPUTING AND COMMUNICATIONS; IEEE 14TH INTERNATIONAL CONFERENCE ON SMART CITY; IEEE 2ND INTERNATIONAL CONFERENCE ON DATA SCIENCE AND SYSTEMS (HPCC/SMARTCITY/DSS) / [ed] Chen, J Yang, LT, IEEE, 2016, 489-496 p.Conference paper, Published paper (Refereed)
Abstract [en]

In this paper, we present a novel approach based on a rubber band technique to solve the " maximum flow" problem for a single-source, single-sink directed graph implemented on the Microsoft Azure cloud platform. The problem of finding the maximum possible flow for a given graph is a classic network optimization problem that arises in several real life circumstances. Having proposed several solutions to this problem in traditional distributed platforms, a solution that explicitly takes advantage of the cloud paradigm has not yet been thoroughly investigated. The rubber band technique, which is inspired by the behavior of an elastic rubber band on a plate with several poles, has been exploited in this paper to design a solution to the problem. Our experimental results show that the proposed technique can effectively find an answer for the maximum flow problem in a graph. As the size of the graph in terms of number of nodes, number of edges and flow value increase, the proposed scheme outperforms in comparison to the selected benchmarks.

Place, publisher, year, edition, pages
IEEE, 2016. 489-496 p.
Keyword [en]
Rubber Band Technique, Max-Flow Problem, Platform as a Service (PaaS), Microsoft Azure
National Category
Computer and Information Sciences
Research subject
Computer Science
Identifiers
URN: urn:nbn:se:kau:diva-65092DOI: 10.1109/HPCC-SmartCity-DSS.2016.168ISI: 000401700900065ISBN: 978-1-5090-4297-5 OAI: oai:DiVA.org:kau-65092DiVA: diva2:1154367
Conference
18th IEEE International Conference on High Performance Computing and Communications (HPCC) / 14th IEEE International Conference on Smart City (Smart City) / 2nd IEEE International Conference on Data Science and Systems (DSS), DEC 12-14, 2016, Sydney, AUSTRALIA
Available from: 2017-11-02 Created: 2017-11-02 Last updated: 2017-11-06Bibliographically approved

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