{"id":{"repo_id":"vt","oai_identifier":"oai:vtechworks.lib.vt.edu:10919/54546"},"canonical_url":"https://search.dev.ndltd.org/etd/vt/oai:vtechworks.lib.vt.edu:10919/54546","repository":{"repo_id":"vt","name":"Virginia Tech","base_url":"https://vtechworks.lib.vt.edu/oai/request"},"display":{"title":"On the Feasibility of MapReduce to Compute Phase Space Properties of Graphical Dynamical Systems: An Empirical Study","abstract":"A graph dynamical system (GDS) is a theoretical construct that can be used to simulate and analyze the dynamics of a wide spectrum of real world processes which can be modeled as networked systems. One of our goals is to compute the phase space of a system, and for this, even 30-vertex graphs present a computational challenge. This is because the number of state transitions needed to compute the phase space is exponential in the number of graph vertices. These problems thus produce memory and execution speed challenges. To address this, we devise various MapReduce programming paradigms that can be used to characterize system state transitions, compute phase spaces, functional equivalence classes, dynamic equivalence classes and cycle equivalence classes of dynamical systems. We also evaluate these paradigms and analyze their suitability for modeling different GDSs.","abstract_html":"A graph dynamical system (GDS) is a theoretical construct that can be used to simulate and analyze the dynamics of a wide spectrum of real world processes which can be modeled as networked systems. One of our goals is to compute the phase space of a system, and for this, even 30-vertex graphs present a computational challenge. This is because the number of state transitions needed to compute the phase space is exponential in the number of graph vertices. These problems thus produce memory and execution speed challenges. To address this, we devise various MapReduce programming paradigms that can be used to characterize system state transitions, compute phase spaces, functional equivalence classes, dynamic equivalence classes and cycle equivalence classes of dynamical systems. We also evaluate these paradigms and analyze their suitability for modeling different GDSs.","abstract_has_math":false,"creators":["Hamid, Tania"],"institution":"Virginia Tech","degree_name":"Master of Science","degree_level":"masters","degree_discipline":"Computer Science and Applications","degree_department":"Computer Science","school":null,"contributors":[],"advisors":[],"committee_chairs":["Marathe, Madhav Vishnu","Kuhlman, Christopher James"],"committee_members":["Ribbens, Calvin J.","Vullikanti, Anil Kumar S."],"year":2015,"date_issued":"2015-07-09","date_published":"2015-07-09","updated_at":"2026-07-22T22:18:42Z","subjects":["Graph Dynamical Systems","GDS","MapReduce","Map","Reduce","Hadoop"],"languages":[],"rights":["In Copyright"],"rights_urls":["http://rightsstatements.org/vocab/InC/1.0/"],"identifier_entries":[{"key":"dc:identifier.other","label":"Dc Identifier Other","values":["vt_gsexam:5808"],"render_values":[{"text":"vt_gsexam:5808","href":null,"code":true}]}]},"links":{"outbound_url":"http://hdl.handle.net/10919/54546","outbound_label":"Handle","outbound_source":"dc:identifier.uri"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:contributor.committeechair","label":"Committee Chair","values":["Marathe, Madhav Vishnu","Kuhlman, Christopher James"]},{"key":"dc:contributor.committeemember","label":"Committee Member","values":["Ribbens, Calvin J.","Vullikanti, Anil Kumar S."]},{"key":"dc:contributor.department","label":"Department","values":["Computer Science"]},{"key":"dc:creator","label":"Author","values":["Hamid, Tania"]}]},{"id":"academic_context","label":"Academic Context","entries":[{"key":"dc:date.accessioned","label":"Dc Date Accessioned","values":["2015-07-11T08:01:09Z"]},{"key":"dc:date.available","label":"Dc Date Available","values":["2015-07-11T08:01:09Z"]},{"key":"dc:date.issued","label":"Date","values":["2015-07-09"]},{"key":"dc:publisher","label":"Institution","values":["Virginia Tech"]},{"key":"dc:type","label":"Dc Type","values":["Thesis"]},{"key":"thesis:degree_discipline","label":"Discipline","values":["Computer Science and Applications"]},{"key":"thesis:degree_level","label":"Degree Level","values":["masters"]},{"key":"thesis:degree_name","label":"Degree Name","values":["Master of Science"]},{"key":"thesis:institution_name","label":"Thesis Institution Name","values":["Virginia Polytechnic Institute and State University"]}]},{"id":"subjects_keywords","label":"Subjects and Keywords","entries":[{"key":"dc:subject","label":"Dc Subject","values":["Graph Dynamical Systems","GDS","MapReduce","Map","Reduce","Hadoop"]}]},{"id":"language_rights","label":"Language and Rights","entries":[{"key":"dc:rights","label":"Dc Rights","values":["In Copyright"]},{"key":"dc:rights.uri","label":"Rights URI","values":["http://rightsstatements.org/vocab/InC/1.0/"]}]},{"id":"identifiers","label":"Identifiers","entries":[{"key":"dc:identifier.other","label":"Dc Identifier Other","values":["vt_gsexam:5808"]},{"key":"dc:identifier.uri","label":"Identifier URI","values":["http://hdl.handle.net/10919/54546"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description.abstract","label":"Abstract","values":["A graph dynamical system (GDS) is a theoretical construct that can be used to simulate and analyze the dynamics of a wide spectrum of real world processes which can be modeled as networked systems. One of our goals is to compute the phase space of a system, and for this, even 30-vertex graphs present a computational challenge. This is because the number of state transitions needed to compute the phase space is exponential in the number of graph vertices. These problems thus produce memory and execution speed challenges. To address this, we devise various MapReduce programming paradigms that can be used to characterize system state transitions, compute phase spaces, functional equivalence classes, dynamic equivalence classes and cycle equivalence classes of dynamical systems. We also evaluate these paradigms and analyze their suitability for modeling different GDSs."]},{"key":"dc:description.degree","label":"Dc Description Degree","values":["Master of Science"]},{"key":"dc:format.medium","label":"Dc Format Medium","values":["ETD"]},{"key":"dc:title","label":"Title","values":["On the Feasibility of MapReduce to Compute Phase Space Properties of Graphical Dynamical Systems: An Empirical Study"]}]}],"canonical_facts":{"dc:contributor.committeechair":["Marathe, Madhav Vishnu","Kuhlman, Christopher James"],"dc:contributor.committeemember":["Ribbens, Calvin J.","Vullikanti, Anil Kumar S."],"dc:contributor.department":["Computer Science"],"dc:creator":["Hamid, Tania"],"dc:date.accessioned":["2015-07-11T08:01:09Z"],"dc:date.available":["2015-07-11T08:01:09Z"],"dc:date.issued":["2015-07-09"],"dc:description.abstract":["A graph dynamical system (GDS) is a theoretical construct that can be used to simulate and analyze the dynamics of a wide spectrum of real world processes which can be modeled as networked systems. One of our goals is to compute the phase space of a system, and for this, even 30-vertex graphs present a computational challenge. This is because the number of state transitions needed to compute the phase space is exponential in the number of graph vertices. These problems thus produce memory and execution speed challenges. To address this, we devise various MapReduce programming paradigms that can be used to characterize system state transitions, compute phase spaces, functional equivalence classes, dynamic equivalence classes and cycle equivalence classes of dynamical systems. 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