{"id":{"repo_id":"helsinki","oai_identifier":"oai:helda.helsinki.fi:10138/230796"},"canonical_url":"https://search.dev.ndltd.org/etd/helsinki/oai:helda.helsinki.fi:10138/230796","repository":{"repo_id":"helsinki","name":"University of Helsinki","base_url":"https://helda.helsinki.fi/server/oai/request"},"display":{"title":"Replication-based Load Balancing in Distributed Content-Based Publish /Subscribe Systems","abstract":"In recent years, content-based Publish/Subscribe (pub/sub) has become a popular paradigm to decouple content producers and consumers for Internet-scale content services. Many real applications show that the content workloads frequently follow very skewed distribution, and incur unbalanced workloads. To balance the workloads, the current content-based Publish/Subscribe systems normally adopt a migration scheme (Mis) to move (a subset of) subscription filters from overloaded brokers to underloaded brokers. In this way, the publications that successfully match the moved filters are then o oaded, leading to balanced workloads. Unfortunately, the Mis scheme cannot reduce the overall matching workloads. In the worse case, suppose that all brokers su er from heavy workloads. Mis cannot find available brokers to o oad the heavy workloads of those overloaded brokers, and fail to balance the workloads of the overloaded brokers. To overcome the issue, we develop a set of novel load balancing algorithms, namely a similarity-based replication scheme (Sir). The novelty of Sir is that it not only balances the workloads of brokers but also reduces the overall workloads. Based on both simulation and emulation results, the extensive experiments verify that Sir can achieve much better performance than Mis, in terms of 43.10% higher entropy value (i.e., more balanced workloads) and 46.39% lower workloads.","abstract_html":"In recent years, content-based Publish/Subscribe (pub/sub) has become a popular paradigm to decouple content producers and consumers for Internet-scale content services. Many real applications show that the content workloads frequently follow very skewed distribution, and incur unbalanced workloads. To balance the workloads, the current content-based Publish/Subscribe systems normally adopt a migration scheme (Mis) to move (a subset of) subscription filters from overloaded brokers to underloaded brokers. In this way, the publications that successfully match the moved filters are then o oaded, leading to balanced workloads. Unfortunately, the Mis scheme cannot reduce the overall matching workloads. In the worse case, suppose that all brokers su er from heavy workloads. Mis cannot find available brokers to o oad the heavy workloads of those overloaded brokers, and fail to balance the workloads of the overloaded brokers. To overcome the issue, we develop a set of novel load balancing algorithms, namely a similarity-based replication scheme (Sir). The novelty of Sir is that it not only balances the workloads of brokers but also reduces the overall workloads. Based on both simulation and emulation results, the extensive experiments verify that Sir can achieve much better performance than Mis, in terms of 43.10% higher entropy value (i.e., more balanced workloads) and 46.39% lower workloads.","abstract_has_math":false,"creators":["Chao, Chen"],"institution":"Helsingfors universitet","degree_name":null,"degree_level":null,"degree_discipline":null,"degree_department":null,"school":null,"contributors":["Helsingin yliopisto, Matemaattis-luonnontieteellinen tiedekunta, Tietojenkäsittelytieteen laitos","University of Helsinki, Faculty of Science, Department of Computer Science","Helsingfors universitet, Matematisk-naturvetenskapliga fakulteten, Institutionen för datavetenskap"],"advisors":[],"committee_chairs":[],"committee_members":[],"year":2012,"date_issued":"2012","date_published":"2012","updated_at":"2026-07-27T19:56:09Z","subjects":[],"languages":["eng"],"rights":[],"rights_urls":[],"identifier_entries":[{"key":"dc:identifier.uri","label":"Identifier URI","values":["URN:NBN:fi-fe2017112252489"],"render_values":[{"text":"URN:NBN:fi-fe2017112252489","href":null,"code":true}]}]},"links":{"outbound_url":"http://hdl.handle.net/10138/230796","outbound_label":"Handle","outbound_source":"dc:identifier.uri"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:contributor","label":"Contributor","values":["Helsingin yliopisto, Matemaattis-luonnontieteellinen tiedekunta, Tietojenkäsittelytieteen laitos","University of Helsinki, Faculty of Science, Department of Computer Science","Helsingfors universitet, Matematisk-naturvetenskapliga fakulteten, Institutionen för datavetenskap"]},{"key":"dc:creator","label":"Author","values":["Chao, Chen"]}]},{"id":"academic_context","label":"Academic Context","entries":[{"key":"dc:date.issued","label":"Date","values":["2012"]},{"key":"dc:publisher","label":"Institution","values":["Helsingfors universitet","University of Helsinki","Helsingin yliopisto"]}]},{"id":"language_rights","label":"Language and Rights","entries":[{"key":"dc:language.iso","label":"Language (ISO)","values":["eng"]}]},{"id":"identifiers","label":"Identifiers","entries":[{"key":"dc:identifier.uri","label":"Identifier URI","values":["URN:NBN:fi-fe2017112252489","http://hdl.handle.net/10138/230796"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description.abstract","label":"Abstract","values":["In recent years, content-based Publish/Subscribe (pub/sub) has become a popular paradigm to decouple content producers and consumers for Internet-scale content services. Many real applications show that the content workloads frequently follow very skewed distribution, and incur unbalanced workloads. To balance the workloads, the current content-based Publish/Subscribe systems normally adopt a migration scheme (Mis) to move (a subset of) subscription filters from overloaded brokers to underloaded brokers. In this way, the publications that successfully match the moved filters are then o oaded, leading to balanced workloads. Unfortunately, the Mis scheme cannot reduce the overall matching workloads. In the worse case, suppose that all brokers su er from heavy workloads. Mis cannot find available brokers to o oad the heavy workloads of those overloaded brokers, and fail to balance the workloads of the overloaded brokers. To overcome the issue, we develop a set of novel load balancing algorithms, namely a similarity-based replication scheme (Sir). The novelty of Sir is that it not only balances the workloads of brokers but also reduces the overall workloads. Based on both simulation and emulation results, the extensive experiments verify that Sir can achieve much better performance than Mis, in terms of 43.10% higher entropy value (i.e., more balanced workloads) and 46.39% lower workloads."]},{"key":"dc:title","label":"Title","values":["Replication-based Load Balancing in Distributed Content-Based Publish /Subscribe Systems"]}]}],"canonical_facts":{"dc:contributor":["Helsingin yliopisto, Matemaattis-luonnontieteellinen tiedekunta, Tietojenkäsittelytieteen laitos","University of Helsinki, Faculty of Science, Department of Computer Science","Helsingfors universitet, Matematisk-naturvetenskapliga fakulteten, Institutionen för datavetenskap"],"dc:creator":["Chao, Chen"],"dc:date.issued":["2012"],"dc:description.abstract":["In recent years, content-based Publish/Subscribe (pub/sub) has become a popular paradigm to decouple content producers and consumers for Internet-scale content services. Many real applications show that the content workloads frequently follow very skewed distribution, and incur unbalanced workloads. To balance the workloads, the current content-based Publish/Subscribe systems normally adopt a migration scheme (Mis) to move (a subset of) subscription filters from overloaded brokers to underloaded brokers. In this way, the publications that successfully match the moved filters are then o oaded, leading to balanced workloads. Unfortunately, the Mis scheme cannot reduce the overall matching workloads. In the worse case, suppose that all brokers su er from heavy workloads. Mis cannot find available brokers to o oad the heavy workloads of those overloaded brokers, and fail to balance the workloads of the overloaded brokers. To overcome the issue, we develop a set of novel load balancing algorithms, namely a similarity-based replication scheme (Sir). The novelty of Sir is that it not only balances the workloads of brokers but also reduces the overall workloads. Based on both simulation and emulation results, the extensive experiments verify that Sir can achieve much better performance than Mis, in terms of 43.10% higher entropy value (i.e., more balanced workloads) and 46.39% lower workloads."],"dc:identifier.uri":["URN:NBN:fi-fe2017112252489","http://hdl.handle.net/10138/230796"],"dc:language.iso":["eng"],"dc:publisher":["Helsingfors universitet","University of Helsinki","Helsingin yliopisto"],"dc:title":["Replication-based Load Balancing in Distributed Content-Based Publish /Subscribe Systems"]},"updated_at":"2026-07-27T19:56:09Z"}