This thesis presents a methodology for implementing decentralized scheduling for distributed systems. The environment in which the controlling entities make decisions is stochastic and can be described as uncertain since each entity may have a different view of the system state. As a consequence, these entities may make inconsistent decisions.
The methodology is based on defining the system state as a set of distributions and using a queueing model to predict the future behaviour of the system. The predicted state is used to schedule the individual job tasks based on minimum predicted job response time.
A hypothetical real system is simulated. The methodology was tested using different queueing models and under different environments. An evaluation of the proposed technique using the simulation results indicates a consistent performance improvement over the no network case. Suggestions for extending this research are also presented.
","abstract_html":"<p>This thesis presents a methodology for implementing decentralized scheduling for distributed systems. The environment in which the controlling entities make decisions is stochastic and can be described as uncertain since each entity may have a different view of the system state. As a consequence, these entities may make inconsistent decisions.</p><p>The methodology is based on defining the system state as a set of distributions and using a queueing model to predict the future behaviour of the system. The predicted state is used to schedule the individual job tasks based on minimum predicted job response time.</p><p>A hypothetical real system is simulated. The methodology was tested using different queueing models and under different environments. An evaluation of the proposed technique using the simulation results indicates a consistent performance improvement over the no network case. Suggestions for extending this research are also presented.</p>","abstract_has_math":false,"creators":["EZZAT, AHMED KAMAL"],"institution":null,"degree_name":"Doctor of Philosophy","degree_level":"Dissertation","degree_discipline":null,"degree_department":null,"school":null,"contributors":[],"advisors":[],"committee_chairs":[],"committee_members":[],"year":1982,"date_issued":"1982-01-01T08:00:00Z","date_published":"1982-01-01T08:00:00Z","updated_at":"2026-07-24T05:23:15Z","subjects":["Engineering","System Science"],"languages":[],"rights":[],"rights_urls":[],"identifier_entries":[]},"links":{"outbound_url":"https://scholars.unh.edu/dissertation/1332","outbound_label":"Repository record","outbound_source":"dc:identifier"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:creator","label":"Author","values":["EZZAT, AHMED KAMAL"]}]},{"id":"academic_context","label":"Academic Context","entries":[{"key":"thesis:degree_level","label":"Degree Level","values":["Dissertation"]},{"key":"thesis:degree_name","label":"Degree Name","values":["Doctor of Philosophy"]}]},{"id":"subjects_keywords","label":"Subjects and Keywords","entries":[{"key":"dc:subject","label":"Dc Subject","values":["Engineering","System Science"]}]},{"id":"identifiers","label":"Identifiers","entries":[{"key":"dc:identifier","label":"Identifier","values":["https://scholars.unh.edu/dissertation/1332"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description.abstract","label":"Abstract","values":["This thesis presents a methodology for implementing decentralized scheduling for distributed systems. The environment in which the controlling entities make decisions is stochastic and can be described as uncertain since each entity may have a different view of the system state. As a consequence, these entities may make inconsistent decisions.
The methodology is based on defining the system state as a set of distributions and using a queueing model to predict the future behaviour of the system. The predicted state is used to schedule the individual job tasks based on minimum predicted job response time.
A hypothetical real system is simulated. The methodology was tested using different queueing models and under different environments. An evaluation of the proposed technique using the simulation results indicates a consistent performance improvement over the no network case. Suggestions for extending this research are also presented.
"]},{"key":"dc:title","label":"Title","values":["DECENTRALIZED CONTROL OF DISTRIBUTED PROCESSING SYSTEMS"]}]}],"canonical_facts":{"dc:creator":["EZZAT, AHMED KAMAL"],"dc:description.abstract":["This thesis presents a methodology for implementing decentralized scheduling for distributed systems. The environment in which the controlling entities make decisions is stochastic and can be described as uncertain since each entity may have a different view of the system state. As a consequence, these entities may make inconsistent decisions.
The methodology is based on defining the system state as a set of distributions and using a queueing model to predict the future behaviour of the system. The predicted state is used to schedule the individual job tasks based on minimum predicted job response time.
A hypothetical real system is simulated. The methodology was tested using different queueing models and under different environments. An evaluation of the proposed technique using the simulation results indicates a consistent performance improvement over the no network case. Suggestions for extending this research are also presented.
"],"dc:identifier":["https://scholars.unh.edu/dissertation/1332"],"dc:subject":["Engineering","System Science"],"dc:title":["DECENTRALIZED CONTROL OF DISTRIBUTED PROCESSING SYSTEMS"],"thesis:degree_level":["Dissertation"],"thesis:degree_name":["Doctor of Philosophy"]},"updated_at":"2026-07-24T05:23:15Z"}