{"id":{"repo_id":"texas-state","oai_identifier":"oai:digital.library.txst.edu:10877/5896"},"canonical_url":"https://search.dev.ndltd.org/etd/texas-state/oai:digital.library.txst.edu:10877/5896","repository":{"repo_id":"texas-state","name":"Texas State University","base_url":"https://digital.library.txst.edu/server/oai/request"},"display":{"title":"Local Overlay-Based Mobile Clouds","abstract":"The growing capabilities of mobile devices provide a rich computing platform for various applications. Most of these devices have the ability to form a mobile cloud among themselves without relying on an existing infrastructure or a centralized administration whereby each device offer its capabilities as a cloud service for other devices to use. Mobile clouds are useful in scenarios where the deployment of access points is not feasible or expensive (e.g., natural disasters, heavily crowded areas, military operations). In this thesis, we propose a mobile cloud that capitalizes on locality. The mobile cloud provides an efficient collaborative computing framework that enables a group of mobile devices to form an ad-hoc network based on their proximity and advertise their capabilities as cloud services. We propose a hybrid routing algorithm through the combination of reliable flooding and Distributed Hash Tables (DHT) to find the closest nodes that have the desired capabilities for task execution. We evaluated our proposed platform through simulations, and we studied the impact of different factors such as the number of lookup messages generated and the number of lookup hops taken until a response is received. Our results show the feasibility of our proposed mobile cloud platform.","abstract_html":"The growing capabilities of mobile devices provide a rich computing platform for various applications. Most of these devices have the ability to form a mobile cloud among themselves without relying on an existing infrastructure or a centralized administration whereby each device offer its capabilities as a cloud service for other devices to use. Mobile clouds are useful in scenarios where the deployment of access points is not feasible or expensive (e.g., natural disasters, heavily crowded areas, military operations). In this thesis, we propose a mobile cloud that capitalizes on locality. The mobile cloud provides an efficient collaborative computing framework that enables a group of mobile devices to form an ad-hoc network based on their proximity and advertise their capabilities as cloud services. We propose a hybrid routing algorithm through the combination of reliable flooding and Distributed Hash Tables (DHT) to find the closest nodes that have the desired capabilities for task execution. We evaluated our proposed platform through simulations, and we studied the impact of different factors such as the number of lookup messages generated and the number of lookup hops taken until a response is received. Our results show the feasibility of our proposed mobile cloud platform.","abstract_has_math":false,"creators":["Tammineni, Lavanya"],"institution":"Texas State University","degree_name":"Master of Science","degree_level":"Masters","degree_discipline":"Computer Science","degree_department":null,"school":null,"contributors":[],"advisors":["Guirguis, Mina"],"committee_chairs":[],"committee_members":["Gu, Qijun","Chen, Xiao"],"year":2015,"date_issued":"2015-12","date_published":"2015-12","updated_at":"2026-07-27T21:22:47Z","subjects":["mobile ad-hoc networks","P2P networks","location based chord"],"languages":["en"],"rights":[],"rights_urls":[],"identifier_entries":[]},"links":{"outbound_url":"https://hdl.handle.net/10877/5896","outbound_label":"Handle","outbound_source":"dc:identifier.uri"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:contributor.advisor","label":"Advisor","values":["Guirguis, Mina"]},{"key":"dc:contributor.committeemember","label":"Committee Member","values":["Gu, Qijun","Chen, Xiao"]},{"key":"dc:creator","label":"Author","values":["Tammineni, Lavanya"]}]},{"id":"academic_context","label":"Academic Context","entries":[{"key":"dc:date.accessioned","label":"Dc Date Accessioned","values":["2015-12-11T20:36:32Z"]},{"key":"dc:date.available","label":"Dc Date Available","values":["2015-12-11T20:36:32Z"]},{"key":"dc:date.issued","label":"Date","values":["2015-12"]},{"key":"dc:type","label":"Dc Type","values":["Thesis"]},{"key":"thesis:degree_discipline","label":"Discipline","values":["Computer Science"]},{"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":["Texas State University"]}]},{"id":"subjects_keywords","label":"Subjects and Keywords","entries":[{"key":"dc:subject","label":"Dc Subject","values":["mobile ad-hoc networks","P2P networks","location based chord"]}]},{"id":"language_rights","label":"Language and Rights","entries":[{"key":"dc:language.iso","label":"Language (ISO)","values":["en"]}]},{"id":"identifiers","label":"Identifiers","entries":[{"key":"dc:identifier.uri","label":"Identifier URI","values":["https://hdl.handle.net/10877/5896"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description.abstract","label":"Abstract","values":["The growing capabilities of mobile devices provide a rich computing platform for various applications. Most of these devices have the ability to form a mobile cloud among themselves without relying on an existing infrastructure or a centralized administration whereby each device offer its capabilities as a cloud service for other devices to use. Mobile clouds are useful in scenarios where the deployment of access points is not feasible or expensive (e.g., natural disasters, heavily crowded areas, military operations). In this thesis, we propose a mobile cloud that capitalizes on locality. The mobile cloud provides an efficient collaborative computing framework that enables a group of mobile devices to form an ad-hoc network based on their proximity and advertise their capabilities as cloud services. We propose a hybrid routing algorithm through the combination of reliable flooding and Distributed Hash Tables (DHT) to find the closest nodes that have the desired capabilities for task execution. We evaluated our proposed platform through simulations, and we studied the impact of different factors such as the number of lookup messages generated and the number of lookup hops taken until a response is received. Our results show the feasibility of our proposed mobile cloud platform."]},{"key":"dc:format","label":"Dc Format","values":["Text"]},{"key":"dc:format.medium","label":"Dc Format Medium","values":["1 file (.pdf)"]},{"key":"dc:title","label":"Title","values":["Local Overlay-Based Mobile Clouds"]}]}],"canonical_facts":{"dc:contributor.advisor":["Guirguis, Mina"],"dc:contributor.committeemember":["Gu, Qijun","Chen, Xiao"],"dc:creator":["Tammineni, Lavanya"],"dc:date.accessioned":["2015-12-11T20:36:32Z"],"dc:date.available":["2015-12-11T20:36:32Z"],"dc:date.issued":["2015-12"],"dc:description.abstract":["The growing capabilities of mobile devices provide a rich computing platform for various applications. Most of these devices have the ability to form a mobile cloud among themselves without relying on an existing infrastructure or a centralized administration whereby each device offer its capabilities as a cloud service for other devices to use. Mobile clouds are useful in scenarios where the deployment of access points is not feasible or expensive (e.g., natural disasters, heavily crowded areas, military operations). In this thesis, we propose a mobile cloud that capitalizes on locality. The mobile cloud provides an efficient collaborative computing framework that enables a group of mobile devices to form an ad-hoc network based on their proximity and advertise their capabilities as cloud services. We propose a hybrid routing algorithm through the combination of reliable flooding and Distributed Hash Tables (DHT) to find the closest nodes that have the desired capabilities for task execution. 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