{"id":{"repo_id":"buffalo","oai_identifier":"oai:ubir.buffalo.edu:10477/78602"},"canonical_url":"https://search.dev.ndltd.org/etd/buffalo/oai:ubir.buffalo.edu:10477/78602","repository":{"repo_id":"buffalo","name":"Buffalo","base_url":"https://ubir.buffalo.edu/oai/request"},"display":{"title":"Energy-Efficient Data Transfer Algorithms for Mobile Network I/O","abstract":"Ph.D.","abstract_html":"Ph.D.","abstract_has_math":false,"creators":["Guner, Kemal; 0000-0003-3495-9044"],"institution":"State University of New York at Buffalo","degree_name":null,"degree_level":null,"degree_discipline":null,"degree_department":null,"school":null,"contributors":["Kosar, Tevfik","Computer Science and Engineering"],"advisors":[],"committee_chairs":[],"committee_members":[],"year":2018,"date_issued":"2018-10-26T02:56:25Z","date_published":"2018-10-26T02:56:25Z","updated_at":"2026-07-27T19:05:12Z","subjects":["computer science","computer engineering"],"languages":["eng"],"rights":["Users of works found in University at Buffalo Institutional Repository (UBIR) are responsible for identifying and contacting the copyright owner for permission to reuse. University at Buffalo Libraries do not manage rights for copyright-protected works and cannot assist with permissions.","Copyright retained by author."],"rights_urls":[],"identifier_entries":[]},"links":{"outbound_url":"http://hdl.handle.net/10477/78602","outbound_label":"Handle","outbound_source":"dc:identifier"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:contributor","label":"Contributor","values":["Kosar, Tevfik","Computer Science and Engineering"]},{"key":"dc:creator","label":"Author","values":["Guner, Kemal; 0000-0003-3495-9044"]}]},{"id":"academic_context","label":"Academic Context","entries":[{"key":"dc:date","label":"Dc Date","values":["2018-10-26T02:56:25Z","2018","2018-08-09 19:51:57"]},{"key":"dc:publisher","label":"Institution","values":["State University of New York at Buffalo"]},{"key":"dc:type","label":"Dc Type","values":["Text","Dissertation"]}]},{"id":"subjects_keywords","label":"Subjects and Keywords","entries":[{"key":"dc:subject","label":"Dc Subject","values":["computer science","computer engineering"]}]},{"id":"language_rights","label":"Language and Rights","entries":[{"key":"dc:language","label":"Dc Language","values":["eng"]},{"key":"dc:rights","label":"Dc Rights","values":["Users of works found in University at Buffalo Institutional Repository (UBIR) are responsible for identifying and contacting the copyright owner for permission to reuse. University at Buffalo Libraries do not manage rights for copyright-protected works and cannot assist with permissions.","Copyright retained by author."]}]},{"id":"identifiers","label":"Identifiers","entries":[{"key":"dc:identifier","label":"Identifier","values":["http://hdl.handle.net/10477/78602"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description","label":"Description","values":["Ph.D.","By year 2020, the number of smartphone users globally will exceed 3 Billion and the mobile data traffic (cellular + WiFi) will reach 370 Exabytes per year, surpassing the PC internet traffic the first time in the history. As the number of smartphone users and the amount of data transferred per smartphone grow exponentially, limited battery power is becoming an increasingly critical problem for mobile devices which increasingly depend on network I/O. An average smartphone consumes between 300 -- 1200 milliwatts power depending on the type of applications it is running, and most of the energy in smartphone applications is spent for network I/O. During an active data transfer, the cellular (i.e., GSM) and WiFi components of a smartphone consume more power than its CPU, RAM, and even LCD+graphics card at the highest brightness level. Despite the growing body of research in power management techniques for the mobile devices at the hardware layer as well as the lower layers of the networking stack, there has been little work focusing on saving energy at the application layer for the mobile systems during network I/O. In this dissertation, we propose a novel approach for high-performance and low-energy network I/O for mobile deceives through application-layer energy-efficient throughput optimization. To accomplish this objective, we examine and analyze different application-layer protocol parameters that influence the data transfer performance as well as the energy consumption of mobile phones. We show that significant energy savings can be achieved with no or minimal performance penalty on mobile systems during data transfer by intelligently tuning application-layer parameters, such as the level of concurrent file transfers, the number of parallel data streams, TCP pipelining level, and I/O request size. Setting the optimal values for these parameters is a crucially challenging task, since incorrect tuning of these parameters can either cause underutilization of the network, may increase the power-consumption drastically, or may overload the network and degrade the performance due to the increased packet loss ratio, end-system overhead, and other factors. We also show that, in many cases, performance increase and energy savings can be achieved simultaneously. With the knowledge acquired from the in-depth analysis of the effects of application-layer data transfer protocol parameters, we develop five novel data transfer algorithms for different performance and energy consumption goals in consideration: i) Lowest-possible Energy Algorithm which aims to minimize the overall energy consumption without any performance concerns; ii) Energy-aware High Throughput Algorithm which aims to maximize achieved throughput with low energy consumption constraints; iii) Highest-achievable Throughput Algorithm which only aims to maximize the throughput performance without consideration of energy consumption; iv) SLA-based Energy-aware Transfer Algorithm which lets the end-users to maximize energy savings with the promised throughput gain as part of service-level-agreement; and v) Historical-log Analysis Algorithm that outsources the analysis of historical data transfer logs to either an edge server or to the Cloud for various network protocols and platforms which consider energy efficiency and throughput constraints. Our experimental analyses over different testbeds show that our algorithms outperform the state-of-the art solutions in this area considerably in terms of energy saving while keeping the performance at the desired levels."]},{"key":"dc:format","label":"Dc Format","values":["application/pdf"]},{"key":"dc:title","label":"Title","values":["Energy-Efficient Data Transfer Algorithms for Mobile Network I/O"]}]}],"canonical_facts":{"dc:contributor":["Kosar, Tevfik","Computer Science and Engineering"],"dc:creator":["Guner, Kemal; 0000-0003-3495-9044"],"dc:date":["2018-10-26T02:56:25Z","2018","2018-08-09 19:51:57"],"dc:description":["Ph.D.","By year 2020, the number of smartphone users globally will exceed 3 Billion and the mobile data traffic (cellular + WiFi) will reach 370 Exabytes per year, surpassing the PC internet traffic the first time in the history. As the number of smartphone users and the amount of data transferred per smartphone grow exponentially, limited battery power is becoming an increasingly critical problem for mobile devices which increasingly depend on network I/O. An average smartphone consumes between 300 -- 1200 milliwatts power depending on the type of applications it is running, and most of the energy in smartphone applications is spent for network I/O. During an active data transfer, the cellular (i.e., GSM) and WiFi components of a smartphone consume more power than its CPU, RAM, and even LCD+graphics card at the highest brightness level. Despite the growing body of research in power management techniques for the mobile devices at the hardware layer as well as the lower layers of the networking stack, there has been little work focusing on saving energy at the application layer for the mobile systems during network I/O. In this dissertation, we propose a novel approach for high-performance and low-energy network I/O for mobile deceives through application-layer energy-efficient throughput optimization. To accomplish this objective, we examine and analyze different application-layer protocol parameters that influence the data transfer performance as well as the energy consumption of mobile phones. We show that significant energy savings can be achieved with no or minimal performance penalty on mobile systems during data transfer by intelligently tuning application-layer parameters, such as the level of concurrent file transfers, the number of parallel data streams, TCP pipelining level, and I/O request size. Setting the optimal values for these parameters is a crucially challenging task, since incorrect tuning of these parameters can either cause underutilization of the network, may increase the power-consumption drastically, or may overload the network and degrade the performance due to the increased packet loss ratio, end-system overhead, and other factors. We also show that, in many cases, performance increase and energy savings can be achieved simultaneously. With the knowledge acquired from the in-depth analysis of the effects of application-layer data transfer protocol parameters, we develop five novel data transfer algorithms for different performance and energy consumption goals in consideration: i) Lowest-possible Energy Algorithm which aims to minimize the overall energy consumption without any performance concerns; ii) Energy-aware High Throughput Algorithm which aims to maximize achieved throughput with low energy consumption constraints; iii) Highest-achievable Throughput Algorithm which only aims to maximize the throughput performance without consideration of energy consumption; iv) SLA-based Energy-aware Transfer Algorithm which lets the end-users to maximize energy savings with the promised throughput gain as part of service-level-agreement; and v) Historical-log Analysis Algorithm that outsources the analysis of historical data transfer logs to either an edge server or to the Cloud for various network protocols and platforms which consider energy efficiency and throughput constraints. Our experimental analyses over different testbeds show that our algorithms outperform the state-of-the art solutions in this area considerably in terms of energy saving while keeping the performance at the desired levels."],"dc:format":["application/pdf"],"dc:identifier":["http://hdl.handle.net/10477/78602"],"dc:language":["eng"],"dc:publisher":["State University of New York at Buffalo"],"dc:rights":["Users of works found in University at Buffalo Institutional Repository (UBIR) are responsible for identifying and contacting the copyright owner for permission to reuse. University at Buffalo Libraries do not manage rights for copyright-protected works and cannot assist with permissions.","Copyright retained by author."],"dc:subject":["computer science","computer engineering"],"dc:title":["Energy-Efficient Data Transfer Algorithms for Mobile Network I/O"],"dc:type":["Text","Dissertation"]},"updated_at":"2026-07-27T19:05:12Z"}