東華大學圖書館 |

語系: 繁體中文

說明(常見問題)

回圖書館首頁

手機版館藏查詢

登入

回首頁

切換: 標籤 | MARC模式 | ISBD

Energy-efficient Data Transfer Algor...

Guner, Kemal.

FindBook

Google Book

Amazon

博客來

Energy-efficient Data Transfer Algorithms for Mobile Network I/O.

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	Energy-efficient Data Transfer Algorithms for Mobile Network I/O./
作者:	Guner, Kemal.
出版者:	Ann Arbor : ProQuest Dissertations & Theses, : 2018,
面頁冊數:	127 p.
附註:	Source: Dissertations Abstracts International, Volume: 80-04, Section: B.
Contained By:	Dissertations Abstracts International80-04B.
標題:	Computer Engineering. -
電子資源:	http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=10930747
ISBN:	9780438456525

Energy-efficient Data Transfer Algorithms for Mobile Network I/O.
Guner, Kemal.

Energy-efficient Data Transfer Algorithms for Mobile Network I/O. - Ann Arbor : ProQuest Dissertations & Theses, 2018 - 127 p.

Source: Dissertations Abstracts International, Volume: 80-04, Section: B.

Thesis (Ph.D.)--State University of New York at Buffalo, 2018.

This item must not be added to any third party search indexes.

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.

ISBN: 9780438456525Subjects--Topical Terms:

1567821
Computer Engineering.

Energy-efficient Data Transfer Algorithms for Mobile Network I/O.
LDR:04722nmm a2200337 4500 001 2205620
005 20190828120327.5
008 201008s2018 ||||||||||||||||| ||eng d
020 $a 9780438456525
035 $a (MiAaPQ)AAI10930747
035 $a (MiAaPQ)buffalo:16044
035 $a AAI10930747
040 $a MiAaPQ $c MiAaPQ
100 1 $a Guner, Kemal. $3 3432484
245 1 0 $a Energy-efficient Data Transfer Algorithms for Mobile Network I/O.
260 1 $a Ann Arbor : $b ProQuest Dissertations & Theses, $c 2018
300 $a 127 p.
500 $a Source: Dissertations Abstracts International, Volume: 80-04, Section: B.
500 $a Publisher info.: Dissertation/Thesis.
500 $a Kosar, Tevfik.
502 $a Thesis (Ph.D.)--State University of New York at Buffalo, 2018.
506 $a This item must not be added to any third party search indexes.
506 $a This item must not be sold to any third party vendors.
520 $a 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.
590 $a School code: 0656.
650 4 $a Computer Engineering. $3 1567821
650 4 $a Computer science. $3 523869
690 $a 0464
690 $a 0984
710 2 $a State University of New York at Buffalo. $b Computer Science and Engineering. $3 1035503
773 0 $t Dissertations Abstracts International $g 80-04B.
790 $a 0656
791 $a Ph.D.
792 $a 2018
793 $a English
856 4 0 $u http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=10930747