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

FindBook

Google Book

Amazon

博客來

Application-Oriented Scheduling for Optimizing Information Freshness in Wireless Networks.

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	Application-Oriented Scheduling for Optimizing Information Freshness in Wireless Networks./
作者:	Yin, Bo.
出版者:	Ann Arbor : ProQuest Dissertations & Theses, : 2020,
面頁冊數:	80 p.
附註:	Source: Dissertations Abstracts International, Volume: 82-03, Section: B.
Contained By:	Dissertations Abstracts International82-03B.
標題:	Computer engineering. -
電子資源:	http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=28028546
ISBN:	9798664779394

Application-Oriented Scheduling for Optimizing Information Freshness in Wireless Networks.
Yin, Bo.

Application-Oriented Scheduling for Optimizing Information Freshness in Wireless Networks. - Ann Arbor : ProQuest Dissertations & Theses, 2020 - 80 p.

Source: Dissertations Abstracts International, Volume: 82-03, Section: B.

Thesis (Ph.D.)--Illinois Institute of Technology, 2020.

This item must not be sold to any third party vendors.

Recent years have witnessed a significant advancement of networking technologies as well as the proliferation of mobile devices. Due to the convergence of pervasive connectivity and ubiquitous computing, Internet of Things (IoT) systems are becoming increasingly information-centric. For those IoT devices, wireless communication is the dominant way to exchange information. The development of IoT has spawned a plethora of real-time applications, boosting the demand for timely information updates. Age of Information (AoI) has recently been introduced to quantify the freshness of the knowledge the controller has about the remote information sources. Due to its sheer novelty in capturing the timeliness requirements of various applications, AoI has sparked tremendous interest and been studied in many communication systems. This thesis aims at an exploratory study on how to characterize the essence of wireless scheduling for effective information freshness from the decision-making perspectives through two representative application scenarios, information retrieval and information integration. For the former, request-aware proactive scheduling policies in both static and dynamic request patterns are developed, which target at minimizing time-average effective AoI (EAoI). For the latter, an experience-driven scheduling framework based on deep reinforcement learning techniques is investigated to minimize the time-average AoI in the presence of correlated information sources. Future research directions are also discussed to present possible extensions of this thesis work to a broader range of network scenarios.

ISBN: 9798664779394Subjects--Topical Terms:

621879
Computer engineering.
Subjects--Index Terms:

Age of information

Application-Oriented Scheduling for Optimizing Information Freshness in Wireless Networks.
LDR:02843nmm a2200373 4500 001 2344579
005 20220531064558.5
008 241004s2020 ||||||||||||||||| ||eng d
020 $a 9798664779394
035 $a (MiAaPQ)AAI28028546
035 $a AAI28028546
040 $a MiAaPQ $c MiAaPQ
100 1 $a Yin, Bo. $3 1948851
245 1 0 $a Application-Oriented Scheduling for Optimizing Information Freshness in Wireless Networks.
260 1 $a Ann Arbor : $b ProQuest Dissertations & Theses, $c 2020
300 $a 80 p.
500 $a Source: Dissertations Abstracts International, Volume: 82-03, Section: B.
500 $a Advisor: Cheng, Yu.
502 $a Thesis (Ph.D.)--Illinois Institute of Technology, 2020.
506 $a This item must not be sold to any third party vendors.
520 $a Recent years have witnessed a significant advancement of networking technologies as well as the proliferation of mobile devices. Due to the convergence of pervasive connectivity and ubiquitous computing, Internet of Things (IoT) systems are becoming increasingly information-centric. For those IoT devices, wireless communication is the dominant way to exchange information. The development of IoT has spawned a plethora of real-time applications, boosting the demand for timely information updates. Age of Information (AoI) has recently been introduced to quantify the freshness of the knowledge the controller has about the remote information sources. Due to its sheer novelty in capturing the timeliness requirements of various applications, AoI has sparked tremendous interest and been studied in many communication systems. This thesis aims at an exploratory study on how to characterize the essence of wireless scheduling for effective information freshness from the decision-making perspectives through two representative application scenarios, information retrieval and information integration. For the former, request-aware proactive scheduling policies in both static and dynamic request patterns are developed, which target at minimizing time-average effective AoI (EAoI). For the latter, an experience-driven scheduling framework based on deep reinforcement learning techniques is investigated to minimize the time-average AoI in the presence of correlated information sources. Future research directions are also discussed to present possible extensions of this thesis work to a broader range of network scenarios.
590 $a School code: 0091.
650 4 $a Computer engineering. $3 621879
650 4 $a Information technology. $3 532993
653 $a Age of information
653 $a Information correlation
653 $a Information freshness
653 $a Information rRetrieval
653 $a Wireless networks
653 $a Wireless scheduling
690 $a 0464
690 $a 0489
710 2 $a Illinois Institute of Technology. $b Electrical and Computer Engineering. $3 2094779
773 0 $t Dissertations Abstracts International $g 82-03B.
790 $a 0091
791 $a Ph.D.
792 $a 2020
793 $a English
856 4 0 $u http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=28028546