語系:
繁體中文
English
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
Decentralized Runtime Architecture D...
~
Porter, Jason.
FindBook
Google Book
Amazon
博客來
Decentralized Runtime Architecture Discovery and Testbed for Adaptation and Failure Recovery of Large Dynamic Distributed Systems.
紀錄類型:
書目-電子資源 : Monograph/item
正題名/作者:
Decentralized Runtime Architecture Discovery and Testbed for Adaptation and Failure Recovery of Large Dynamic Distributed Systems./
作者:
Porter, Jason.
出版者:
Ann Arbor : ProQuest Dissertations & Theses, : 2018,
面頁冊數:
129 p.
附註:
Source: Dissertations Abstracts International, Volume: 80-01, Section: B.
Contained By:
Dissertations Abstracts International80-01B.
標題:
Computer science. -
電子資源:
http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=10811923
ISBN:
9780438115019
Decentralized Runtime Architecture Discovery and Testbed for Adaptation and Failure Recovery of Large Dynamic Distributed Systems.
Porter, Jason.
Decentralized Runtime Architecture Discovery and Testbed for Adaptation and Failure Recovery of Large Dynamic Distributed Systems.
- Ann Arbor : ProQuest Dissertations & Theses, 2018 - 129 p.
Source: Dissertations Abstracts International, Volume: 80-01, Section: B.
Thesis (Ph.D.)--George Mason University, 2018.
This item must not be added to any third party search indexes.
Runtime models play a critical role in modern self-adaptive systems. Hence, runtime architectural models are needed when making adaptation decisions in architecture-based self-adaptive systems. However, when these systems are distributed and highly dynamic, there is an added need to discover the system's software architecture model at runtime. Current methods of runtime architecture discovery use a centralized approach, in which the process is carried out from a single location. These methods are inadequate for large distributed systems because they do not scale up well and have a single point of failure. Also, systems of such size consist of nodes that are typically highly dynamic in nature. Existing approaches to architecture discovery are not capable of addressing these concerns. This dissertation describes DeSARM (Decentralized Software Architecture discoveRy Mechanism), a completely decentralized and automated approach for runtime discovery of software architecture models of distributed systems based on gossiping and message tracing. DeSARM is able to identify at runtime important architectural characteristics such as components and connectors, in addition to synchronous and asynchronous communication patterns. Furthermore, through its use of gossiping, it exhibits the properties of scalability, global consistency among participating nodes, and resiliency to failures. This dissertation describes DeSARM's architecture, algorithms and design, and demonstrates its properties through experimentation. In addition, this dissertation describes the design of a distributed testbed called TESS (Testbed for Evaluation of Self-healing and Self-adaptive distributed software systems). TESS allows for the automated generation and instantiation of random architectures on which experiments may be conducted for issues such as adaptation and failure recovery of distributed software systems. Metrics are automatically collected from the experiments and stored in a database for later analysis. TESS was developed to evaluate recovery and adaptation frameworks (RAFs) as well as other capabilities such as DeSARM's architecture discovery mechanism.
ISBN: 9780438115019Subjects--Topical Terms:
523869
Computer science.
Decentralized Runtime Architecture Discovery and Testbed for Adaptation and Failure Recovery of Large Dynamic Distributed Systems.
LDR
:03354nmm a2200325 4500
001
2205559
005
20190828120315.5
008
201008s2018 ||||||||||||||||| ||eng d
020
$a
9780438115019
035
$a
(MiAaPQ)AAI10811923
035
$a
(MiAaPQ)gmu:11716
035
$a
AAI10811923
040
$a
MiAaPQ
$c
MiAaPQ
100
1
$a
Porter, Jason.
$3
614870
245
1 0
$a
Decentralized Runtime Architecture Discovery and Testbed for Adaptation and Failure Recovery of Large Dynamic Distributed Systems.
260
1
$a
Ann Arbor :
$b
ProQuest Dissertations & Theses,
$c
2018
300
$a
129 p.
500
$a
Source: Dissertations Abstracts International, Volume: 80-01, Section: B.
500
$a
Publisher info.: Dissertation/Thesis.
500
$a
Menasce, Daniel A.;Gomaa, Hassan.
502
$a
Thesis (Ph.D.)--George Mason University, 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
Runtime models play a critical role in modern self-adaptive systems. Hence, runtime architectural models are needed when making adaptation decisions in architecture-based self-adaptive systems. However, when these systems are distributed and highly dynamic, there is an added need to discover the system's software architecture model at runtime. Current methods of runtime architecture discovery use a centralized approach, in which the process is carried out from a single location. These methods are inadequate for large distributed systems because they do not scale up well and have a single point of failure. Also, systems of such size consist of nodes that are typically highly dynamic in nature. Existing approaches to architecture discovery are not capable of addressing these concerns. This dissertation describes DeSARM (Decentralized Software Architecture discoveRy Mechanism), a completely decentralized and automated approach for runtime discovery of software architecture models of distributed systems based on gossiping and message tracing. DeSARM is able to identify at runtime important architectural characteristics such as components and connectors, in addition to synchronous and asynchronous communication patterns. Furthermore, through its use of gossiping, it exhibits the properties of scalability, global consistency among participating nodes, and resiliency to failures. This dissertation describes DeSARM's architecture, algorithms and design, and demonstrates its properties through experimentation. In addition, this dissertation describes the design of a distributed testbed called TESS (Testbed for Evaluation of Self-healing and Self-adaptive distributed software systems). TESS allows for the automated generation and instantiation of random architectures on which experiments may be conducted for issues such as adaptation and failure recovery of distributed software systems. Metrics are automatically collected from the experiments and stored in a database for later analysis. TESS was developed to evaluate recovery and adaptation frameworks (RAFs) as well as other capabilities such as DeSARM's architecture discovery mechanism.
590
$a
School code: 0883.
650
4
$a
Computer science.
$3
523869
690
$a
0984
710
2
$a
George Mason University.
$b
Computer Science.
$3
2097804
773
0
$t
Dissertations Abstracts International
$g
80-01B.
790
$a
0883
791
$a
Ph.D.
792
$a
2018
793
$a
English
856
4 0
$u
http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=10811923
筆 0 讀者評論
館藏地:
全部
電子資源
出版年:
卷號:
館藏
1 筆 • 頁數 1 •
1
條碼號
典藏地名稱
館藏流通類別
資料類型
索書號
使用類型
借閱狀態
預約狀態
備註欄
附件
W9382108
電子資源
11.線上閱覽_V
電子書
EB
一般使用(Normal)
在架
0
1 筆 • 頁數 1 •
1
多媒體
評論
新增評論
分享你的心得
Export
取書館
處理中
...
變更密碼
登入