Self-Management for Large-Scale Distributed Systems

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Fältnamn	Indikatorer	Metadata
000		05972nam a2200541 4500
001		oai:DiVA.org:kth-101661
003		SwePub
008		120830s2012 \| \|\|\|\|\|\|\|\|\|\|\|000 \|\|eng\|
009		oai:DiVA.org:ri-24046
020		a 9789175014371q print
024	7	a https://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-1016612 URI
024	7	a https://urn.kb.se/resolve?urn=urn:nbn:se:ri:diva-240462 URI
040		a (SwePub)kthd (SwePub)ri
041		a engb eng
042		9 SwePub
072	7	a vet2 swepub-contenttype
072	7	a dok2 swepub-publicationtype
100	1	a Al-Shishtawy, Ahmad,d 1978-u RISE,KTH,Programvaruteknik och Datorsystem, SCS,Computer Systems Laboratory4 aut0 (Swepub:ri)AhmadAl@ri.se
245	1 0	a Self-Management for Large-Scale Distributed Systems
264	1	a Stockholm :b KTH Royal Institute of Technology,c 2012
300		a xix, 266 s.
338		a electronic2 rdacarrier
490	0	a SICS dissertation series,x 1101-1335 ;v 57
500		a QC 20120831
520		a Autonomic computing aims at making computing systems self-managing by using autonomic managers in order to reduce obstacles caused by management complexity. This thesis presents results of research on self-management for large-scale distributed systems. This research was motivated by the increasing complexity of computing systems and their management.In the first part, we present our platform, called Niche, for programming self-managing component-based distributed applications. In our work on Niche, we have faced and addressed the following four challenges in achieving self-management in a dynamic environment characterized by volatile resources and high churn: resource discovery, robust and efficient sensing and actuation, management bottleneck, and scale. We present results of our research on addressing the above challenges. Niche implements the autonomic computing architecture, proposed by IBM, in a fully decentralized way. Niche supports a network-transparent view of the system architecture simplifying the design of distributed self-management. Niche provides a concise and expressive API for self-management. The implementation of the platform relies on the scalability and robustness of structured overlay networks. We proceed by presenting a methodology for designing the management part of a distributed self-managing application. We define design steps that include partitioning of management functions and orchestration of multiple autonomic managers.In the second part, we discuss robustness of management and data consistency, which are necessary in a distributed system. Dealing with the effect of churn on management increases the complexity of the management logic and thus makes its development time consuming and error prone. We propose the abstraction of Robust Management Elements, which are able to heal themselves under continuous churn. Our approach is based on replicating a management element using finite state machine replication with a reconfigurable replica set. Our algorithm automates the reconfiguration (migration) of the replica set in order to tolerate continuous churn. For data consistency, we propose a majority-based distributed key-value store supporting multiple consistency levels that is based on a peer-to-peer network. The store enables the tradeoff between high availability and data consistency. Using majority allows avoiding potential drawbacks of a master-based consistency control, namely, a single-point of failure and a potential performance bottleneck.In the third part, we investigate self-management for Cloud-based storage systems with the focus on elasticity control using elements of control theory and machine learning. We have conducted research on a number of different designs of an elasticity controller, including a State-Space feedback controller and a controller that combines feedback and feedforward control. We describe our experience in designing an elasticity controller for a Cloud-based key-value store using state-space model that enables to trade-off performance for cost. We describe the steps in designing an elasticity controller. We continue by presenting the design and evaluation of ElastMan, an elasticity controller for Cloud-based elastic key-value stores that combines feedforward and feedback control.
650	7	a TEKNIK OCH TEKNOLOGIERx Elektroteknik och elektronikx Datorsystem0 (SwePub)202062 hsv//swe
650	7	a ENGINEERING AND TECHNOLOGYx Electrical Engineering, Electronic Engineering, Information Engineeringx Computer Systems0 (SwePub)202062 hsv//eng
650	7	a NATURVETENSKAPx Data- och informationsvetenskap0 (SwePub)1022 hsv//swe
650	7	a NATURAL SCIENCESx Computer and Information Sciences0 (SwePub)1022 hsv//eng
653		a Self-Management
653		a Autonomic Computing
653		a Control Theory
653		a Distributed Systems
653		a Grid Computing
653		a Cloud Computing
653		a Elastic Services
653		a Key-Value Stores
653		a SRA - ICT
653		a SRA - Informations- och kommunikationsteknik
700	1	a Vlassov, Vlassov,c Associate Professoru KTH,Programvaru- och datorsystem, SCS4 ths0 (Swepub:kth)u19yb2c8
700	1	a Haridi, Seif,c Professoru KTH,Programvaru- och datorsystem, SCS4 ths0 (Swepub:kth)u1j6y2uf
700	1	a Brand, Per,c Dr.u Swedish Institute of Computer Science4 ths
700	1	a Navarro Moldes, Leandro,c Associate Professoru Department of Computer Architecture, Universitat Politècnica de Catalunya4 opn
710	2	a KTHb Programvaruteknik och Datorsystem, SCS4 org
856	4	u https://kth.diva-portal.org/smash/get/diva2:548547/FULLTEXT01.pdfx primaryx Raw objecty fulltext
856	4	u https://ri.diva-portal.org/smash/get/diva2:1043125/FULLTEXT01.pdfx primaryx Raw objecty fulltext
856	4 8	u https://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-101661
856	4 8	u https://urn.kb.se/resolve?urn=urn:nbn:se:ri:diva-24046

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