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Robust Fault-Tolerant Majority-Based Key-Value Store Supporting Multiple Consistency Levels
KTH, School of Information and Communication Technology (ICT), Communication: Services and Infrastucture, Software and Computer Systems, SCS.
KTH, School of Information and Communication Technology (ICT), Communication: Services and Infrastucture, Software and Computer Systems, SCS.
KTH, School of Information and Communication Technology (ICT), Communication: Services and Infrastucture, Software and Computer Systems, SCS.
2011 (English)In: 2011 IEEE 17TH INTERNATIONAL CONFERENCE ON PARALLEL AND DISTRIBUTED SYSTEMS (ICPADS), 2011, 589-596 p.Conference paper, Published paper (Refereed)
Abstract [en]

The wide spread of Web 2.0 applications with rapidly growing amounts of user generated data, such as, wikis, social networks, and media sharing, have posed new challenges on the supporting infrastructure, in particular, on storage systems. In order to meet these challenges, Web 2.0 applications have to tradeoff between the high availability and the consistency of their data. Another important issue is the privacy of user generated data that might be caused by organizations that own and control datacenters where user data are stored. We propose a large-scale, robust and fault-tolerant key-value object store that is based on a peer-to-peer network owned and controlled by a community of users. To meet the demands of Web 2.0 applications, the store supports an API consisting of different read and write operations with various data consistency guarantees from which a wide range of web applications would be able to choose the operations according to their data consistency, performance and availability requirements. For evaluation, simulation has been carried out to test the system availability, scalability and fault-tolerance in a dynamic, Internet wide environment.

Place, publisher, year, edition, pages
2011. 589-596 p.
Series
International Conference on Parallel and Distributed Systems - Proceedings, ISSN 1521-9097
Keyword [en]
peer-to-peer, key-value store, consistency models, distributed hash table, majority-based quorum technique
National Category
Electrical Engineering, Electronic Engineering, Information Engineering
Identifiers
URN: urn:nbn:se:kth:diva-92454DOI: 10.1109/ICPADS.2011.110ISI: 000299395900076Scopus ID: 2-s2.0-84856603401ISBN: 978-0-7695-4576-9 (print)OAI: oai:DiVA.org:kth-92454DiVA: diva2:513898
Conference
17th IEEE International Conference on Parallel and Distributed Systems (ICPADS) DEC 07-09, 2011 Tainan, TAIWAN
Note
QC 20120404Available from: 2012-04-04 Created: 2012-04-02 Last updated: 2012-08-31Bibliographically approved
In thesis
1. Self-Management for Large-Scale Distributed Systems
Open this publication in new window or tab >>Self-Management for Large-Scale Distributed Systems
2012 (English)Doctoral thesis, comprehensive summary (Other academic)
Abstract [en]

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.

Place, publisher, year, edition, pages
Stockholm: KTH Royal Institute of Technology, 2012. xix, 266 p.
Series
TRITA-ICT-ECS AVH, ISSN 1653-6363 ; 12:04
Keyword
Self-Management, Autonomic Computing, Control Theory, Distributed Systems, Grid Computing, Cloud Computing, Elastic Services, Key-Value Stores
National Category
Computer Systems
Research subject
SRA - ICT
Identifiers
urn:nbn:se:kth:diva-101661 (URN)978-91-7501-437-1 (ISBN)
Public defence
2012-09-26, Sal E, Forum IT-Universitetet, KTH, Isajordsgatan 39, Kista, 14:00 (English)
Opponent
Supervisors
Funder
ICT - The Next Generation
Note

QC 20120831

Available from: 2012-08-31 Created: 2012-08-30 Last updated: 2014-01-23Bibliographically approved

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