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Achieving Robust Self-Management for Large-Scale Distributed Applications
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.
Swedish Institute of Computer Science (SICS), Kista, Sweden.
KTH, School of Information and Communication Technology (ICT), Communication: Services and Infrastucture, Software and Computer Systems, SCS.
2010 (English)In: Self-Adaptive and Self-Organizing Systems (SASO), 2010 4th IEEE International Conference on: SASO 2010, IEEE Computer Society, 2010, 31-40 p.Conference paper, Published paper (Refereed)
Abstract [sv]

Achieving self-management can be challenging, particularly in dynamic environments with resource churn (joins/leaves/failures). 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 (RMEs), which are able to heal themselves under continuous churn. Using RMEs allows the developer to separate the issue of dealing with the effect of churn on management from the management logic. This facilitates the development of robust management by making the developer focus on managing the application while relying on the platform to provide the robustness of management. RMEs can be implemented as fault-tolerant long-living services. We present a generic approach and an associated algorithm to achieve fault-tolerant long-living services. Our approach is based on replicating a service 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. The algorithm uses P2P replica placement schemes to place replicas and uses the P2P overlay to monitor them. The replicated state machine is extended to analyze monitoring data in order to decide on when and where to migrate. We describe how to use our approach to achieve robust management elements. We present a simulation-based evaluation of our approach which shows its feasibility.

Place, publisher, year, edition, pages
IEEE Computer Society, 2010. 31-40 p.
Keyword [en]
P2P replica placement schemes;fault-tolerant long-living services;finite state machine replication;large-scale distributed applications;management logic;reconfigurable replica set;resource churn;robust management elements;robust self-management;fault tolerant computing;finite state machines;peer-to-peer computing
National Category
Computer Science Computer Systems
Identifiers
URN: urn:nbn:se:kth:diva-53219DOI: 10.1109/SASO.2010.42Scopus ID: 2-s2.0-79952045321ISBN: 978-1-4244-8537-6 (print)OAI: oai:DiVA.org:kth-53219DiVA: diva2:469383
Conference
2010 Fourth IEEE International Conference on Self-Adaptive and Self-Organizing Systems (SASO), Budapest, Hungary, Sep. 27-Oct. 1, 2010
Funder
ICT - The Next Generation
Note
VV 20121223. QC 20120103Available from: 2011-12-23 Created: 2011-12-23 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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