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Astrolabe: A robust and scalable technology for distributed system monitoring, management, and data mining
Abstract
Scalable management and self-organizational capabilities are emerging as central requirements for a generation of large-scale, highly dynamic, distributed applications. We have developed an entirely new distributed information management system called Astrolabe. Astrolabe collects large-scale system state, permitting rapid updates and providing on-the-fly attribute aggregation. This latter capability permits an application to locate a resource, and also offers a scalable way to track system state as it evolves over time. The combination of features makes it possible to solve a wide variety of management and self-configuration problems. This paper describes the design of the system with a focus upon its scalability. After describing the Astrolabe service, we present examples of the use of Astrolabe for locating resources, publish-subscribe, and distributed synchronization in large systems. Astrolabe is implemented using a peer-to-peer protocol, and uses a restricted form of mobile code based on the SQL query language for aggregation. This protocol gives rise to a novel consistency model. Astrolabe addresses several security considerations using a built-in PKI. The scalability of the system is evaluated using both simulation and experiments; these confirm that Astrolabe could scale to thousands and perhaps millions of nodes, with information propagation delays in the tens of seconds.
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Cited by
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Kempe, D., Dobra, A., & Gehrke, J. (2004) · 44th Annual IEEE Symposium on Foundations of Computer Science, 2003. Proceedings. · doi:10.1109/sfcs.2003.1238221 · Cited by 1,480
Processing flows of information: From data stream to complex event processing
Cugola, G., & Margara, A. (2012) · ACM Computing Surveys · doi:10.1145/2187671.2187677 · Cited by 833
Jelasity, M., Voulgaris, S., Guerraoui, R., Kermarrec, A.-M., & van Steen, M. (2007) · ACM Transactions on Computer Systems · doi:10.1145/1275517.1275520 · Cited by 494
Adaptive filters for continuous queries over distributed data streams
Olston, C., Jiang, J., & Widom, J. (2003) · Proceedings of the 2003 ACM SIGMOD international conference on Management of data · doi:10.1145/872757.872825 · Cited by 447
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Risson, J., & Moors, T. (2006) · Computer Networks · doi:10.1016/j.comnet.2006.02.001 · Cited by 386
Metadata
- Authors
- Van Renesse, R., Birman, K. P., & Vogels, W.
- Venue
- ACM Transactions on Computer Systems
- Published
- 2003-05
- Volume
- 21
- Issue
- 2
- Pages
- 164-206
- ISSN
- 0734-2071 (ISSN-L)
- 1557-7333
- OpenAlex
- W1997369208
- Cited by
- 645
- References
- 0
- FWCI
- 82.05
- Type
- journal article
- Language
- en
- Open access
- closed
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- Van Renesse, R., Birman, K. P., & Vogels, W. (2003). Astrolabe: A robust and scalable technology for distributed system monitoring, management, and data mining. ACM Transactions on Computer Systems. https://doi.org/10.1145/762483.762485
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