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IFIP International Conference on Distributed Applications and Interoperable Systems

DAIS 2012: Distributed Applications and Interoperable Systems pp 1–15Cite as

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Slead: Low-Memory, Steady Distributed Systems Slicing

Slead: Low-Memory, Steady Distributed Systems Slicing

  • Francisco Maia18,
  • Miguel Matos18,
  • Etienne Rivière19 &
  • …
  • Rui Oliveira18 
  • Conference paper
  • 694 Accesses

  • 6 Citations

Part of the Lecture Notes in Computer Science book series (LNCCN,volume 7272)

Abstract

Slicing a large-scale distributed system is the process of autonomously partitioning its nodes into k groups, named slices. Slicing is associated to an order on node-specific criteria, such as available storage, uptime, or bandwidth. Each slice corresponds to the nodes between two quantiles in a virtual ranking according to the criteria.

For instance, a system can be split in three groups, one with nodes with the lowest uptimes, one with nodes with the highest uptimes, and one in the middle. Such a partitioning can be used by applications to assign different tasks to different groups of nodes, e.g., assigning critical tasks to the more powerful or stable nodes and less critical tasks to other slices.

Assigning a slice to each node in a large-scale distributed system, where no global knowledge of nodes’ criteria exists, is not trivial. Recently, much research effort was dedicated to guaranteeing a fast and correct convergence in comparison to a global sort of the nodes.

Unfortunately, state-of-the-art slicing protocols exhibit flaws that preclude their application in real scenarios, in particular with respect to cost and stability. In this paper, we identify steadiness issues where nodes in a slice border constantly exchange slice and large memory requirements for adequate convergence, and provide practical solutions for the two. Our solutions are generic and can be applied to two different state-of-the-art slicing protocols with little effort and while preserving the desirable properties of each. The effectiveness of the proposed solutions is extensively studied in several simulated experiments.

Keywords

  • Friction Factor
  • Memory Usage
  • Memory Consumption
  • Bloom Filter
  • Stable Node

These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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References

  1. Almeida, P.S., Baquero, C., Preguiça, N., Hutchison, D.: Scalable Bloom Filters. Information Processing Letters (2007)

    Google Scholar 

  2. Bhagwan, R., Savage, S., Voelker, G.M.: Understanding availability. In: International Workshop on Peer-to-Peer Systems (2003)

    Google Scholar 

  3. Bloom, B.H.: Space/time trade-offs in hash coding with allowable errors. Communications of the ACM (1970)

    Google Scholar 

  4. Cheng, K., Xiang, L., Iwaihara, M.: Time-decaying Bloom Filters for data streams with skewed distributions. In: International Workshop on Research Issues in Data Engineering: Stream Data Mining and Applications (2005)

    Google Scholar 

  5. Eugster, P.T., Guerraoui, R., Handurukande, S.B., Kouznetsov, P., Kermarrec, A.-M.: Lightweight probabilistic broadcast. ACM Transactions on Computer Systems (2003)

    Google Scholar 

  6. Fernandez, A., Gramoli, V., Jimenez, E., Kermarrec, A.-M., Raynal, M.: Distributed Slicing in Dynamic Systems. In: International Conference on Distributed Computing Systems (2007)

    Google Scholar 

  7. Gantz, J.: The Diverse and Exploding Digital Universe. Technical report, IDC White Paper - sponsored by EMC (2008)

    Google Scholar 

  8. Gramoli, V., Vigfusson, Y., Birman, K., Kermarrec, A.-M., van Renesse, R.: Sliver, A fast distributed slicing algorithm. In: ACM Symposium on Principles of Distributed Computing (2008)

    Google Scholar 

  9. Gramoli, V., Vigfusson, Y., Birman, K., Kermarrec, A.-M., van Renesse, R.: Slicing Distributed Systems. IEEE Transactions on Computers (2009)

    Google Scholar 

  10. Jelasity, M., Voulgaris, S., Guerraoui, R., Kermarrec, A.-M., Van Steen, M.: Gossip-based peer sampling. ACM Transactions on Computer Systems (2007)

    Google Scholar 

  11. Matos, M., Vilaca, R., Pereira, J., Oliveira, R.: An epidemic approach to dependable key-value substrates. In: IEEE/IFIP International Conference on Dependable Systems and Networks Workshops (2011)

    Google Scholar 

  12. Montresor, A., Jelasity, M.: PeerSim: A scalable P2P simulator. In: International Conference on Peer-to-Peer (2009)

    Google Scholar 

  13. Montresor, A., Jelasity, M., Babaoglu, O.: Decentralized Ranking in Large-Scale Overlay Networks (2008)

    Google Scholar 

  14. Pruteanu, A., Iyer, V., Dulman, S.: ChurnDetect: A Gossip-Based Churn Estimator for Large-Scale Dynamic Networks. In: Jeannot, E., Namyst, R., Roman, J. (eds.) Euro-Par 2011, Part II. LNCS, vol. 6853, pp. 289–301. Springer, Heidelberg (2011)

    CrossRef  Google Scholar 

  15. Rivière, E., Voulgaris, S.: Gossip-Based Networking for Internet-Scale Distributed Systems. In: Babin, G., Stanoevska-Slabeva, K., Kropf, P. (eds.) MCETECH 2011. LNBIP, vol. 78, pp. 253–284. Springer, Heidelberg (2011)

    CrossRef  Google Scholar 

  16. Sutter, H.: The Free Lunch Is Over: A Fundamental Turn Toward Concurrency in Software. Dr. Dobb’s Journal (2005)

    Google Scholar 

  17. Voulgaris, S., Gavidia, D., Van Steen, M.: CYCLON: Inexpensive Membership Management for Unstructured P2P Overlays. Journal of Network and Systems Management (2005)

    Google Scholar 

  18. Wang, F., Xiong, Y., Liu, J.: mTreebone: A Collaborative Tree-Mesh Overlay Network for Multicast Video Streaming. IEEE Transactions on Parallel and Distributed Systems (2010)

    Google Scholar 

  19. Yoon, M.: Aging Bloom Filter with Two Active Buffers for Dynamic Sets. IEEE Transactions on Knowledge and Data Engineering (2010)

    Google Scholar 

Download references

Author information

Authors and Affiliations

  1. High-Assurance Software Laboratory, INESC TEC & University of Minho, Portugal

    Francisco Maia, Miguel Matos & Rui Oliveira

  2. Université de Neuchâtel, Switzerland

    Etienne Rivière

Authors
  1. Francisco Maia
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  2. Miguel Matos
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  3. Etienne Rivière
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  4. Rui Oliveira
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Editor information

Editors and Affiliations

  1. Institute of Information Systems, Vienna University of Technology, Argentinierstrasse 8/184-1, 1040, Vienna, Austria

    Karl Michael Göschka

  2. Swedish Institute of Computer Science, Isafjordsgatan 22, 164 29, Kista, Sweden

    Seif Haridi

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© 2012 IFIP International Federation for Information Processing

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Cite this paper

Maia, F., Matos, M., Rivière, E., Oliveira, R. (2012). Slead: Low-Memory, Steady Distributed Systems Slicing. In: Göschka, K.M., Haridi, S. (eds) Distributed Applications and Interoperable Systems. DAIS 2012. Lecture Notes in Computer Science, vol 7272. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-30823-9_1

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  • DOI: https://doi.org/10.1007/978-3-642-30823-9_1

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  • Print ISBN: 978-3-642-30822-2

  • Online ISBN: 978-3-642-30823-9

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