The Journal of Supercomputing

, Volume 68, Issue 3, pp 1280–1301 | Cite as

Improving the benefits of multicast prioritization algorithms

  • Emili Miedes
  • Francesc D. Muñoz-Escoí


Prioritized atomic multicast consists in delivering messages in total order while ensuring that the priorities of the messages are considered; i.e., messages with higher priorities are delivered first. That service can be used in multiple applications. An example is the usage of prioritization algorithms for reducing the transaction abort rates in applications that use a replicated database system. To this end, transaction messages get priorities according to their probability of violating the existing integrity constraints. This paper evaluates how that abort reduction may be improved varying the message sending rate and the bounds set on the length of the priority reordering queue being used by those multicast algorithms.


Total-order multicast Database replication Integrity constraints Abort rate Prioritized message delivery 


  1. 1.
    Amir Y, Danilov C, Stanton JR (2000) A low latency, loss tolerant architecture and protocol for wide area group communication. In: International Conference on Dependable Systems and Networks (DSN), IEEE-CS, Washington, DC, USA, pp 327–336Google Scholar
  2. 2.
    Chockler G, Keidar I, Vitenberg R (2001) Group communication specifications: a comprehensive study. ACM Comput Surv 33(4):427–469CrossRefGoogle Scholar
  3. 3.
    CiA (2001) About CAN in Automation (CiA).
  4. 4.
    Défago X, Schiper A, Urbán P (2004) Total order broadcast and multicast algorithms: taxonomy and survey. ACM Comput Surv 36(4):372–421CrossRefGoogle Scholar
  5. 5.
    Dolev D, Dwork C, Stockmeyer L (1987) On the minimal synchronism needed for distributed consensus. J ACM 34(1):77–97CrossRefzbMATHMathSciNetGoogle Scholar
  6. 6.
    International Organization for Standardization (ISO) (1993) Road vehicles—interchange of digital information—controller area network (CAN) for high-speed communication. Revised by ISO 11898-1:2003Google Scholar
  7. 7.
    JBoss (2011) The Netty project 3.2 user guide.
  8. 8.
    Kaashoek MF, Tanenbaum AS (1996) An evaluation of the Amoeba group communication system. In: International conference on distributed computing system (ICDCS), IEEE-CS, Washington, DC, USA, pp 436–448Google Scholar
  9. 9.
    Miedes E, Muñoz-Escoí FD (2008) Managing priorities in atomic multicast protocols. In: International conference on availability, reliability and security (ARES), Barcelona, Spain, pp 514–519Google Scholar
  10. 10.
    Miedes E, Muñoz-Escoí FD (2010) Dynamic switching of total-order broadcast protocols. In: International conference on parallel and distributed processing techniques and applications (PDPTA), CSREA Press, Las Vegas, Nevada, USA, pp 457–463Google Scholar
  11. 11.
    Miedes E, Muñoz-Escoí FD, Decker H (2008) Reducing transaction abort rates with prioritized atomic multicast protocols. In: International European conference on parallel and distributed computing (Euro-Par), Springer, Las Palmas de Gran Canaria, Spain, Lecture notes in computer science, vol 5168, pp 394–403Google Scholar
  12. 12.
    Mocito J, Rodrigues L (2006) Run-time switching between total order algorithms. In: International European conference on parallel and distributed computing (Euro-Par), Springer, Dresden, Germany, Lecture Notes in Computer Science, vol 4128, pp 582–591Google Scholar
  13. 13.
    Moser LE, Melliar-Smith PM, Agarwal DA, Budhia R, Lingley-Papadopoulos C (1996) Totem: a fault-tolerant multicast group communication system. Commun ACM 39(4):54–63CrossRefGoogle Scholar
  14. 14.
    Nakamura A, Takizawa M (1992) Priority-based total and semi-total ordering broadcast protocols. In: International conference on distributed computing systems (ICDCS), Yokohama, Japan, pp 178–185Google Scholar
  15. 15.
    Nakamura A, Takizawa M (1993) Starvation-prevented priority based total ordering broadcast protocol on high-speed single channel network. In: 2nd International symposium on high performance distributed computing (HPDC), pp 281–288Google Scholar
  16. 16.
    Rodrigues L, Veríssimo P, Casimiro A (1995) Priority-based totally ordered multicast. In: Workshop on algorithms and architectures for real-time control (AARTC), Ostend, BelgiumGoogle Scholar
  17. 17.
    Rütti O, Wojciechowski P, Schiper A (2006) Structural and algorithmic issues of dynamic protocol update. In: 20th International parallel and distributed processing symposium (IPDPS), IEEE-CS Press, Rhodes Island, GreeceGoogle Scholar
  18. 18.
    Tindell K, Clark J (1994) Holistic schedulability analysis for distributed hard real-time systems. Microprocess Microprogr 40(2–3):117–134CrossRefGoogle Scholar
  19. 19.
    Tully A, Shrivastava SK (1990) Preventing state divergence in replicated distributed programs. In: International symposium on reliable distributed systems (SRDS), Huntsville, Alabama, USA, pp 104–113Google Scholar
  20. 20.
    Wiesmann M, Schiper A (2005) Comparison of database replication techniques based on total order broadcast. IEEE Trans Knowl Data Eng 17(4):551–566CrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media New York 2014

Authors and Affiliations

  1. 1.Instituto Universitario Mixto Tecnológico de InformáticaUniversitat Politècnica de ValènciaValenciaSpain

Personalised recommendations