A calculus of value broadcasts

  • K. V. S. Prasad
Paper Sessions Concurrency Semantic
Part of the Lecture Notes in Computer Science book series (LNCS, volume 694)


Computation can be modelled as a sequence of values, each broadcast by one agent and instantaneously audible to all those in parallel with it. Listening agents receive the value; others lose it. Subsystems interface via translators; these can scramble values and thus hide or restrict them. Examples show the calculus describing this model to be a powerful and natural programming tool. Weak bisimulation, a candidate for observational equivalence, is defined on the basis that receiving a value can be matched by losing it.

Key words and phrases

Broadcast parallel computation distributed computing process calculi CCS communicating processes bisimulation observational equivalence 

CR classification

F3.2 Semantics of Programming Languages—operational semantics algebraic approaches to semantics F3.1 Logics of programs 


Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.


  1. [Abr87]
    Samson Abramsky. Observation equivalence as a testing equivalence. Theoretical Computer Science, 53, 1987.Google Scholar
  2. [AJ92]
    Lennart Augustsson and Thomas Johnsson. Lazy ML user's manual. Technical report, Department of Computer Science, Chalmers University of Technology, 1992.Google Scholar
  3. [BC91]
    Kenneth Birman and Robert Cooper. The ISIS project: Real experience with a fault tolerant programming system. Operating Systems Review, 25(2), April 1991.Google Scholar
  4. [BMT92]
    Dave Berry, Robin Milner, and David Turner. A semantics for ML concurrency primitives. In Symposium on Principles of Programming Languages. ACM, 1992.Google Scholar
  5. [CH88]
    Rance Cleaveland and Matthew Hennessy. Priorities in process algebras. In Symposium on Logic in Computer Science. IEEE, 1988.Google Scholar
  6. [DK86]
    Rina Dechter and Leonard Kleinrock. Broadcast communications and distributed algorithms. IEEE Trans. on Computers, 35(3):418, Mar 1986.Google Scholar
  7. [GMP89]
    Alessandro Giacalone, Prateek Mishra, and Sanjeev Prasad. Facile: A symmetric integration of functional and concurrent programming. International Journal of Parallel Programming, 18(2), 1989.Google Scholar
  8. [Gro90]
    J.F. Groote. Transition system specifications with negative premises. In CONCUR '90, 1990. Springer Verlag LNCS 458.Google Scholar
  9. [Hen91]
    Matthew Hennessy. A proof system for communicating processes with value-passing. Formal Aspects of Computer Science, 3:346–366, 1991.Google Scholar
  10. [Hol83]
    Sören Holmström. PFL: A functional language for parallel programming. Technical Report 7, Dept. of Computer Sciences, Chalmers Univ. of Tech., 1983.Google Scholar
  11. [HT92]
    Tzung-Pei Hong and Shian-Shyong Tseng. Parallel perceptron learning on a single-channel broadcast communication model. Parallel Computing, 18:133–148, 1992.CrossRefGoogle Scholar
  12. [Jon92]
    Simon Jones. Translating CBS to LML. Technical report, Department of Computer Science, University of Stirling, 1992.Google Scholar
  13. [LT87]
    Nancy Lynch and Mark Tuttle. Hierarchical correctness proofs for distributed algorithms. Technical Report MIT/LCS/TR-387, Laboratory for Computer Science, Massachusetts Institute of Technology, 1987.Google Scholar
  14. [Mil89]
    Robin Milner. Communication and Concurrency. Prentice Hall, 1989.Google Scholar
  15. [Pet93]
    Jenny Petersson. Tools for CBS. Licentiate thesis, Department of Computer Science, Chalmers University of Technology, 1993. In preparation.Google Scholar
  16. [Pra91a]
    K. V. S. Prasad. Bisimulations induced by preorders on action sequences. In Chalmers Workshop On Concurrency, May 1991.Google Scholar
  17. [Pra91b]
    K. V. S. Prasad. A calculus of broadcasting systems. In TAPSOFT'91 Volume 1: CAAP, April 1991. Springer Verlag LNCS 493.Google Scholar
  18. [Pra93a]
    K. V. S. Prasad. Broadcasting with priority. Technical report, Department of Computer Science, Chalmers University of Technology, 1993.Google Scholar
  19. [Pra93b]
    K. V. S. Prasad. Programming with broadcasts. Technical report, Department of Computer Science, Chalmers University of Technology, 1993.Google Scholar
  20. [Sjö91]
    Peter Sjödin. From LOTOS specifications to distributed implementations. PhD thesis, Uppsala University, December 1991.Google Scholar
  21. [Vaa91]
    Frits Vaandrager. On the relationship between process algebra and input/output automata. 6th Annual Symposium on Logic in Computer Science, 1991.Google Scholar
  22. [YLC90]
    Chang-Biau Yang, R. C. T. Lee, and Wen-Tsuen Chen, Parallel graph algorithms based upon broadcast communications. IEEE Trans. on Computers, 39(12):1468, Dec 1990.CrossRefGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 1993

Authors and Affiliations

  1. 1.Department of Computer SciencesChalmers University of TechnologyGothenburgSweden

Personalised recommendations