Distributed Computing

, Volume 20, Issue 2, pp 95–114

The design of novel distributed protocols from differential equations

  • Indranil Gupta
  • Mahvesh Nagda
  • Christo Frank Devaraj

DOI: 10.1007/s00446-007-0024-2

Cite this article as:
Gupta, I., Nagda, M. & Devaraj, C.F. Distrib. Comput. (2007) 20: 95. doi:10.1007/s00446-007-0024-2


This paper proposes a framework to translate certain subclasses of differential equation systems into practical protocols for distributed systems. The generated protocols are intended for large-scale distributed systems that contain several hundreds to thousands of processes. The synthesized protocols are state machines containing probabilistic transitions and actions, and they are proved to show equivalent stochastic behavior to the original equations. The protocols are probabilistically scalable and reliable, and have practical applications in large-scale distributed systems, e.g., peer to peer systems. In order to illustrate the usefulness of the framework, it is used to generate new solutions for the problems of (a) responsibility migration (giving rise to a novel model of dynamic replication), and (b) majority selection. We present mathematical analysis of these two protocols, and experimental results from our implementations. These two protocols are derived from natural analogies that are represented as differential equations—endemics and the Lotka–Volterra model of competition, respectively. We believe the design framework could be effectively used in transforming, in a very systematic manner, well-known natural phenomena into protocols for distributed systems.


Science of protocol design Differential equations Distributed protocols Scalability Reliability Replication Endemics Voting LV Probabilistic protocols 

Copyright information

© Springer-Verlag 2007

Authors and Affiliations

  • Indranil Gupta
    • 1
  • Mahvesh Nagda
    • 2
  • Christo Frank Devaraj
    • 3
  1. 1.Department of Computer ScienceUniversity of Illinois at Urbana-ChampaignUrbanaUSA
  2. 2.Wolverine Asset ManagementNapervilleUSA
  3. 3.Microsoft CorporationSeattleUSA

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