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Jesús Gutiérrez-Gutiérrez1, Marta Zárraga-Rodríguez2, Xabier Insausti3

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This summary is machine-generated.

This study analyzes distributed average consensus algorithms in sensor networks, comparing convergence times for deterministic and randomized methods on cycle, path, and grid topologies. The fastest deterministic algorithm shows optimal performance on grids.

Keywords:
average consensus algorithmsconvergence timedistributed computationnumber of transmissionssensor networks

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Area of Science:

  • Distributed systems
  • Network algorithms
  • Sensor networks

Background:

  • Distributed average consensus is crucial for sensor network coordination.
  • Evaluating algorithm efficiency in terms of convergence time is essential for practical applications.
  • Network topology significantly impacts algorithm performance.

Purpose of the Study:

  • To compare the convergence time of six linear distributed average consensus algorithms.
  • To analyze algorithm performance on cycle, path, and grid network topologies.
  • To derive closed-form expressions and bounds for algorithm convergence times.

Main Methods:

  • Mathematical analysis to compute closed-form expressions for convergence time.
  • Evaluation of deterministic and randomized consensus algorithms.
  • Comparison of algorithms on distinct network structures: cycles, paths, and grids.

Main Results:

  • Closed-form expressions for the convergence time of four deterministic algorithms on cycles and paths.
  • Closed-form bounds for the convergence time of two randomized algorithms on cycles and paths.
  • A closed-form expression for the convergence time of the fastest deterministic algorithm on grids.

Conclusions:

  • The convergence time of distributed average consensus algorithms varies significantly with algorithm type and network topology.
  • Deterministic algorithms offer predictable convergence on specific topologies.
  • The fastest deterministic algorithm demonstrates efficient performance on grid networks, relevant for sensor network applications.