Scalability in Computing and Robotics

  title={Scalability in Computing and Robotics},
  author={Heiko Hamann and Andreagiovanni Reina},
  journal={IEEE Transactions on Computers},
Efficient engineered systems require scalability. A scalable system has increasing performance with increasing system size. In an ideal situation, the increase in performance (e.g., speedup) corresponds to the number of units (e.g., processors, robots, users) that are added to the system (e.g., three times the number of processors in a computer would lead to three times faster computations). However, if multiple units work on the same task, then coordination among these units is required. This… 

Figures and Tables from this paper

Towards Hierarchical Hybrid Architectures for Human-Swarm Interaction
This contribution summarizes an integrated view on human- swarm interaction which investigates how human cognition should be joined with the distributed intelligence of robot swarms. From our
Designing a User-Centered Interaction Interface for Human–Swarm Teaming
This paper designed an interactive interface based on the users’ preference and proposed a controlling mechanism that allows a human operator to control a large swarm of UAVs and evaluated the proposed interaction interface with a complementary user study.
Guerrilla Performance Analysis for Robot Swarms: Degrees of Collaboration and Chains of Interference Events
This work introduces three general classes of performance: linear increase, saturation, and increase/decrease, and discusses options for quickly devising hypotheses about the underlying robot behaviors.


Swarm Robotics - A Formal Approach
A Study of Scalability Properties in Robotic Teams
It is believed that coordination methods can be developed that improve a group’s performance by minimizing interference, and the findings of composite coordination methods that provide evidence of this claim are presented.
Sophisticated collective foraging with minimalist agents: a swarm robotics test
This study demonstrates the sufficiency of simple individual agent rules to generate sophisticated collective foraging behaviour and constructs an optimal foraging theory model that accounts for distance and quality of resources, as well as overcrowding, and predicts a swarm-size-dependent strategy.
The perpetual motion of parallel performance
  • 2015
The accumulative law and its probability model: an extension of the Pareto distribution and the log-normal distribution
It is shown that the resulting accumulative distribution has properties that are akin to both the Pareto distribution and the log-normal distribution, which leads to a broad range of applications in modelling and fitting real data.
Multiscale Modelling Tool: Mathematical modelling of collective behaviour without the maths
By providing simple automated access to advanced mathematical techniques from statistical physics, nonlinear dynamical systems analysis, and computational simulation, this work hopes to advance standards in modelling collective behaviour.
Coherent collective behaviour emerging from decentralised balancing of social feedback and noise
This study illustrates through simulation experiments how the robot swarm can adaptively reach coherence for various noise levels by regulating the number of communication links, and indicates that the derived relationship between social feedback, noise and coherence is robust and swarm size independent.
Collective Change Detection: Adaptivity to Dynamic Swarm Densities and Light Conditions in Robot Swarms
This work studies aggregation of swarm robots controlled by an extended variant of the BEECLUST algorithm and finds an improved performance compared to robot swarms without communication and without awareness of the swarm density.
SciPy 1.0: fundamental algorithms for scientific computing in Python
An overview of the capabilities and development practices of SciPy 1.0 is provided and some recent technical developments are highlighted.
Machine behaviour
It is argued that this necessitates a broad scientific research agenda to study machine behaviour that incorporates and expands upon the discipline of computer science and includes insights from across the sciences.