Toward Predicting Distributed Systems Dynamics

Amy Kumar; Jacob Beal; Soura Dasgupta; Raghu Mudumbai

doi:10.1109/SASOW.2015.16

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Conference proceeding

Toward Predicting Distributed Systems Dynamics

Amy Kumar, Jacob Beal, Soura Dasgupta and Raghu Mudumbai

2015 IEEE International Conference on Self-Adaptive and Self-Organizing Systems Workshops, pp.68-73

09/2015

DOI: 10.1109/SASOW.2015.16

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Abstract

Systems of "building block" algorithms can guarantee that self-organizing systems eventually converge to a predictable state, but what of their dynamical behavior in environments with ongoing changes? To begin to address this challenge, we analyze a commonly used distributed distance estimation algorithm from a stability theory perspective, identifying key properties of monotonicity and dynamical behavior envelope. This allows standard stability theory analysis to be applied to predict the behavior of the algorithm in response to persistent perturbation, both in isolation and as part of a composite system, as demonstrated both analytically and in simulation.

Algorithm design and analysis

predictable composition

aggregate programming

Heuristic algorithms

control theory

Estimation

Prediction algorithms

Stability analysis

Calculus

Convergence

Details

Title: Subtitle: Toward Predicting Distributed Systems Dynamics
Creators: Amy Kumar - Univ. of Iowa, Iowa City, IA, USA
Jacob Beal - Raytheon BBN Technol., Cambridge, MA, USA
Soura Dasgupta - Univ. of Iowa, Iowa City, IA, USA
Raghu Mudumbai - Univ. of Iowa, Iowa City, IA, USA
Resource Type: Conference proceeding
Publication Details: 2015 IEEE International Conference on Self-Adaptive and Self-Organizing Systems Workshops, pp.68-73
DOI: 10.1109/SASOW.2015.16
Publisher: IEEE
Language: English
Date published: 09/2015
Academic Unit: Electrical and Computer Engineering
Record Identifier: 9984083211602771

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