Energy efficiency; Nonlinear dynamical systems; Scheduling algorithms; Distributed computing
Abstract :
[en] This paper investigates a self-organized critical approach for dynamically load-balancing computational workloads. The proposed model is based on the Bak-Tang-Wiesenfeld sandpile: a cellular automaton that works in a critical regime at the edge of chaos. In analogy to grains of sand, tasks arrive, pile up and slip through the different processing elements or sites of the system. When a pile exceeds a certain threshold, it collapses and initiates an avalanche of migrating tasks, i.e. producing load-balancing. We show that the frequency of such avalanches is in power-law relation with their sizes, a scale-invariant fingerprint of self-organized criticality that emerges without any tuning of parameters. Such an emergent pattern has organic properties such as the self-organization of tasks into resources or the self-optimization of the computing performance. The conducted experimentation also reveals that the system is in balanced (i.e. not driving to overloaded or underutilized resources) as long as the arrival rate of tasks equals the processing power of the system. Taking advantage of this fact, we hypothesize that the processing elements can be turned on and off depending on the state of the workload as to maximize the utilization of resources. An interesting side-effect is that the overall energy consumption of the system is minimized without compromising the quality of service.
Disciplines :
Computer science
Author, co-author :
Laredo, Jean-Luis; Université du Havre > LITIS
Guinand, Frédéric; Université du Havre > LITIS
Damien, Olivier; Université du Havre > LITIS
Bouvry, Pascal ; University of Luxembourg > Faculty of Science, Technology and Communication (FSTC) > Computer Science and Communications Research Unit (CSC)
External co-authors :
yes
Language :
English
Title :
Load Balancing at the Edge of Chaos: How Can Self-Organized Criticality Lead to Energy-Efficient Computing
Publication date :
01 January 2017
Journal title :
IEEE Transactions on Parallel and Distributed Systems