Load Balancing at the Edge of Chaos: How Self Self-Organized Organized Criticality Can Lead to Energy Energy-Efficient Computing
Abstract: This paper investigates a self self-organized organized critical approach for dynamically loadload balancing computational workloads. The proposed model is based on the BakBak Tang-Wiesenfeld Wiesenfeld sandpile: a cellular automaton that works in a critical regime at the edge of chaos. In n analogy to grains of sand, tasks arrive and pile up on 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. balancing. We show that the frequency of such avalanches is in power-law law relation with their sizes, a scale scale-invariant invariant fingerprint of self-organized self criticality that emerges without any tuning of parameters. Such an emergent pattern has organic properties such as the self self-organization anization of tasks into resources or the self-optimization optimization of the computing performance. The conducted experimentation also reveals that the system has a critical attractor in the point in which 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 n of the system is minimized without compromising the quality of service.