Self-* overload control for distributed web systems

TL;DR

This paper introduces a Self-* Overload Control (SOC) policy for distributed web systems that automatically adapts to traffic surges, ensuring service quality without manual tuning, and outperforms previous methods in stability and resource utilization.

Contribution

The paper presents an original SOC policy that self-configures session admission constraints without prior traffic knowledge or manual parameter tuning.

Findings

SOC rapidly adapts to changing traffic conditions.

SOC maximizes resource utilization while respecting service agreements.

SOC demonstrates more stable behavior and better performance than previous approaches.

Abstract

Unexpected increases in demand and most of all flash crowds are considered the bane of every web application as they may cause intolerable delays or even service unavailability. Proper quality of service policies must guarantee rapid reactivity and responsiveness even in such critical situations. Previous solutions fail to meet common performance requirements when the system has to face sudden and unpredictable surges of traffic. Indeed they often rely on a proper setting of key parameters which requires laborious manual tuning, preventing a fast adaptation of the control policies. We contribute an original Self-* Overload Control (SOC) policy. This allows the system to self-configure a dynamic constraint on the rate of admitted sessions in order to respect service level agreements and maximize the resource utilization at the same time. Our policy does not require any prior information on the incoming traffic or manual configuration of key parameters. We ran extensive simulations under a wide range of operating conditions, showing that SOC rapidly adapts to time varying traffic and self-optimizes the resource utilization. It admits as many new sessions as possible in observance of the agreements, even under intense workload variations. We compared our algorithm to previously proposed approaches highlighting a more stable behavior and a better performance.