Control-based load-balancing techniques: Analysis and performance evaluation via a randomized optimization approach

• Published in: Control engineering practice Vol. 52; no. July; pp. 24 - 34
• Main Authors: Papadopoulos, Alessandro Vittorio, Klein, Cristian, Maggio, Martina, Dürango, Jonas, Dellkrantz, Manfred, Hernández-Rodriguez, Francisco, Elmroth, Erik, Årzén, Karl-Erik
• Format: Journal Article
• Language: English
• Published: Elsevier Ltd 01.07.2016
• Subjects: Cloud computing; Cloud control; Computer Science; Controllers; datalogi; Engineering and Technology; Failure; Load balancing; Optimization; Proposals; Randomized optimization; Redundancy; Response time; Teknik; Randomized optimization; Load-balancing; Cloud control
• ISSN: 0967-0661; 1873-6939; 1873-6939
• DOI: 10.1016/j.conengprac.2016.03.020

Cloud applications are often subject to unexpected events like flashcrowds and hardware failures. Users that expect a predictable behavior may abandon an unresponsive application when these events occur. Researchers and engineers addressed this problem on two separate fronts: first, they introduced replicas – copies of the application with the same functionality – for redundancy and scalability; second, they added a self-adaptive feature called brownout inside cloud applications to bound response times by modulating user experience. The presence of multiple replicas requires a dedicated component to direct incoming traffic: a load-balancer. Existing load-balancing strategies based on response times interfere with the response time controller developed for brownout-compliant applications. In fact, the brownout approach bounds response times using a control action. Hence, the response time, that was used to aid load-balancing decision, is not a good indicator of how well a replica is performing. To fix this issue, this paper reviews some proposal for brownout-aware load-balancing and provides a comprehensive experimental evaluation that compares them. To provide formal guarantees on the load-balancing performance, we use a randomized optimization approach and apply the scenario theory. We perform an extensive set of experiments on a real machine, extending the popular lighttpd web server and load-balancer, and obtaining a production-ready implementation. Experimental results show an improvement of the user experience over Shortest Queue First (SQF)—believed to be near-optimal in the non-adaptive case. The improved user experience is obtained preserving the response time predictability.