Control-Based Load-Balancing Techniques: Analysis and Performance Evaluation via a Randomized Optimization Approach

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Bibtex

@article{ccf16d562433430c83c2e6b952e82067,
title = "Control-Based Load-Balancing Techniques: Analysis and Performance Evaluation via a Randomized Optimization Approach",
abstract = "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.",
keywords = "load-balancing, randomized optimization, cloud control",
author = "Papadopoulos, {Alessandro Vittorio} and Cristian Klein and Martina Maggio and Jonas D{\"u}rango and Manfred Dellkrantz and Francisco Hernandez-Rodriguez and Erik Elmroth and Karl-Erik {\AA}rz{\'e}n",
year = "2016",
month = "7",
doi = "10.1016/j.conengprac.2016.03.020",
language = "English",
volume = "52",
pages = "24--34",
journal = "Control Engineering Practice",
issn = "0967-0661",
publisher = "Elsevier",
number = "July",

}