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On Load Balancing: A Mix-aware Algorithm for Heterogeneous Systems

Publikationsart Peer-reviewed
Publikationsform Tagungsbeitrag (peer-reviewed)
Autor/in Spicuglia Sebastiano, Björkqvist Mathias, Chen Lydia, Serazzi Giuseppe, Binder Walter, Smirni Evgenia,
Projekt LoadOpt - Workload Characterization and Optimization for Multicore Systems
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Tagungsbeitrag (peer-reviewed)

Titel der Proceedings Proceedings of the 4th ACM/SPEC International Conference on Performance Engineering (ICPE'13)
Ort Prague, Czech Republic
DOI 10.1145/2479871.2479884


Today's web services are commonly hosted on clusters of servers that are often located within computing clouds, whose computational and storage resources can be highly heterogeneous. The workload served typically exhibits disparate computation patterns (e.g., CPU-intensive or IO-intensive), that fluctuate both in terms of volume and mix. The system heterogeneity together with workload diversity further exacerbates the challenge of effective distribution of load within a computing cloud. This paper presents a novel, mix-aware load-balancing algorithm, which aims to distribute requests sent by multiple applications in heterogeneous servers such that the application response times are minimized and system resources (e.g., CPU and IO) are equally utilized. To this end, the presented algorithm tries to not only balance the total number of requests seen by each server, but also to shape the requests received by each server into a certain "mix", that is analytically shown to be optimal for response time minimization. Our experimental results - based both on simulation and on a prototype implementation - show that the mix-aware algorithm achieves robust performance in most workload mixes as well as a consistent performance improvement in comparison with one of the most robust load-balancing schemes of the Apache server.