Online Spike Detection in Cloud Workloads
2015 (English)In: 2015 IEEE INTERNATIONAL CONFERENCE ON CLOUD ENGINEERING (IC2E 2015), New York: IEEE Computer Society, 2015, 446-451 p.Conference paper (Refereed)
We investigate methods for detection of rapid workload increases (load spikes) for cloud workloads. Such rapid and unexpected workload spikes are a main cause for poor performance or even crashing applications as the allocated cloud resources become insufficient. To detect the spikes early is fundamental to perform corrective management actions, like allocating additional resources, before the spikes become large enough to cause problems. For this, we propose a number of methods for early spike detection, based on established techniques from adaptive signal processing. A comparative evaluation shows, for example, to what extent the different methods manage to detect the spikes, how early the detection is made, and how frequently they falsely report spikes.
Place, publisher, year, edition, pages
New York: IEEE Computer Society, 2015. 446-451 p.
IdentifiersURN: urn:nbn:se:umu:diva-125610DOI: 10.1109/IC2E.2015.50ISI: 000380449000072ISBN: 978-1-4799-8218-9OAI: oai:DiVA.org:umu-125610DiVA: diva2:1034090
2015 IEEE International Conference on Cloud Engineering, Arizona State University, Tempe, AZ, Mar 09-12, 2015.