Dynamic control of CPU usage in a Lambda platform

Young Ki Kim, M. Reza HoseinyFarahabady, Young Choon Lee, Albert Y. Zomaya, Raja Jurdak

Research output: Chapter in Book/Report/Conference proceedingConference proceeding contributionpeer-review

11 Citations (Scopus)


Lambda platform is a new concept based on an event-driven server-less computation that empowers application developers to build scalable enterprise software in a virtualized environment without provisioning or managing any physical servers (a server-less solution). In reality, however, devising an effective consolidation method to host multiple Lambda functions into a single machine is challenging. The existing simple resource allocation algorithms, such as the round-robin policy used in many commercial server-less systems, suffer from lack of responsiveness to a sudden surge in the incoming workload. This will result in an unsatisfactory performance degradation that is directly experienced by the end-user of a Lambda application. In this paper, we address the problem of CPU cap management in a Lambda platform for ensuring different QoS enforcement levels in a platform with shared resources, in case of fluctuations and sudden surges in the incoming workload requests. To this end, we present a closed-loop (feedback-based) CPU cap controller, which fulfills the QoS levels enforced by the application owners. The controller adjusts the number of working threads per QoS class and dispatches the outstanding Lambda functions along with the associated events to the most appropriate working thread. The proposed solution reduces the QoS violations by an average of 6.36 times compared to the round-robin policy. It can also maintain the end-to-end response time of applications belonging to the highest priority QoS class close to the target set-point while decreasing the overall response time by up to 52%.

Original languageEnglish
Title of host publicationProceedings - 2018 IEEE International Conference on Cluster Computing, CLUSTER 2018
Place of PublicationPiscatway, NJ
PublisherInstitute of Electrical and Electronics Engineers (IEEE)
Number of pages11
ISBN (Electronic)9781538683194
ISBN (Print)9781538683200
Publication statusPublished - 29 Oct 2018
Event2018 IEEE International Conference on Cluster Computing, CLUSTER 2018 - Belfast, United Kingdom
Duration: 10 Sept 201813 Sept 2018

Publication series

NameIEEE International Conference on Cluster Computing
ISSN (Print)1552-5244


Conference2018 IEEE International Conference on Cluster Computing, CLUSTER 2018
Country/TerritoryUnited Kingdom


  • Dynamic CPU usage control
  • FaaS (Function as a Service)
  • QoS-aware resource manager
  • Server-less computing


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