QACO: Exploiting partial execution in web servers

Jinhan Kim, Sameh Elnikety, Yuxiong He, Seung Won Hwang, Shaolei Ren

Research output: Chapter in Book/Report/Conference proceedingConference contribution

4 Citations (Scopus)


Web servers provide content to users, with the requirement of providing high response quality within a short response time. Meeting these requirements is challenging, especially in the event of load spikes. Meanwhile, we observe that a response to a request can be adapted or partially executed depending on current resource availability at the server. For example, a web server can choose to send a low or medium resolution image instead of sending the original high resolution image under resource contention. In this paper, we exploit partial execution to expose a trade off between resource consumption and service quality. We show how to manage server resources to improve service quality and responsiveness. Specifically, we develop a framework, called Quota-based Control Optimization (QACO). The quota represents the total amount of resources available for all pending requests. QACO consists of two modules: (1) A control module adjusts the quota to meet the response time target. (2) An optimization module exploits partial execution and allocates the quota to pending requests in a manner that improves total response quality. We evaluate the framework using a system implementation in the Apache Web server, and using a simulation study of a Video-on-Demand server. The results show that under a response time target, QACO achieves a higher response quality than traditional techniques that admit or reject requests without exploiting partial execution.

Original languageEnglish
Title of host publicationProceedings of the 2013 ACM Cloud and Autonomic Computing Conference, CAC 2013
Publication statusPublished - 2013
Event2013 ACM International Conference on Cloud and Autonomic Computing, CAC 2013 - Miami, FL, United States
Duration: 2013 Aug 52013 Aug 9

Publication series

NameACM International Conference Proceeding Series


Other2013 ACM International Conference on Cloud and Autonomic Computing, CAC 2013
Country/TerritoryUnited States
CityMiami, FL

All Science Journal Classification (ASJC) codes

  • Software
  • Human-Computer Interaction
  • Computer Vision and Pattern Recognition
  • Computer Networks and Communications


Dive into the research topics of 'QACO: Exploiting partial execution in web servers'. Together they form a unique fingerprint.

Cite this