{"id":615690,"date":"2019-10-16T13:12:51","date_gmt":"2019-10-16T20:12:51","guid":{"rendered":"https:\/\/www.microsoft.com\/en-us\/research\/?post_type=msr-research-item&#038;p=615690"},"modified":"2019-10-16T13:12:51","modified_gmt":"2019-10-16T20:12:51","slug":"e2e-embracing-user-heterogeneity-to-improve-quality-of-experience-on-the-web","status":"publish","type":"msr-research-item","link":"https:\/\/www.microsoft.com\/en-us\/research\/publication\/e2e-embracing-user-heterogeneity-to-improve-quality-of-experience-on-the-web\/","title":{"rendered":"E2E: Embracing User Heterogeneity to Improve Quality of Experience on the Web"},"content":{"rendered":"<p><span>Conventional wisdom states that to improve quality of experience (QoE), web service providers should reduce the median or other percentiles of server-side delays. This work shows that doing so can be inefficient due to user heterogeneity in how the delays impact QoE. From the perspective of QoE, the sensitivity of a request to delays can vary greatly even among identical requests arriving at the service, because they di\ufffder in the wide-area network latency experienced prior to arriving at the service. In other words, saving 50ms of server-side delay affects different users differently.<\/span><\/p>\n<p><span>This paper presents E2E, the first resource allocation system that embraces user heterogeneity to allocate server-side resources in a QoE-aware manner. Exploiting this heterogeneity faces a unique challenge: unlike other application-level properties of a web request (e.g., a user\u2019s subscription type), the QoE sensitivity of a request to<br \/>\nserver-side delays cannot be pre-determined, as it depends on the delays themselves, which are determined by the resource allocation decisions and the incoming requests. This circular dependence makes the problem computationally difficult. <\/span><\/p>\n<p><span>We make three contributions: (1) a case for exploiting user heterogeneity to improve QoE, based on end-to-end traces from Microsoft\u2019s cloud-scale production web framework, as well as a user study on Amazon MTurk; (2) a novel resource allocation policy that addresses the circular dependence mentioned above; and (3) an efficient system implementation with almost negligible overhead. We applied E2E to two open-source systems: replica selection in Cassandra and message scheduling in RabbitMQ. Using traces and our testbed deployments, we show that E2E can increase QoE (e.g., duration of user engagement) by 28%, or serve 40% more concurrent<br \/>\nrequests without any drop in QoE.<\/span><\/p>\n","protected":false},"excerpt":{"rendered":"<p>Conventional wisdom states that to improve quality of experience (QoE), web service providers should reduce the median or other percentiles of server-side delays. This work shows that doing so can be inefficient due to user heterogeneity in how the delays impact QoE. From the perspective of QoE, the sensitivity of a request to delays can [&hellip;]<\/p>\n","protected":false},"featured_media":0,"template":"","meta":{"msr-url-field":"","msr-podcast-episode":"","msrModifiedDate":"","msrModifiedDateEnabled":false,"ep_exclude_from_search":false,"_classifai_error":"","msr-author-ordering":null,"msr_publishername":"","msr_publisher_other":"","msr_booktitle":"","msr_chapter":"","msr_edition":"","msr_editors":"","msr_how_published":"","msr_isbn":"","msr_issue":"","msr_journal":"","msr_number":"","msr_organization":"","msr_pages_string":"","msr_page_range_start":"","msr_page_range_end":"","msr_series":"","msr_volume":"","msr_copyright":"","msr_conference_name":"ACM Special Interest Group on Data Communication 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