Verizon Digital Media Services Inc.

Jonathan DiVincenzo

Karthik Sathyanarayana

Robert J Peters

Seungyeob Choi

Eric Dyoniziak

Jie Feng

Some embodiments provide intelligent predictive stream caching for live, linear, or video-on-demand streaming content using prefetching, segmented caching, and request clustering. Prefetching involves retrieving streaming content segments from an origin server prior to the segments being requested by users. Prefetching live or linear streaming content segments involves continually reissuing requests to the origin until the segments are obtained or a preset retry duration is completed. Prefetching is initiated in response to a first request for a segment falling within a particular interval. Request clustering commences thereafter. Subsequent requests are queued until the segments are retrieved. Segmented caching involves caching segments for one particular interval. Segments falling within a next interval are not prefetched until a first request for one such segment in the next interval is received. Cached segments from the previous interval can be replaced in cache with segments for the current interval, thereby minimizing cache footprint utilization.

Intelligent predictive stream caching

Some embodiments provide a system for simultaneously monitoring a content stream that is streamed using any of a plurality of streaming protocols from different points-of-presence (PoP) from within a distributed platform in real-time without the need for manual visual verification. The system is implemented with different emulation engines, each providing client-side player emulation for a different streaming protocol. The client-side player emulation involves requesting and downloading content stream chunks from a specified PoP according to the streaming protocol that is used by the distributed platform to stream the content stream under test. As part of the emulation, each instance inspects the downloaded chunks without decoding or rendering in order to track real-time performance and any errors in the server-side transmission of the content stream under test.

Stream monitoring across a distributed platform

Some embodiments dynamically test capacity of a streaming server under test (SUT). The dynamic testing involves a test server generating different test scenarios. Each test scenario specifies a mix of different streaming protocols, content streams, and content stream upload to download ratio. The test server tests the SUT with a gradually increasing traffic load from each test scenario while monitoring SUT performance under each load. The test server records each load from each test scenario under which the SUT becomes saturated. The test server produces a grid mapping the observed SUT saturation points to the test loads that caused them. The grid is used when the SUT is deployed to a production environment to determine if SUT saturation is imminent based on current traffic patterns being serviced by the SUT in the production environment. If so, a remedial action is dynamically performed to prevent the saturation from occurring.

Growing community of inventors

Los Angeles, CA, United States of America

Jonathan DiVincenzo