Microsoft Technology Licensing, LLC

Ning Lin

Won Yoo

Anil K Ruia

Himanshu Patel

Chittaranjan Sadanand Pattekar

John A Bocharov

Paul England

Anirban Roy

Vishal Sood

Jack E Freelander

Quintin Swayne Burns

John Carl Simmons

Lin Liu

Raymond Cheng

Krishna Prakash Duggaraju

Samuel John Wenker

Andrew Lee Jenks

Kevin M Kane

Venkat Raman Don

Pu Su

Lightweight mechanisms provide a way to assert provenance when live streaming media content and establish provenance upon playback. For example, a provenance claim generator generates a key pair including a live-stream private key and live-stream public key. The claim generator signs, with a long-term private key reliably associated with a sender, manifest metadata including the live-stream public key, thereby producing a manifest signature. During live streaming, the claim generator signs respective portions of media content with the live-stream private key, producing portion signatures for the respective portions. A provenance claim validator receives the manifest signature and manifest metadata. The claim validator verifies the manifest metadata using a long-term public key (reliably associated with the sender) and the manifest signature. During live streaming, the claim validator verifies the respective portions of the media content using the live-stream public key and the portion signatures for the respective portions.

Asserting and establishing provenance of media content during live streaming

A caching system segments content into multiple, individually cacheable chunks cached by a cache server that caches partial content and serves byte range requests with low latency and fewer duplicate requests to an origin server. The system receives a request from a client for a byte range of a content resource. The system determines the chunks overlapped by the specified byte range and sends a byte range request to the origin server for the overlapped chunks not already stored in a cache. The system stores the bytes of received responses as chunks in the cache and responds to the received request using the chunks stored in the cache. The system serves subsequent requests that overlap with previously requested ranges of bytes from the already retrieved chunks in the cache and makes requests to the origin server only for those chunks that a client has not previously requested.

Byte range caching

An intelligent caching system is described herein that intelligently consolidates the name-value pairs in content requests containing query strings so that only substantially non-redundant responses are cached, thereby saving cache proxy resources. The intelligent caching system determines which name-value pairs in the query string can affect the redundancy of the content response and which name-value pairs can be ignored. The intelligent caching system organically builds the list of relevant name-value pairs by relying on a custom response header or other indication from the content server. Thus, the intelligent caching system results in fewer requests to the content server as well as fewer objects in the cache.

Intelligent caching for requests with query strings

Embodiments are directed to pacing on-demand linear advertisement entries to appear as being live entries, to generating a sequential segment map from a parallel playlist and to consolidating linear ad and main content portions into a single linear chunklist. In one embodiment, a computer system receives video content updates for a portion of live video programming, and generates a parallel playlist with parallel playlist entries that identify a presentation that is to be played. The computer system then generates a sequential segment map from the parallel playlist that identifies which parallel playlist entry is to be played, monitors a live position for new media, determines that an on-demand linear advertisement is to be played at the live position, and appends on-demand linear advertisement chunks to a chunklist to replace the main content chunks and play the on-demand linear advertisement entries in a pseudo-live format as if they were live.

Overwriting existing media content with viewer-specific advertisements

A low latency streaming system provides a stateless protocol between a client and server with reduced latency. The server embeds incremental information in media fragments that eliminates the usage of a typical control channel. In addition, the server provides uniform media fragment responses to media fragment requests, thereby allowing existing Internet cache infrastructure to cache streaming media data. Each fragment has a distinguished Uniform Resource Locator (URL) that allows the fragment to be identified and cached by both Internet cache servers and the client's browser cache. The system reduces latency using various techniques, such as sending fragments that contain less than a full group of pictures (GOP), encoding media without dependencies on subsequent frames, and by allowing clients to request subsequent frames with only information about previous frames.

Low latency cacheable media streaming

A load balancing system is described herein that proactively balances client requests among multiple destination servers using information about anticipated loads or events on each destination server to inform the load balancing decision. The system detects one or more upcoming events that will affect the performance and/or capacity for handling requests of a destination server. Upon detecting the event, the system informs the load balancer to drain connections around the time of the event. Next, the event occurs on the destination server, and the system detects when the event is complete. In response, the system informs the load balancer to restore connections to the destination server. In this way, the system is able to redirect clients to other available destination servers before the tasks occur. Thus, the load balancing system provides more efficient routing of client requests and improves responsiveness.

Proactive load balancing

A live caching system is described herein that reduces the burden on origin servers for serving live content. In response to receiving a first request that results in a cache miss, the system forwards the first request to the next tier while 'holding' other requests for the same content. If the system receives a second request while the first request is pending, the system will recognize that a similar request is outstanding and hold the second request by not forwarding the request to the origin server. After the response to the first request arrives from the next tier, the system shares the response with other held requests. Thus, the live caching system allows a content provider to prepare for very large events by adding more cache hardware and building out a cache server network rather than by increasing the capacity of the origin server.

Network caching for multiple contemporaneous requests

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Redmond, WA, United States of America

Ning Lin