Abstract:
In one embodiment, an HTTP streaming session may be initiated at a client device in a network. The client device may have a buffer and may be configured to request and receive one or more data segments over HTTP from an HTTP server. A first data segment at a first data source rate may be requested and subsequently received. The first data segment may be stored in the buffer. A second data source rate may then be calculated based on a storage level in the buffer, and a second data segment at the second data source rate may be requested.
Abstract:
In one embodiment, an HTTP streaming session may be initiated at a client device in a network. The client device may have a buffer and may be configured to request and receive one or more data segments over HTTP from an HTTP server. A first data segment at a first data source rate may be requested and subsequently received. The first data segment may be stored in the buffer. A second data source rate may then be calculated based on a storage level in the buffer, and a second data segment at the second data source rate may be requested.
Abstract:
A precaching system identifies an object, such as a media file, that a user accesses and then analyzes a social graph of the user to identify social graph contacts that may be interested in the object. Based on the content of the object—and the interests and connections of contacts in the social graph—the precaching system determines whether a particular contact in the user's social graph is likely also to access the object. For example, the precaching system may determine a hit score corresponding to the object and a likelihood that the particular contact in the social graph will access the object. If the precaching system determines that the likelihood that the particular contact will access the object meets or exceeds a threshold probability level for precaching the object, the precaching system precaches the object near the contact in anticipation that the contact will access the object.
Abstract:
In one implementation, a method includes obtaining time series data. The time serious data includes a plurality of network utilization measurements. The plurality of network utilization measurements is indicative of a plurality of utilizations of one or more resources of a network resource at a plurality of times. The method also includes determining whether the time series data comprises a plurality of segments. Each segment of the plurality of segments is associated with a separate regression model and each segment includes a portion of the time series data. The method further includes identifying a current segment from the time series data when the time series data comprises the plurality of segments. The method further includes determining an estimated network utilization based on a current regression model associated with the current segment.
Abstract:
In one embodiment, an HTTP streaming session may be initiated at a client device in a network. The client device may have a buffer and may be configured to request and receive one or more data segments over HTTP from an HTTP server. A first data segment at a first data source rate may be requested and subsequently received. The first data segment may be stored in the buffer. A second data source rate may then be calculated based on a storage level in the buffer, and a second data segment at the second data source rate may be requested.
Abstract:
In one implementation, a method includes obtaining time series data. The time serious data includes a plurality of network utilization measurements. The plurality of network utilization measurements is indicative of a plurality of utilizations of one or more resources of a network resource at a plurality of times. The method also includes determining whether the time series data comprises a plurality of segments. Each segment of the plurality of segments is associated with a separate regression model and each segment includes a portion of the time series data. The method further includes identifying a current segment from the time series data when the time series data comprises the plurality of segments. The method further includes determining an estimated network utilization based on a current regression model associated with the current segment.
Abstract:
In one implementation, a method includes obtaining time series data. The time serious data includes a plurality of network utilization measurements. The plurality of network utilization measurements is indicative of a plurality of utilizations of one or more resources of a network resource at a plurality of times. The method also includes determining whether the time series data comprises a plurality of segments. Each segment of the plurality of segments is associated with a separate regression model and each segment includes a portion of the time series data. The method further includes identifying a current segment from the time series data when the time series data comprises the plurality of segments. The method further includes determining an estimated network utilization based on a current regression model associated with the current segment.
Abstract:
A precaching system identifies an object, such as a media file, that a user accesses and then analyzes a social graph of the user to identify social graph contacts that may be interested in the object. Based on the content of the object—and the interests and connections of contacts in the social graph—the precaching system determines whether a particular contact in the user's social graph is likely also to access the object. For example, the precaching system may determine a hit score corresponding to the object and a likelihood that the particular contact in the social graph will access the object. If the precaching system determines that the likelihood that the particular contact will access the object meets or exceeds a threshold probability level for precaching the object, the precaching system precaches the object near the contact in anticipation that the contact will access the object.
Abstract:
In one implementation, a method includes obtaining time series data. The time serious data includes a plurality of network utilization measurements. The plurality of network utilization measurements is indicative of a plurality of utilizations of one or more resources of a network resource at a plurality of times. The method also includes determining whether the time series data comprises a plurality of segments. Each segment of the plurality of segments is associated with a separate regression model and each segment includes a portion of the time series data. The method further includes identifying a current segment from the time series data when the time series data comprises the plurality of segments. The method further includes determining an estimated network utilization based on a current regression model associated with the current segment.
Abstract:
In one embodiment, an HTTP streaming session may be initiated at a client device in a network. The client device may have a buffer and may be configured to request and receive one or more data segments over HTTP from an HTTP server. A first data segment at a first data source rate may be requested and subsequently received. The first data segment may be stored in the buffer. A second data source rate may then be calculated based on a storage level in the buffer, and a second data segment at the second data source rate may be requested.