Abstract:
In one embodiment, a method includes training a deep neural network using a first set of network characteristics corresponding to a first time and a second set of network characteristics corresponding to a second time, generating, using the deep neural network, a predictive set of network characteristics corresponding to a future time, and assigning a task of a distributed application to a processing unit based on the predictive set of network characteristics.
Abstract:
Various systems and methods for counting people. For example, one method involves receiving input data at an analytics system that includes a neural network. The input data includes a representation of an environment, including representations of several people. The method also includes identifying the representations of the people in the representation of the environment. The method also includes updating an output value that indicates the number of people identified as being present in the environment.
Abstract:
According to one aspect, a method includes identifying at least a first chunk to be obtained, the at least first chunk including at least a first packet, and determining a deadline for the first chunk, the deadline being indicative of an amount of time before the first chunk is needed. The method also includes determining whether the deadline for the first chunk is relatively long, and de-prioritizing the first chunk with respect to obtaining the first chunk for queueing in a buffer when it is determined that the deadline for the first chunk is relatively long. Finally, the method includes obtaining the first chunk for queueing in the buffer, wherein obtaining the first chunk for queueing in the buffer includes obtaining the first chunk after obtaining a second chunk for queueing in the buffer, the second chunk having a shorter deadline than the deadline for the first chunk.
Abstract:
In one embodiment, a method includes receiving current data, the current data including time series data representing a plurality of time instances. The method includes storing at least a recent portion of the current data in a buffer. The method includes reducing the dimensionality of the current data to generate dimensionality-reduced data. The method includes generating a reconstruction error based on the dimensionality-reduced data and a plurality of neural network metrics. At least one of a size of the recent portion of the current data stored in the buffer or an amount of the reducing the dimensionality of the current data is based on the reconstruction error.
Abstract:
Disclosed are systems, methods, and computer-readable storage media for adaptive telemetry based on in-network cross domain intelligence. A telemetry server can receive at least a first telemetry data stream and a second telemetry data stream. The first telemetry data stream can provide data collected from a first data source and the second telemetry data stream can provide data collected from a second data source. The telemetry server can determine correlations between the first telemetry data stream and the second telemetry data stream that indicate redundancies between data included in the first telemetry data stream and the second telemetry data stream, and then adjust, based on the correlations between the first telemetry data stream and the second telemetry data stream, data collection of the second telemetry data stream to reduce redundant data included in the first telemetry data stream and the second telemetry data stream.
Abstract:
A method for retrieving content on a network comprising a first device and a second device is described. The method includes receiving in the network a request for content from the first device, the request identifying the content using an IPv6 address for the content, and determining whether the content is stored in a cache of the second device. Upon determining the content is stored in the cache of the second device, a request is sent to the second device for the content using the IPv6 address of the content. The content is forwarded to the first device from the second device, wherein the first and second devices are part of the same layer 2 domain. Methods of injecting content to a home network and packaging content are also described.
Abstract:
A method is provided in one example embodiment and includes, for each of a plurality of individual storage units collectively comprising a virtual storage unit, mapping an internal address of the storage unit to a unique IP address, wherein each of the storage units comprises a block of storage on one of a plurality of physical storage devices and wherein the IP address includes a virtual storage unit number identifying the virtual storage unit; receiving from a client a request to perform an operation on at least one of the data storage units, wherein the request identifies the internal address of the at least one of the data storage units; translating the internal address of the at least one of the data storage unit to the unique IP address of the at least one of the data storage units; and performing the requested operation on the at least one of the data storage units.
Abstract:
Various systems and methods for counting people. For example, one method involves receiving input data at an analytics system that includes a neural network. The input data includes a representation of an environment, including representations of several people. The method also includes identifying the representations of the people in the representation of the environment. The method also includes updating an output value that indicates the number of people identified as being present in the environment.
Abstract:
According to one aspect, a method includes obtaining a segment routing (SR) packet from an endpoint via a first router at a first server along a path, the SR packet including an SR list and a last address, the last address being an address of a requested service. The method also includes determining, at the first server, whether the requested service is available from the first server, wherein determining whether the requested service is available from the first server includes opening the SR packet, parsing an SR header of the SR packet, and performing a lookup in a service table. Finally, the method includes modifying the SR packet at the first server when it is determined that the requested service is not available from the first server; and forwarding the SR packet along the path.
Abstract:
In one embodiment, a method includes receiving current data, the current data including time series data representing a plurality of time instances. The method includes storing at least a recent portion of the current data in a buffer. The method includes reducing the dimensionality of the current data to generate dimensionality-reduced data. The method includes generating a reconstruction error based on the dimensionality-reduced data and a plurality of neural network metrics. At least one of a size of the recent portion of the current data stored in the buffer or an amount of the reducing the dimensionality of the current data is based on the reconstruction error.