Abstract: Methods, systems, and computer-readable media for providing network-based audience measurement are provided. Data packets are intercepted between a client computer and a content server. Unique subscribers and content names are identified based on the data packets. One or more audience measurement metrics are computed based on the unique subscribers and the content names.

Abstract: A method, non-transitory computer readable medium and apparatus for detecting a tethering function being performed by an endpoint device in a communications network are disclosed. For example, the method analyzes a data packet directed towards the endpoint device, detects a signature based upon analyzing the data packet, and identifies the endpoint device as performing the tethering function based upon detecting the signature.

Abstract: A network includes a cache server and a network aware server that operates to determine an optimization between a cost of retrieving content from a communication network and a cost of caching content at the cache server. The optimization is determined as a minimum of a sum of a transit cost, a backbone cost, and a caching cost. The transit cost includes a money cost per data unit. The backbone cost includes a money cost per data unit and time unit. The caching cost includes a money cost per server unit. In response to determining the optimization, the network aware server sends a content identifier to the cache server, and the cache server receives the content identifier, determines a source of a content item, and if the source is the same as the content identifier, then cache the content item.

Abstract: A traffic classifier has a plurality of binary classifiers, each associated with one of a plurality of calibrators. Each calibrator trained to translate an output score of the associated binary classifier into an estimated class probability value using a fitted logistic curve, each estimated class probability value indicating a probability that the packet flow on which the output score is based belongs to the traffic class associated with the binary classifier associated with the calibrator. The classifier training system configured to generate a training data based on network information gained using flow and packet sampling methods. In some embodiments, the classifier training system configured to generate reduced training data sets, one for each traffic class, reducing the training data related to traffic not associated with the traffic class.

Abstract: Systems and methods for controlling a wireless device by a user based on bandwidth used when the device is connected to a network are disclosed. The bandwidth used by a process when the wireless device is connected to a network is determined. Information associating the value of the bandwidth used by the process when connected to the network, with at least one characteristic of the network is provided. A bandwidth management profile that identifies what process is allowed to be executed on each network is generated. The bandwidth management profile is used to determine whether the process should be executed on the network.

Abstract: A network includes a cache server and a network aware server that operates to determine an optimization between a cost of retrieving content from a communication network and a cost of caching content at the cache server. The optimization is determined as a minimum of a sum of a transit cost, a backbone cost, and a caching cost. The transit cost includes a money cost per data unit. The backbone cost includes a money cost per data unit and time unit. The caching cost includes a money cost per server unit. In response to determining the optimization, the network aware server sends a content identifier to the cache server, and the cache server receives the content identifier, determines a source of a content item, and if the source is the same as the content identifier, then cache the content item.

Abstract: A traffic classifier has a plurality of binary classifiers, each associated with one of a plurality of calibrators. Each calibrator trained to translate an output score of the associated binary classifier into an estimated class probability value using a fitted logistic curve, each estimated class probability value indicating a probability that the packet flow on which the output score is based belongs to the traffic class associated with the binary classifier associated with the calibrator. The classifier training system configured to generate a training data based on network information gained using flow and packet sampling methods. In some embodiments, the classifier training system configured to generate reduced training data sets, one for each traffic class, reducing the training data related to traffic not associated with the traffic class.

Abstract: A system includes an information storage module and an inspection module. The information storage module is configured to store a plurality of tags. Each tag is associated with a known set of traffic types of a plurality of known sets of traffic types. The inspection module is configured to compare a traffic flow to a set of traffic types to determine a matching set of traffic types, request a tag from the information storage module, and mark the traffic flow with the tag. The tag corresponds to the matching set of traffic types.

Abstract: A network includes a cache server and a network aware server that operates to determine an optimization between a cost of retrieving content from a communication network and a cost of caching content at the cache server. The optimization is determined as a minimum of a sum of a transit cost, a backbone cost, and a caching cost. The transit cost includes a money cost per data unit. The backbone cost includes a money cost per data unit and time unit. The caching cost includes a money cost per server unit. In response to determining the optimization, the network aware server sends a content identifier to the cache server, and the cache server receives the content identifier, determines a source of a content item, and if the source is the same as the content identifier, then cache the content item.

Abstract: An Internet service provider includes a cache server and a network aware server. The network aware server is operable to determine an optimization between a cost of retrieving content from a network and a cost of caching content from the network at the first cache server and then send a content identifier to the cache server. The cache server is operable to receive the content identifier, and determine the source of a content item. If the source is the same as the content identifier, then the cache server caches the content item.

Abstract: Methods, systems, and computer-readable media for providing network-based audience measurement are provided. Data packets are intercepted between a client computer and a content server. Unique subscribers and content names are identified based on the data packets. One or more audience measurement metrics are computed based on the unique subscribers and the content names.

Abstract: A traffic classifier has a plurality of binary classifiers, each associated with one of a plurality of calibrators. Each calibrator trained to translate an output score of the associated binary classifier into an estimated class probability value using a fitted logistic curve, each estimated class probability value indicating a probability that the packet flow on which the output score is based belongs to the traffic class associated with the binary classifier associated with the calibrator. The classifier training system configured to generate a training data based on network information gained using flow and packet sampling methods. In some embodiments, the classifier training system configured to generate reduced training data sets, one for each traffic class, reducing the training data related to traffic not associated with the traffic class.

Abstract: A system includes an information storage module and an inspection module. The information storage module is configured to store a plurality of tags. Each tag is associated with a known set of traffic types of a plurality of known sets of traffic types. The inspection module is configured to compare a traffic flow to a set of traffic types to determine a matching set of traffic types, request a tag from the information storage module, and mark the traffic flow with the tag. The tag corresponds to the matching set of traffic types.