At&t Intellectual Property I, L.p.

Huawei Technologies Co., Limited

At&t Intellecutal Property I, L.p.

Ke Yi

Graham Cormode

Zhenguo Li

Ge Luo

Wei Fan

Cheng He

Yongjian Hu

Qin Zhang

Feifei Li

Divesh Srivastava

Xiang He

Marios Hadjieleftheriou

Wei Xue

George Kollios

Wangqian Li

Jiadao Wei

Yanwen Xiang

This application relates to a slot negotiation method and a device. The method includes: A transmitter sends a first FlexE overhead frame to a receiver, to request active/standby calendar switching. When the receiver is in a restart state, the receiver does not respond to the received first FlexE overhead frame. In addition, the RX sends a routine update second FlexE overhead frame to the transmitter. Determining that the second FlexE overhead frame is not a response to the first FlexE overhead frame, the transmitter sends a third FlexE overhead frame to request active/standby calendar switching again. According to the method in this application, incorrect calendar switching on the transmitter side caused by a mistaken response of the receiver can be avoided. This reduces the likelihood of a service interruption caused by the existing slot negotiation mechanism.

Slot negotiation method and device

A port mode adaptation method includes a network device determining a status of a port on the network device. The method includes the network device setting a mode of the port to an Ethernet interface mode if the status of the port satisfies a first condition. In this way, when the network device identifies the mode of the port on the network device as the FlexE interface mode, and there is no link at the FlexE shim of the port, the network device may determine that a mode used by a port interconnected with the port is not a FlexE interface mode. In this case, the network device may adaptively set the mode of the port to the Ethernet interface mode, to ensure that the port on the network device can use a same mode as another port interconnected with the port.

Port mode adaptation method and apparatus

A data processing method, includes receiving a data flow; generating a triplet set according to the data flow, where each triplet in the set includes three items, the first item is a first element in the data flow, the second item includes a first time point at which the first element appears in the data flow and a first quantity of times that corresponds to the first time point, and the third item includes a second time point at which the first element appears in the data flow and a second quantity of times that corresponds to the second time point; and performing data processing on the data flow according to the triplet set. In the embodiments of the present application, the triplet set may be generated based on the data flow.

Data processing method and apparatus

A method for compressing flow data, including: generating multiple line segments according to flow data and a predefined maximum error that are acquired; obtaining a target piecewise linear function according to the multiple line segments, where the target piecewise linear function includes multiple linear functions, and an intersection set of value ranges of independent variables of every two linear functions among the multiple linear functions includes a maximum of one value; and outputting a reference data point according to the target piecewise linear function, where the reference data point includes a point of continuity and a point of discontinuity of the target piecewise linear function. In this way, a maximum error, a target piecewise linear function is further determined according to the multiple line segments, and a point of continuity and a point of discontinuity of the target piecewise linear function are used to represent compressed flow data.

Method and device for compressing flow data

A method for compressing flow data, including: constructing multiple line segments according to flow data and a predefined maximum error that are acquired; obtaining a target piecewise linear function according to the multiple line segments, where the target piecewise linear function includes multiple linear functions, and an intersection set of value ranges of independent variables of every two linear functions among the multiple linear functions includes a maximum of one value; and outputting a reference data point according to the target piecewise linear function, where the reference data point includes a point of continuity and a point of discontinuity of the target piecewise linear function. In this way, a maximum error, a target piecewise linear function is further determined according to the multiple line segments, and a point of continuity and a point of discontinuity of the target piecewise linear function are used to represent compressed flow data.

The present disclosure is directed to systems, methods, and computer-readable storage media for sampling from distributed data streams. Data elements are received at site servers configured to collect and report data to a coordinator device. The site servers assign a binary string to each of the data elements. Each bit of the binary strings can be independently set to a 0 or a 1 with a probability of one half. The binary string is used to sample from the received data elements, and the data elements and/or the sampled data elements can be transmitted to a coordinator device. The coordinator device can examine one or more bits of the binary string to draw samples of the received data elements in accordance with desired probabilities.

Sampling from distributed streams of data

Methods and apparatus for ranking uncertain data in a probabilistic database are disclosed. An example method disclosed herein comprises using a set of data tuples representing a plurality of possible data set instantiations associated with a respective plurality of instantiation probabilities to store non-deterministic data in a database, each data tuple corresponding to a set of possible data tuple instantiations, each data set instantiation realizable by selecting a respective data tuple instantiation for at least some of the data tuples, the method further comprising determining an expected rank for each data tuple included in at least a subset of the set of data tuples, the expected rank for a particular data tuple representing a combination of weighted component ranks of the particular data tuple, each component rank representing a ranking of the data tuple in a corresponding data set instantiation, each component ranking weighted by a respective instantiation probability.

Methods and apparatus for ranking uncertain data in a probabilistic database

A method for validating outsourced processing of a data stream arriving at a streaming data warehouse of a data service provider includes a proof protocol. A verifier acting on behalf of a data owner of the data stream may interact with a prover acting on behalf of the data service provider. The verifier may calculate a first root hash value of a binary tree during single-pass processing of the original data stream with limited computational effort. A second root hash value may be calculated using the proof protocol between the verifier and the prover. The prover is requested to provide certain queried values before receiving random numbers used to generate subsequent responses dependent on the provided values. The proof protocol may be used to validate the data processing performed by the data service provider.

Interactive proof to validate outsourced data stream processing

A method and system of monitoring computer network activity including determining a first phase frequency estimate, associated with a first frequency vector, determined in response to receiving first bits from a first plurality of remote computer network devices. The first bits received from the first plurality of remote devices in response to satisfying a first activity threshold. Also, determining a second phase frequency estimate associated with a second frequency vector and determined in response to receiving second bits from a second plurality of remote devices. The second bits received from the second plurality of remote devices in response to a second activity threshold being satisfied. The second phase frequency estimate determined in response to the first phase frequency estimate exceeding a global threshold. Further, providing a frequency moment Fin response to the second phase frequency estimate exceeding a refined threshold.

Method and apparatus for monitoring functions of distributed data

Embodiments disclosed herein are directed to verifying query results of an untrusted server. A data owner outsources a data stream to the untrusted server, which is configured to respond to a query from a client with the query result, which is returned to the client. The data owner can maintain a vector associated with query results returned by the server and can generate a verification synopsis using the vector and a seed. The verification synopsis includes a polynomial, where coefficients of the polynomial are determined based on the seed. The data owner outputs the verification synopsis and the seed to a client for verification of the query results.

Verification of outsourced data streams

This invention discloses continuous functional monitoring of distributed network activity using algorithms based on frequency moment calculations given byF=&#x3a3;m.The frequency moment calculations are used to raise an alarm when a value exceeds a certain threshold. Frequency moments for p=0, 1, and 2 are described.

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Hong Kong, China

Ke Yi