A transmission method and a transmission device for a control plane message are provided. The method includes: compressing a control plane message by using a dictionary supported by a transmitting end; and transmitting the control plane message that is compressed by using the dictionary and identification information of the dictionary to a receiving end.

Disclosed in the present disclosure are a processing method and device for a cache synchronous exception, for solving the problem that no solution for a compression check failure is available in the prior art. According to embodiments of the present disclosure, when caches are out of synchronization, a caching failure notification message is sent to a transmitting device; a reset processing is carried out on a compressed cache area, and a reset instruction is sent; and then subsequent data packet transmission is carried out by using reset cache areas. In the present disclosure, after it is determined that the caches are out of synchronization, the caching failure notification message is sent; the transmitting device performs a reset processing on the compressed cache area, and notifies a receiving device to carry out a reset processing on a decompressed cache area.

A method by a network device for detecting data in a data stream. The method includes receiving the data stream, where the data stream includes a sequence of original characters, generating a sequence of type-mapped characters corresponding to the sequence of original characters, converging each of two or more consecutive occurrences of a first character in the sequence of type-mapped characters into a single occurrence of the first character, searching for occurrences of one or more predefined sequences of characters in the sequence of type-mapped characters, and responsive to finding an occurrence of any of the one or more predefined sequences of characters, extracting a sequence of characters in the sequence of original characters corresponding to the occurrence of the predefined sequence of characters found in the sequence of type-mapped characters.

An information processing device executes a process includes determining whether or not encoding target data is in an inflective form of a word when the encoding target data included in target sentence data is encoded; and registering the encoding target data and a code assigned to the encoding target data in a dynamic dictionary in association with each other, in a case where the encoding target data is in the inflective form of the word.

Data units of a dataset may be compressed by clustering the data units into clusters, selecting a reference unit for each unit cluster, and compressing data units of each unit cluster using the reference unit of the unit cluster as a dictionary. The computational efficiency of the clustering algorithm may be improved by not applying it to data units themselves, but rather to hash values of the data units, where the hash values have a much smaller size than the data units. The hash function may be a locality-sensitive hash (LSH) function. The reference unit of a cluster may be determined in any of a variety of ways, for example, by selecting a centroid or exemplar of the cluster. Clusters, including their references values, may be indexed in a cluster index (e.g., a Faiss index), which may be searched to assign future added or modified data units to clusters.

According to one embodiment, a compression device includes a first storage unit, a second storage unit, a calculation unit, and a comparison unit. The first storage unit stores addresses associated with hash values, respectively. The second storage unit includes storage areas specified by the addresses, respectively. The calculation unit determines a hash function to be used for first data in accordance with at least a part of the first data, and calculates a hash value using the hash function and at least a part of second data included in the first data. The comparison unit acquires third data from a storage area in the second storage unit specified by a first address, and compares the second data with the third data. The first address is stored in the first storage unit and is associated with the hash value.

Examples relate to detection of anomalies in a network. Some examples determine a dictionary including a set of keys for a set of packet length values for a selected sequence of packets associated with a traffic flow over a network, each key represents a combination of two or more successive packet length values from the set of packet length values. An aggregated set of statistical features is determined based in part on the set of statistical features using a machine learning algorithm. Upon determining another set of packet length values for another selected sequence of packets, another set of statistical features for the other set of packet length values is determined. The other set of statistical features is compared with the aggregated set of statistical features. Based on the comparison, an indication that an anomaly has occurred in the traffic flow is transmitted to an administrator.

Herein are fine grained updates to pieces of JavaScript object notation (JSON) documents by database statements that can update, delete, and insert parts of JSON documents. In an embodiment, a computer receives a request that specifies a modification of a JSON document that is stored in a compressed format in persistent storage. The modification adds additional content to the JSON document, and/or replaces an old value in the JSON document with a new value that is not a same size as the old value. The modification is recorded in a change log. The change log is eventually applied to the compressed format of the JSON document in the persistent storage without entirely rewriting the compressed format of the JSON document in the persistent storage.

The present disclosure relates to a system and method for compressing a dataset. The dataset can be divided in to a plurality of groups. Each group can be converted independently into corresponding text file using dictionary coding technique. The corresponding text files can be compressed independently into corresponding compressed files. Finally, all the corresponding compressed files can be combined together to generate a complete compressed data.

A computerized method of compressing symbolic information organized into a plurality of documents, each document having a plurality of symbols, includes: (i) automatically identifying a plurality of sequential and non-sequential symbol pairs in an input document; (ii) counting the number of appearances of each unique symbol pair; and (iii) producing a compressed document that includes a replacement symbol at each position associated with one of the plurality of symbol pairs, at least one of which corresponds to a non-sequential symbol pair. For each non-sequential pair the compressed document includes corresponding indicia indicating a distance between locations of the non-sequential symbols of the pair in the input document. In some instances the plurality of symbol pairs includes only those pairs of non-sequential symbols for which the distance between locations of the non-sequential symbols of the pair in the input document is less than a numeric distance cap.