50 results about "Self-balancing binary search tree" patented technology

A data organization system includes an index that offers fast retrieval of records and that protects records from logical modification. The index includes a balanced tree that grows from the root of the tree down to the leaves and requires no re-balancing. Each level in the tree includes a hash table. The hash table in each level in the tree can use a hash function that is different and independent from the hash function used in any other level in the tree. Alternatively, the hash table in each level in the tree can use a universal hash function. Possible locations of a record in the tree are fixed and determined by a hash function of a key of that record.

A tree-structured index to multidimensional data is created using occurring patterns and clusters within the data which permit efficient search and retrieval strategies in a database of DNA profiles. A search engine utilizes hierarchical decomposition of the database by identifying clusters of similar DNA profiles and maps to parallel computer architecture, allowing scale up past previously feasible limits. Key benefits of the new method are logarithmic scale up and parallelization. These benefits are achieved by identification and utilization of occurring patterns and clusters within stored data. The patterns and clusters enable the stored data to be partitioned into subsets of roughly equal size. The method can be applied recursively, resulting in a database tree that is balanced, meaning that all paths or branches through the tree have roughly the same length. The method achieves high performance by exploiting the natural structure of the data in a manner that maintains balanced trees. Implementation of the method maps to parallel computer architectures, allowing scale up to very large databases.

The embodiment of the invention discloses a data query method and a device, a storage medium and electronic equipment. The data query method comprises the steps of when a data query request is received, determining a first sheet key and a query condition according to the data query request; determining a first fragment corresponding to the first fragment key from a fragment cluster, determining atarget balance tree matched with the query condition from a plurality of balance trees stored in the first fragment, and storing non-leaf nodes in a memory; searching the target balance tree layer bylayer to obtain a first index meeting a query condition and data record information associated with the first index from the leaf node; and obtaining first data corresponding to the first index from the first fragment according to the data record information, and responding to the data query request based on the first data to realize efficient query of the data.

A system and methods to construct and maintain a balanced-tree overlay network are used to host distributed databases. As overlay nodes can detach from and re-attach to an overlay unpredictably, overlay protocols must maintain the overlay tree properly to minimize communication overheads associated with store and retrieval operations of the hosted databases. Unlike a DHT (distributed hash table) approach, the balanced-tree approach has the advantages of stabilizibility and provable correctness of the overlay protocols. Fast inquiry can be achieved by using a caching algorithm that allows each overlay node to keep track of data ranges stored in a neighboring set of nodes. Self-healing and load balancing protocols are also incorporated to enhance the performance and stability of the tree-structured overlay.

The embodiment of the invention discloses a file system quota managing method, device and system, is applied to the field of computers and is used for solving the defect of low quota operation efficiency in the prior art. The method comprises, when a file system is loaded, obtaining the quota entry of every file system quota from a storage object, wherein every quota entry contains the configuration data and the statistical data of the corresponding file system quota; generating a quota tree according to the lists of all the file system quotas, the memory management object of the quota tree comprises two memory self-balancing binary search trees, wherein the first memory self-balancing binary search tree serves for management of the quota entries of user quotas of all the file system quota, and the second memory self-balancing binary search tree serves for management of the quota entries of group quotas of all the file system quotas; updating the quota entries, and storing the updated quota entry of every file system quota in the storage object. The file system quota managing method, device and system is applicable to file system quota management.

The invention discloses a wireless sensor network key management method. The method comprises the steps that a base station distributes public and private key pairs to all sensor nodes according to set parameters, cluster head nodes are elected from all the sensor nodes, the elected cluster head nodes send information to the surrounding sensor nodes, the surrounding sensor nodes select the cluster head nodes of their own according to the information so that clusters can be formed, the base station generates a self-balancing binary search tree (AVL tree) of the in-cluster sensor nodes for all the clusters to generate the in-cluster sensor nodes, and the in-cluster sensor nodes inquire the information of the other sensor nodes according to the AVL tree, exchange information, mutually authenticate the legality of the public keys, and share the session keys after the authenticating is successful. According to the method, the AVL tree mode is utilized for storing the public keys and the identity information, the searching time is shortened, and the consumption is reduced; an elliptical curve password system is utilized for achieving key distribution and management, the higher safety of the network can be ensured, and the calculation expenditure can be reduced to the greatest extent.

A method of incrementally computing an aggregate function of a sliding window in a streaming application includes receiving a plurality of data tuples in the sliding window, extracting at least one data tuple from the sliding window, and storing the at least one extracted data tuple in a data structure in a memory. The data structure is a balanced tree and the at least one data tuple is stored in leaf nodes of the balanced tree. The method further includes maintaining at least one intermediate result in at least one internal node of the balanced tree. The at least one intermediate result corresponds to a partial window aggregation. The method further includes generating a final result in the balanced tree based on the at least one intermediate result, and outputting the final result from the balanced tree. The final result corresponds to a final window aggregation.

The invention provides a fast approximate K neighbor method based on a tree strategy and balanced K-means clustering, so as to improve the performance and speed of approximate K neighbor retrieval. The method comprises the following steps: firstly, constructing a balanced K-means tree through a balanced K-means clustering method, enabling data to be organized in a tree-shaped structure efficientlyand orderly, and realizing rapid positioning of any new sample data; then, utilizing an anchor positioning method and a neighbor cluster idea, and quickly finding a plurality of approximate neighborpoints, namely K neighbor points, of the new data sample through a balance tree. According to the method, the advantages of a tree-based K-nearest neighbor algorithm and a balanced K-means algorithm are taken into account at the same time, and the method can be applied to the fields of image recognition, data compression, mode recognition and classification, machine learning, document retrieval systems, statistics, data analysis and the like.

The invention discloses a non-structural grid nearest wall surface distance solving method based on a balanced KD tree. The method comprises the following steps: 1) establishing a balanced KD tree structure according to a central point of a wall surface unit; 2) for a certain target point in the space, searching k nearest wall surface units from the KD tree structure by taking the distance from the target point to the central point of the wall surface unit as an approximate nearest distance; and 3) aiming at the k wall surface units, accurately calculating the nearest distance between the target point and the k wall surface units, and selecting the minimum value as a calculation result. According to the method, the KD tree data structure of the object plane unit is established, and an optimized searching path and wall surface distance solving algorithm is adopted, so that the time complexity and the calculation amount of query are greatly reduced. According to the method, the calculation efficiency can be greatly improved on the premise of fully ensuring the calculation precision, and parallel calculation is easy to realize. Test results for thousands of thousands of magnitudes ofcalculation grids show that compared with a direct method, the method can shorten the calculation time by more than two orders of magnitudes.

The invention discloses a method for realizing image retrieval by mining distinguishing features from multiple relevant pictures. The method is characterized in that the method is finished by the generation of a flexible binary descriptor and feature matching on the basis of the binary descriptor. The flexible binary descriptor compares each dimension of an original floating-point type image feature with a corresponding reference value of each knot of a binary balance tree so as to convert the original floating-point type image feature into a binary form; and the feature matching firstly calculates similarity among features on the basis of the binary descriptor and then carries out normalization on the similarity scores of the features to successively select optimal-matching feature pairs, and the distinguishing features in the multiple relevant pictures can be found through the optimal-matching feature pairs. Although an amount of the distinguishing features is small, the distinguishing features represent the important visual content of the picture, the geometrical information of the picture is combined for retrieval, and therefore, a good retrieval result can be obtained.

The invention discloses a numerical value and text mixed inverted index algorithm based on a multilayer-optimization balanced tree. The traditional text inverted index only supports indexing on free texts, wherein the content of a numerical value is generally converted into a text, and then an inverted index is established according to the content of the text. According to the invention, the traditional text inverted index algorithm is optimized and expanded so as to be capable of supporting the indexing on numerical value and text mixed data, and a reasonable balance is realized in the aspects of query performance, index space and establishing performance. The index algorithm disclosed by the invention is suitable for being used in a mixed type data management engine and can be used for increasing the composite query performance of the numerical value and text mixed type data.

Disclosed is a high-speed information interaction system based on an FPGA-CPU mixed architecture. The system comprises an FPGA module, a central control module and an interaction terminal, wherein the FPGA module is in data communication with the central control module through a PCIe interface, the central control module receives multi-path TCP demand data for external selection, stores historical demand data and generates and maintain a historical data pricing table; the FPGA manages and maintains a real-time data pricing table generated according to the real-time demand data, the historical data pricing table and the real-time data pricing table are called according to the trigger of the interaction terminal to execute corresponding operation instructions to conduct quick decision-making and order combination, an interaction instruction is generated, and information interaction is achieved through the interaction terminal; the content of the real-time data pricing table is sorted through the adoption of a hardware bitonic sorting method, and the content of the historical data pricing table is sorted through the adoption of a balanced tree method. According to the high-speed information interaction system based on the FPGA-CPU mixed architecture, the delay of interaction between the FPGA and the CPU is controlled within a better delay range, a flexible and effective communication mode is adopted, the respective processing characteristics of the FPGA and the CPU take effects, and the speedup ratio of the mixed architecture system is increased.

The invention discloses a data processing method, a data access method, a data access device and computer equipment. The data processing method comprises the following steps: reading the access frequency of each piece of data stored in a key value storage system, wherein in each hash table of the key value storage system, an ordered linked list is adopted to store data, the data access popularityin each linked list node of the ordered linked list is sequentially reduced, and a balance tree is stored in each linked list node of the ordered linked list, performing data storage in each balance tree based on the key value size of the data; when the access frequency of the target data does not belong to an access popularity interval corresponding to the balance tree, searching a target accesspopularity interval corresponding to the access frequency of the target data; and migrating the target data to the balance tree of the linked list node corresponding to the target access popularity interval. According to the method, all the data does not need to be traversed during data access, so the read-write performance of the data can be improved; and the higher the access popularity is, theshorter the search time required for accessing of the data is.

A distribution network, comprises: circuit blocks having counters, wherein the counters are synchronized relative to an input signal; drivers connected in a balanced tree for distributing the input signal synchronously to the circuit blocks; and drivers connected in an unbalanced tree for distributing a reset signal to the circuit blocks, wherein the input signal is distributed via the balanced tree as a function of the reset signal.

The invention provides a communication system, a cache server and a cache content pushing and finding method and system. The cache server establishes a balance tree and a dictionary tree according to the type of a cache pushing request and judges the type of the received cache pushing request, a matched tree node is found according to the balance tree when the type is a regular expression type, a matched tree node is found according to the dictionary tree when the type is a relative path type, and after the matched node is found, the cache content corresponding to the node is updated. The cache content is flexibly stored and found in different modes according to the type of a pushing rule of the cache pushing request, the complexity of time for finding is low, and accuracy is high.

The invention provides a data monitoring method based on cloud computing. A user file is verified through adoption of a full storage tree. The full storage tree specifically comprises the fact that the full storage tree is established by taking a balance binary search tree as a basic structure; each node of the full storage tree stores the following content: 1), a file block m at the node; 2), a hash value H=H(m) of the file block of the node; 3), a joint hash value H<sum>(i), wherein if the i is a leaf sub-node, the H<sum>(i) is equal to the Hi, otherwise, the hash value of a father node is solved according to the hash value of the ith sub-node of the node, iterative calculation is carried out until the hash value of a root node of the full storage three, namely the hash value H(Root) of the whole full storage tree, is obtained. The method comprises the steps of (1), storing data; (2), initiating a verification request; (3), generating a verification message; and (4), carrying out verification. According to the method provided by the invention, the data processing efficiency is improved and the occupied storage space is reduced.