51 results about "HashClash" patented technology

The invention provides a method and a system for processing Hash collision. The method includes separating list items which include a first list item corresponding a first Hash function and a second list item corresponding to a second Hash function and store Hash data; receiving Hash key words and judging whether the Hash collision exists or not, if collision exists in the first list item, storing the Hash key words to the corresponding position of the second list item according to the second Hash function; if no collision exists, storing the Hash key words into the corresponding position of the first list item according to the first Hash function; searching clauses corresponding to the Hash key words sequentially in the first list item and the second list item according to the first Hash function and the second Hash function. On the basis of keeping hardware cost constant, incidence rate of the Hash collision is decrease effectively.

The invention discloses an editable block chain system, which comprises a first chain and a second chain, wherein the first chain and the second chain are connected through a common node; wherein thefirst chain has an editing control smart contract; wherein the common node is provided with a trap door fragment, and the trap door fragment is used for synthesizing a trap door; the common node is used for initiating an editing behavior, synthesizing a trap door according to the trap door fragment, verifying the trap door through the editing control smart contract, calculating a hash conflict value according to the original content, the original random number and the target content after verification is passed, publishing the target content and the hash conflict value to the second chain; andenabling a node in the second chain to verify the target content and the hash conflict value, and replaces the original content with the target content if the target content and the hash conflict value pass the verification. The system has the advantages that the requirement for data storage safety can be met, and the requirement for data modification under specific conditions can also be met.

The invention belongs to the field of computer hash data structures, in particular to a data structure for hash operation and a hash table storage and query method based on the structure. In order toensure the query efficiency, a dual-port memory bank is adopted for hardware implementation, the content of two addresses of the memory bank can be read at the same time, key value comparison can be completed within the determined time, and the method is suitable for achieving efficient query in an assembly line mode. More candidate positions are provided through more hash operations, the probability of hash conflicts is reduced, the insertion, storage and updating efficiency of hash table entries is improved, dynamic change of hash table entry capacity is supported, space waste or performancereduction caused by table entry insertion operation is avoided, and the method is suitable for applications with unknown and constantly changing hash table entries. A CRC algorithm is adopted as a hash function, a hash calculation result has good uniqueness, the hash calculation result can be obtained on the basis of XOR exclusive-OR operation and a parallel pipeline implementation structure during specific implementation, and hardware design implementation is facilitated.

The invention discloses a scalable-ot-based privacy set intersection method and device, and the method comprises the steps that: a first data party calculates current first to-be-processed data through employing a first Hash algorithm, obtains a first calculation result, and judges whether the first calculation result has a Hash conflict with all currently generated first Hash tables or not; if the first calculation result has the Hash conflict with all currently generated first Hash tables, a new first hash table is generated to store the current first to-be-processed data; and the steps are repeated until all the first to-be-processed data are calculated, a second data party calculates second to-be-processed data through a second hash algorithm, a second hash table is generated according to an obtained second calculation result, intersection data of all the first to-be-processed data and the second to-be-processed data is calculated according to all the first hash tables and the second hash tables, and a privacy intersection is generated according to the intersection data. The situation that the intersection result is obtained by repeating the whole calculation process for many times can be avoided, the calculation amount of intersection is greatly reduced, the calculation efficiency is improved, and the whole calculation process is more concise.

A hash table data structure is provided that reduces the number of DMA operations, and if possible, the number of key comparisons, needed to traverse the table entries to find an entry that matches a key, especially with a bucket having several collisions. A new hash table entry called a “cumulative node” is introduced, which stores keys into a “key table” within the entry and includes pointers to metadata associated with the keys. The number of entries stored in the cumulative node depends on the size of the cumulative node, key size, and the size of the pointer type.

The invention discloses a small flow filtering-based active large flow accurate detection architecture and method, and the architecture comprises a small flow filter which is used for filtering most small flows in a network, reducing the resource overhead, and reducing the Hash conflict rate; and the active large flow detector is used for extracting the active large flow in the network and improving the identification precision of the active large flow. According to the method, the small flow filter is constructed by using the thought of cycle updating, so that the resource overhead is reduced, and meanwhile, the filter can continuously and effectively filter the small flow. Meanwhile, an active large flow detector is constructed based on a Hopscotch Hashing algorithm, and inactive flows are screened out through an LRU strategy while Hash conflicts are reduced, so that Top-k flows in the network are accurately identified.

The invention provides a data storage method. The method comprises the steps of judging whether a fingerprint value exists in local storage or not when the fingerprint value of to-be-stored data is received; if yes, storing the to-be-stored data into an independent storage area; judging whether the to-be-stored data is the same as stored data corresponding to the fingerprint value in the local storage or not; if yes, deleting the to-be-stored data from the independent storage area; and if not, transferring the to-be-stored data from the independent storage area to the local storage. Accordingto the method, the problem of data mistaken deletion possibly caused by hash conflicts is solved by utilizing the independent storage area, and the data storage consistency is ensured. The invention further provides a data storage system, a computer readable storage medium and a server, which have the above beneficial effects.

The invention discloses a hash conflict processing method and system. The method comprises the steps of S1, judging whether a hash conflict occurs in a keyword corresponding to data needing to be added or not; s2, if yes, respectively calculating hash values corresponding to the keywords in a plurality of hash buckets, and obtaining a plurality of conflicting data in the plurality of hash buckets;and S3, selecting a hash bucket, and moving one piece of conflicting data in the hash bucket to another hash bucket. According to the invention, the hash conflict can be effectively solved by using data migration of depth-first search, so that the utilization rate of the storage space is improved, the use of a hash conflict solution table is reduced, and the cost and the power consumption are greatly reduced.

The invention provides an indexing method and system for a concurrent hash index data structure based on machine learning. The indexing method comprises the steps of M1, searching a group node where atarget key value pair is located for from a root node according to a key in a request; M2, in the group nodes obtained through positioning, calculating data positions according to a machine learningmodel of the group nodes; and M3, searching target data according to the data position, and carrying out corresponding operation according to the request type. Compared with an existing machine learning hash index, the system can retrain the machine learning model, hash expansion operation is carried out when the hash conflict probability exceeds a threshold value, the machine learning model is made to adapt to newly inserted data, and the high performance of the index is kept.

The invention discloses a point cloud dynamic Hash division method and equipment, and the method comprises the steps: determining the total number of division times according to the total number of occupied nodes of a current node layer of a tree structure and an average node number threshold value in a single Hash table after division; determining the number of hash tables corresponding to the current node layer; determining the division times of each coordinate component; and determining a hash table corresponding to the node according to the number of hash tables corresponding to the current node layer, the division times of the coordinate component and the occupied node position data of the current node layer, and adding the node into the hash table corresponding to the node. A plurality of hash tables is configured on each node layer, the serial numbers of the hash tables corresponding to the nodes are determined according to the position data of the occupied nodes of the current node layer, the nodes are added to the hash tables corresponding to the nodes, and the nodes in the different hash tables do not have hash conflicts, so that when that the performance is not lost, the access performance of the hash tables is optimized, and the insertion and query efficiency of the hash tables is improved.

The invention discloses an efficient rule matching method for an FPGA. Filtering the message at a linear speed by using fixed group delay; adding a numerical value to the keyword string of the hash conflict; hash operation is carried out again to solve the Hash conflict problem. The data read from the result of the first hash operation is used as a numerical value C or 0; and after adding the keyword string, carrying out hash operation again, comparing the data read by the result of the second hash operation with the index address of the matching rule, discarding the message which does not meet the requirement in the message cache queue according to the matching result, and outputting the message which meets the requirement, thereby realizing accurate filtering output of the message.

The embodiment of the invention relates to the field of communication, and discloses a hardware accelerated query method and system, electronic equipment and a storage medium. In the embodiment of theinvention, the hardware accelerated query method comprises the following steps: acquiring p groups of characteristic values of a data stream; respectively carrying out hash operation on the p groupsof characteristic values to obtain p hash values respectively corresponding to the p groups of characteristic values; performing exclusive-OR operation on the p hash values, and taking an operation result as an index value corresponding to the data stream; and querying a preset array according to the index value, wherein the preset array comprises each data stream needing to be subjected to hardware acceleration and a preset index value of each data stream needing to be subjected to hardware acceleration. According to the method, the hash algorithm in the hardware accelerated query process ismodified by combining the actual use scene of the home gateway, so that the regularity of the internal characteristic value of the data stream is reduced compared with the operation adopting a singlecharacteristic value, and the hash conflict in the hash algorithm is reduced on the premise of ensuring the actual transmission time.

The invention discloses a rapid stereo matching method based on ZSAD-Census, and the method comprises the following steps: S1, carrying out the initialization configuration before the stereo matching of each frame of image is started; S2, inputting a target image and a reference image, traversing each pixel in the images, and calculating ZSAD information and Census information; S3, jointly using the ZSAD information and the Census information of the reference image, or adopting independent ZSAD information or Census information, constructing a hash function, constructing hash tables through the hash function, wherein each hash table is used for solving hash conflicts by constructing a chain table; and S4, calculating the hash value of the current pixel, and searching the position of the reference pixel with the same hash value as the current pixel. According to the invention, the problems of large power consumption and high area cost in the prior art are solved, and the accuracy and anti-interference performance of a stereo matching algorithm are improved.

The invention discloses a dynamic hash method and device, equipment and a storage medium. The method comprises the steps: obtaining the historical data of accessing a to-be-updated original hash tablein history, and determining the frequency of accessing a corresponding record located in the original hash table in history based on the historical data; generating a corresponding hash function based on the frequency corresponding record higher than the frequency threshold, so as to minimize the possibility of hash conflict when accessing the record of which the frequency is higher than the frequency threshold based on the generated hash function; creating a hash table corresponding to the generated hash function, and inserting each record contained in the original hash table into the generated hash table according to the generated hash function; and replacing the original hash table with the generated hash table, and replacing the hash function corresponding to the original hash table with the generated hash function. According to the method, the efficiency of the hash algorithm can be improved, so that the program running efficiency of the program to which the hash algorithm belongs is improved.

The invention discloses a method and system for avoiding a Hash collision during MAC address learning, and belongs to the testing field of network communications. The method comprises the following steps that S1, a source MAC address, a VLAN ID and a port number are resolved from a message; S2, Hash calculation is conducted on the resolved source MAC address and the VLAN ID, Hash locating is conducted on an MAC address table in a chip, if locating is achieved, the chip MAC address table is updated, the S8 is executed, and otherwise the S3 is executed; S3, the information of the source MAC address, the information of the VLAN ID and the information of the port number are stored in the MAC address table. The method and system for avoiding the Hash collision during MAC address learning have the advantages that the hardware chip gives out interrupt information to quickly locate the Hash collision in the MAC addresses, a software collision detecting unit is used for detecting, and the Hash collision in the MAC addresses is quickly solved in the mode that a TCAM table stores collision MAC addresses.