55 results about "Packet classification" patented technology

The invention relates to a packet classification device for flow table normalization storage, electronic equipment and a storage medium, and the device comprises a flow table normalization unit which is used for cutting an original rule set according to two dimensions of a matching domain and a rule domain of the original rule set to obtain rule subsets; the storage mapping unit is used for determining a comparison and selection character string; matching the comparison and selection character string with the rule subsets corresponding to the lengths to obtain first matching results, and forming a single rule subblock by the first matching results corresponding to the same rule subset; taking the regular sub-blocks as a whole, and storing the first matching result in the regular sub-blocks into a storage device; the packet classification searching unit is used for reading a target first matching result matched with a packet header character string from the storage device based on the packet header character string of a to-be-classified data packet; and determining a target forwarding rule corresponding to the to-be-classified data packet based on the target first matching result. Therefore, the scale of the flow table can be improved, and the to-be-classified data can be classified more finely.

The invention provides a fast and accurate packet classification method based on a learning index, which comprises the following steps: dividing a global rule set into a plurality of rule subsets, and dynamically dividing a key value sequence of each subset into segments with similar distribution trends based on a linear fitting error; the floating point slope parameter and the floating point intercept parameter of each piecewise linear model are coded into integer pairs in a base number-index form, and a lightweight prediction model supporting pure integer operation is constructed; when a to-be-classified data packet is received, all the segment models in each rule subset execute prediction in parallel, and a compact rule group index associated with a target segment is output; and performing parallel retrieval on the rule groups associated with each segment based on the index, and selecting the highest priority rule from matching results of all the rule groups to complete data packet classification.

A method for processing packets, the method comprising receiving a packet by a data processing unit (DPU), making a first determination that there is no exact match flow entry in a hardware switch pipeline in the DPU for the packet, in response to the first determination, classifying, in the DPU, the packet as a data packet, in response to the classifying of the packet: identifying, using a software data plane in the DPU, a forwarding information base (FIB) entry to be used to transmit the packet towards its intended destination, identifying, using the software data plane, a flow associated with the packet, initiating, using the software data plane, programming of an exact match flow entry in the hardware switch pipeline, and initiating, using the software data plane, transmission of the packet towards its intended destination using the FIB entry and the hardware switch pipeline.

Embodiments of the present application disclose a log packet classification method and a computing device, which are used for classifying a to-be-classified log packet. In the present application, the computing device first determines a plurality of feature types of the to-be-classified log packet, and then determines a plurality of model parameters of the to-be-classified log packet based on the plurality of feature types. Next, the computing device calculates similarities between the to-be-classified log packet and each of K log packet types based on the plurality of model parameters, and obtains K similarities. Finally, the computing device determines a log packet type to which the to-be-classified log packet belongs from the K log packet types according to the K similarities. Thus, the to-be-classified log packet that does not conform to any rule of any of the K log packet types can also be classified.

The application discloses a kind of combination packet classifier and method based on hash and TCAM, adopt the combination of imperfect hash classification module and TCAM classification module, the complement of imperfect hash classification and TCAM classification on input key value space is realized;Compared with the traditional TCAM packet classification solution based on, the application reduces hardware resource utilization, system power consumption;Compared with the packet classification solution based on perfect hash, the application reduces the design cost of hash function and the time complexity of generation process under the premise of guaranteeing the function of classifier.The application can consider low space resource consumption, low power consumption and low delay in the classification stage, saves design cost in the classifier generation stage, and reduces the time complexity of generation process;Meanwhile, the application can better balance different types of hardware resources on reconfigurable hardware platforms such as FPGA, and provides a new way of thinking for the design of classifier in network tasks such as firewall packet filtering and routing table lookup.

Technologies for programming flexible accelerated network pipelines include a comping device with a network controller. The computing device loads a program binary file that includes a packet processing program and a requested hint section. The binary file may be an executable and linkable format (ELF) file with an extended Berkeley packet filter (eBPF) program. The computing device determines a hardware configuration for the network controller based on the requested offload hints and programs the network controller. The network controller processes network packets with the requested offloads, such as packet classification, hashing, checksums, traffic shaping, or other offloads. The network controller returns results of the offloads as hints in metadata. The packet processing program performs actions based on the metadata, such as forwarding, dropping, packet modification, or other actions. The computing device may compile an eBPF source file to generate the binary file. Other embodiments are described and claimed.

Disclosed is a system (104) and a method (500) for stream-based packet processing in a communication network. The method comprises receiving values corresponding to a plurality of configuration parameters including a parsing unit count. The method further comprises receiving, from a network interface, a plurality of packets corresponding to one or more data streams based upon the values of the plurality of configuration parameters and forming one or more batches of the plurality of packets based on the values corresponding to the plurality of configuration parameters. The method further comprises retrieving the one or more batches stored in a shared memory based on the value of the parsing unit count. The method further comprises parsing the plurality of packets in the retrieved batches to extract protocol header fields and classifying, based on the parsing, the plurality of packets into parsed packets and unparsed packets to enable the stream-based packet processing.

The invention provides a network communication device and method with a dynamic packet transmission sorting mechanism. The packet classification circuit sets each low-latency packet as a selected low-latency packet for storage in a corresponding selected low-latency queue circuit. The transmission sorting circuit calculates a queue time parameter for the selected low-delay packet to sort the selected low-delay packet with other low-delay packets so as to update a sorting list. Wherein the queue time parameter is the proportion of the total queue time of the selected low-delay packet stored in the selected low-delay queue circuit exceeding the dynamic service time threshold value set corresponding to the selected low-delay queue circuit. The communication circuit sequentially transmits the low-latency packets according to the sorting list. The dynamic adjustment circuit calculates the difference between the total packet transmission time of the selected low-delay packet and the target delay threshold value so as to dynamically adjust the dynamic service time threshold value according to the difference.

The present application relates to the field of computer network security technology. The present application provides a network packet classification method based on field distribution entropy and coverage difference, including: obtaining a rule set for a network data packet; dividing the rule set into multiple levels, selecting a rule set with a high optimization level as a candidate rule set; traversing multiple bit segments in the candidate rule set and performing a comprehensive score; selecting the best partitioned bit segment based on the comprehensive score and constructing a tuple hash bucket; establishing a hash table based on the actual value length of the best partitioned bit segment, and distributing the rules to the corresponding tuple hash bucket; traversing each tuple hash bucket for judgment and recursive processing; when the rules of all tuple hash buckets are effectively divided, the tuple hash subtree of the current node is constructed, and the process of rolling back to the previous level or completing the construction of the entire tree is completed. The present application addresses the deficiencies of packet classification technology in terms of search efficiency, structural balance, space utilization, and rule update support.

Systems and methods for determining whether to perform deep packet inspection (DPI) on packets received at a network device based on shallow packet inspection data are disclosed. Embodiments may include DPI classification data in a combined lookup table that is utilized for shallow packet data based packet classification at a network device. Using the results of lookups in such a combined look table based on received packets, determinations can be made whether to perform DPI on such received packets, and those packets forwarded accordingly.

Systems, methods, apparatuses, and computer program products for computer program products for application-centric processing on servers using mobile network connectivity (e.g., 5G system (5GS) connectivity, 6G system (6GS) connectivity, and so forth). A method may include getting information associated with data network terminations. The method may also include establishing, based on the received information, tunnels to setup connectivity between a plurality of data network terminations. The method may further include ensuring that traffic related with edge application servers is sent on the tunnels based on a given quality of service requirement. In addition, the method may include ensuring a given quality of service requirement and / or packet classification information to the traffic.

The application provides a packet classification parallel method and system based on ensemble learning, comprising the following steps: S1, establishing a rule search cost model to quantify the complementarity between different instances of an algorithm; S2, using a genetic algorithm to generate an optimal combination scheme of different instances of the algorithm, and after finding an algorithm instance meeting the requirements, constructing an algorithm instance library; and S3, constructing a packet classification prediction model, and selecting a suitable algorithm instance from the constructed algorithm instance library to complete a packet classification operation. The application first acutely observes the worst case existing in the existing packet classification method and the cause thereof, and under the enlightenment of ensemble learning, mines the complementarity existing between different instances of an algorithm to optimize the performance.

A plurality of captured packets are received. The plurality of captured packets are from a plurality of packet flows. A packet flow is a communication session between two devices. For example, a packet flow may be a communication session between a client and a server. The plurality of captured packets are sorted into individual packet flows. The individual packet flows are converted into individual videos. For example, each packet from each packet flow is stored as a separate video frame in an individual video. A machine learning algorithm is applied to the individual videos to perform analytic tasks on the individual videos. For example, the machine learning algorithm may be used to identify anomalies within a packet flow and / or between packet flows.

The invention belongs to the field of computer networks, and discloses a dynamic data packet classification method and system based on a dictionary tree and a multilevel decision tree, and the method comprises the steps: S1, constructing the dictionary tree for IP prefixes of all rules in a preprocessing stage of data packet classification; s2, obtaining prefix huge change points based on the dictionary tree; s3, dividing rule subsets based on the prefix huge change points to obtain accurate rule subsets and complex rule subsets; s4, constructing a main decision tree for the accurate rule subset; inputting the complex rule subset into Box for processing; and S5, constructing a shadow tree or a shadow Box copy of the rule modification operation, and performing pointer replacement through a CAS atomic instruction. According to the method, structural layering, behavior driving and field decoupling are taken as a core design concept, rule pre-division, path structure optimization, update behavior perception and an efficient matching mechanism are comprehensively integrated, and the problems of rule replication redundancy, low path efficiency, dynamic update response lag and the like in data packet classification are solved in a breakthrough manner.

The present invention relates to a method for implementing a multi-layer tuple space data packet classification algorithm based on a single hash table, and belongs to the field of communication technology. Compared to existing multi-layer tuple space data packet classification algorithm implementations using multiple hash tables, the multi-layer tuple space data packet classification algorithm based on a single hash table implementation simplifies hash table management and is well-suited for implementation in an FPGA. Furthermore, the number of accesses to the tuple space data structure (Tuple), hash node data structure (HashNode), and rule data structure (Rule) in the multi-layer tuple space data packet classification algorithm is also reduced, thereby reducing the number of memory accesses, thereby improving the performance of the multi-layer tuple space data packet classification algorithm.

A hardware-based framework is provided that enables a network device to accurately estimate the cardinality of (or in other words, the number of unique elements in) a stream of network packets processed by the device, using minimal memory and compute resources. For example, this framework can enable the network device to accurately estimate the number of unique network flows in the packet stream, the number of unique source Internet Protocol (IP) addresses in the packet stream, the number of unique flows for each of a plurality of packet classification characteristics (e.g., ingress ports on which the packets were received, egress ports on which the packets are sent out, etc.), and so on.

A method of providing differential security services for a ship network by a service provider connected to a client performing the differential security services may comprise: receiving a service request from a user terminal by an authentication performing unit of a service provider including a processor; returning or issuing, by the authentication performing unit, an ID token and an authentication code to the user terminal in response to the service request; receiving, by the client, the ID token and the authentication code from the user terminal; verifying, by the client, validity of the ID token; setting, by the client, a session cookie for the service request when the validity is verified; transmitting, by the client, an access token request including the authentication code to a token issuing unit of the service provider; and receiving, by the client, an access token from the token issuing unit.

An ultra-high speed electronic communications device includes: a network communications interface; a memory; and one or more processing units, communicatively coupled to the memory and the network communications interface, wherein the memory stores instructions configured to cause the one or more processing units to: receive a data packet using the network communications interface; determine a classification of the data packet based, at least in part, on a plurality of factors, wherein the plurality of factors comprises a rate at which the data packet was received and a time at which the data packet was received; select, based at least in part, on the classification, an operation from a plurality of operations, wherein the plurality of operations comprises a cut-through operation and a store-and-forward operation; and perform the selected operation.

The invention provides a message classification method. A decision-making unit comprises a TCAM (Ternary Content Addressable Memory), a plurality of boundary value memories cascaded behind the TCAM, and a rear rule memory connected to the last level of boundary value memory, a bit value group is stored in the TCAM, the bit value group corresponds to a bit decision of a decision tree of a rule, a boundary value is stored in the boundary value memory, the boundary value corresponds to a range decision or a bit decision of the decision tree, and the rule is stored in the rule memory; the method comprises the steps of extracting a target key value from a target message and inputting the target key value into a decision-making unit; searching a bit value group matched with the target key value in a TCAM (Ternary Content Addressable Memory), and determining a first-level address index; acquiring a boundary value from each level of boundary value memory according to the address index of the corresponding level, comparing the boundary value with a target key value, and determining the address index of the next level according to a comparison result; and acquiring the rule from the rule memory according to the last-level address index. The invention also provides a message classification device.

Interval binary tree definitions and binary tree definitions can be stored in the memory of a networking device. The interval binary trees can map IP address ranges and port ranges to class identifiers. A networking device receives an IP packet that has a layer 3 header that includes an IP address and a port number. The networking device can use the IP address, the port number, and the interval binary trees to determine a first class identifier and a second class identifier. The first class identifier can indicate a binary tree definition that is searched for the second class identifier. The search identifies yet another class identifier that the networking device uses to determine a networking rule to apply to the IP packet. This technique uses far less memory than the RFC algorithm commonly used to determine a networking rule to apply to the IP packet.

This invention discloses a packet classification processing system based on the joint compilation of multi-mode DFA automata, comprising: a feature extraction module for extracting the state transition path features of each independent DFA automaton participating in the joint compilation and the features of the network packets to be classified; an integrated compilation core module that integrates a quantum hash processing unit and a biological sequence alignment processing unit to achieve collaborative compilation of path optimization and index construction; and a global homogeneous path sharing pool for storing path-related data output by the integrated compilation core module, enabling the reuse of homogeneous path segments among multiple DFAs. This invention, through the collaborative work of quantum hash processing and biological sequence alignment, accurately identifies and reuses homogeneous path segments in multi-mode DFAs, avoiding the repeated storage and computation of paths caused by traditional independent compilation, significantly reducing the overall redundancy of the state machine, improving storage and computation efficiency, and enhancing matching accuracy and reliability.

The invention discloses a data packet information transmission method, a data packet information determination method, devices and communication equipment, and belongs to the technical field of communication, the data packet information transmission method comprises the steps that first equipment executes first operation, and the first operation comprises at least one of the following items: sending first information to a terminal; sending second information to a second device; wherein the first information is used for at least one of the following items: identifying a data packet; classifying the data packets; matching the data packet; mapping the data packet to a quality of service (QoS) flow; the second information is used for at least one of the following items: identifying a data packet; classifying the data packets; matching the data packet; the data packets are mapped to the QoS flow.

A method for controlling packet transmission at a PTN access node for an ITS communication network and an apparatus for the same are disclosed. A packet transmission control method according to an embodiment of the present invention may include: a step of classifying into a plurality of service classes including control traffic and video traffic based on the header and service identifier of a received frame; a step of receiving traffic event metadata including signal cycles, conflicting traffic events, and priority signal events from a control policy server; a step of generating scheduling parameters including time slot allocation parameters for a control traffic queue and weight adjustment parameters for a video traffic queue based on the metadata; a step of calculating a microburst indicator based on frame inflow characteristics in a short-time observation window, and determining the output order by performing queue management and scheduling control for a queue by service class according to the scheduling parameters and the microburst indicator; a step of transmitting by applying a predetermined transmission encapsulation according to a service identifier; and a step of maintaining an independent protection domain for each service and performing linear or ring protection switching only for the corresponding service when a threshold is exceeded based on an OAM performance indicator for each service.

Network devices, systems, and methods are provided. In one example, a network device includes one or more packet classification circuits and one or more hash selection circuits that cooperate with the one or more packet classification circuits to provide the one or more packet classification circuits with a hash table selection order. The hash table selection order may be determined for a packet to be classified with the support of machine learning by the one or more packet classification circuits based on information contained in the packet.

Systems, methods, and computer-readable storage media for packet classification, and more specifically to cloud-driven traffic classification. A system can receive, at a packet identifier, a packet comprising a packet header and packet data, and generate a Universally Unique Identifier (UUID) based on the packet header. The system can then transmit the UUID from the packet identifier to a UUID cloud database and receive, at the packet identifier from the UUID cloud database, packet management instructions. The system can then provide the packet and the packet management instructions to a router.

A network device, system-on-a-chip, and method of performing packet handling are described. A packet is received, and a lookup based on one or more packet header fields of the packet is performed using a lookup generator action handler. An artificial intelligence engine processes packet header data associated with the packet, and a smart indication is generated. A forwarding decision is made for the packet based on the lookup performed by the lookup generator action handler as well as based on the smart indication generated with the artificial intelligence engine.

A wireless IEEE 802.11 queuing architecture supporting Low Latency Low Loss Scalable throughput (L4S) and Dual Queue Active Queue Management (AQM) in which queues for both L4S streams and classic streams are contained in the medium access control (MAC) layer, and one or more of these queues are configured with more than one internal queue, to which different L4S packets and other packet types are retained in different internal queues within the MAC transmit queues. The MAC queues are configured for MAC layer buffering of L4S packets and classical packets in separate queues and / or queues having internal queues for buffering different packet types, classifications, latency sensitivity, QoS considerations, and so forth. The architecture also allows for multiple packet queues in the upper layers above the MAC layer.

The present application relates to a kind of online packet classification method based on rule prefix space, first initialization rule grouping mapping table and rule split mapping table, respectively for recording rule grouping that rule is assigned to, whether the split of a rule occurs.Record addition and deletion rule, carry out packet classification such as operation can be carried out after the initialization of two mapping tables, when adding rule, scale to rule prefix space, it is added to suitable rule grouping;When deleting rule, it is realized fast processing by the record of two mapping tables.The present application has the advantages that rule prefix space is scaled, and the number of rule grouping is reduced;When selecting rule grouping, optimization is carried out based on priority, so that high priority rule is mainly concentrated in the front rule grouping, while guaranteeing rule update performance, the packet matching rate is improved.

A system and method for quality of experience (QoE)-aware transmission over multi-transport is disclosed. The system receives requests for transmitting data packets from source node to destination node in wireless communication network. Further, the system determines payload data of the data packet and n-tuple information associated with the data packet. Furthermore, the system analyzes packet level metrics associated with determined payload data of data packet. Additionally, system classifies data packets into a latency class (LC) and a Quality of Service (QoS) class based on the analyzed packet level metrics. Further, the system determines connection identifier (ID) associated with data packet. Further, the system determines appropriate multi-transport access network (MTAN) among plurality of MTANs for transmitting data packet to destination node. Furthermore, the system establishes multi-path (MP) backbone connection with destination node using determined appropriate MTAN. Additionally, the system transmits data packet to destination node through established MP backbone connection.