20 results about "Programmable networking" patented technology

Methods, apparatus, and systems for adaptive collaborative memory with the assistance of programmable networking devices. Under one example, the programmable networking device is a switch that is deployed in a system or cluster of servers comprising a plurality of nodes. The switch selects one or more nodes to be remote memory server nodes and allocate one or more portions of memory on those nodes to be used as remote memory for one or more remote memory client nodes. The switch receives memory access request messages originating from remote memory client nodes containing indicia identifying memory to be accessed, determines which remote memory server node is to be used for servicing a given memory access request, and sends a memory access request message containing indicia identifying memory to be accessed to the remote memory server node that is determined. The switch also facilitates return of messages containing remote memory access responses to the client nodes.

A system and method for performing rolling updates of distributed applications in a software-defined network environment. An application manager coordinates deployment of updated versions of fxDeviceApp and fxCloudApp components to isolated execution environments on distinct network elements, such as edge devices and cloud-based containers or virtual machines. During the update process, the system establishes secure communication tunnels between the updated components using a virtual messaging fabric, verifies the integrity of the updated components before activation, and maintains service continuity by activating the new versions only after successful validation. The original application instances are decommissioned after the updated components are fully operational. The system supports dynamic scaling of execution environments based on load conditions, policy-governed update concurrency and ordering, coordinated deployment across multiple zones, automatic rollback on failure, and audit logging of deployment events. These mechanisms enable secure, resilient, and minimally disruptive application lifecycle management in distributed and programmable networking environments.

The invention discloses a virtual-real combined sky-ground multi-domain heterogeneous network cooperative computing simulation system and a virtual-real combined sky-ground multi-domain heterogeneous network cooperative computing simulation method. The system comprises a heterogeneous computing power prototype subsystem, a virtual simulation subsystem, a satellite-borne general computing terminal, a programmable network simulator, a heterogeneous resource management subsystem and a simulation verification system interface. Real hardware computing power characteristics are introduced through a physical board card, large-scale expansion is realized through virtual nodes, and authenticity and large-scale performance of simulation are considered; link parameters are generated according to a high-precision orbit dynamics model, and the fidelity of sky-ground network simulation is greatly improved; based on a mixed container arrangement technology, unified management and intelligent scheduling of sky, air and ground heterogeneous resources are realized, and a powerful platform is provided for verifying an advanced cross-domain collaborative algorithm; one set of system can support various simulation verification requirements of networking routing, task unloading, distributed cooperative computing, constellation cluster management and control and the like, and the research and development cost and complexity are reduced.

An apparatus includes a host interface, a network interface, and a programmable circuitry communicably coupled to the host interface and the network interface. The programmable circuitry can include one or more processors to implement network interface functionality, and a discrete trusted platform module (dTPM) to enable the one or more processors to establish a secure boot mechanism for the apparatus, wherein the one or more processors are to instantiate a virtual TPM (vTPM) manager that is associated with the dTPM, the vTPM manager to host vTPM instances corresponding to one or more virtualized environments hosted on at least one of the programmable circuitry or a host device communicable coupled to the apparatus.

The application provides an online dynamic programming method, system and storage medium of a programmable network device, comprising: a control terminal calling a network service function definition to generate a network service instruction sequence; based on the network service instruction sequence and a self-defined protocol structure, a self-defined protocol header is constructed and inserted into an IP data packet, and a type field of the IP data packet is marked with a mark value that the current data packet belongs to a normal data packet or contains network service instructions, and the IP data packet is sent to the programmable network device; wherein the self-defined protocol structure comprises a protocol type, a number of instructions and an instruction sequence; the programmable network device receives the IP data packet, when the mark value in the IP data packet indicates that the current data packet contains network service instructions, the self-defined protocol header is parsed, the network service instruction sequence is executed and removed one by one, and the network service of the programmable network device is dynamically adjusted, otherwise the IP data packet is directly forwarded. The application can solve the problem that the existing programmable network technology cannot simultaneously meet high performance and online programming flexibility.

A system and method for performing load balancing in an In-Network Aggregation (INA) application is provided. A network server partitions data to be aggregated into data parts and sends the data parts in first packets to programmable network switches. Each programmable network switch receives a plurality of first packets, aggregates the first data parts to generate an aggregated data part, and sends the aggregated data part in a second packet to an aggregation network server. The aggregation network server receives a plurality of second packets and generates aggregated data from the aggregated data parts. Routing headers of the first packets may include the programmable network switch address as an intermediate waypoint and the aggregation network server address as a destination address. The routing headers may include a second programmable network switch address as a second intermediate waypoint. The data to be aggregated may be value vectors or key-value pairs.

The application discloses an abnormality detection positioning method and system based on a programmable network and a medium, and belongs to the technical field of data processing. The method comprises the following steps: S1, adding INT header information at an entry node, and passing a first data packet through an INT source switch to obtain a second data packet by adding an INT header label and a metadata field to the first data packet; S2, if an intermediate node is abnormal, adding abnormality information to the second data packet to obtain a third data packet and outputting the third data packet to a next-hop switch; S3, when a final data packet reaches a last-hop switch, using a Bloom filter to determine whether the final data packet needs to be sent to an INT server, and finally updating the Bloom filter; and S4, emptying the Bloom filter and a hash table of the switch after each detection period ends. Abnormality judgment and recording are performed on a data plane, so that the application can directly perform abnormality detection in the transmission process of a data stream, and thus the amount of data sent to the INT server is significantly reduced.

This invention discloses a distributed data plane resource optimization method and system, which fully utilizes merging and splitting algorithms to optimize data plane program resources and solve the resource limitation problem of switches in programmable networks. First, the input programs are classified. Then, a merging algorithm is used for resource-sparse programs, and a splitting algorithm is used for resource-intensive programs. The merging and splitting algorithms yield a set of subtasks, and finally, the deployment scheme of each task in the subtask set in the underlying network is obtained. Compared with existing technologies, this invention can improve the speed and effectiveness of program merging, effectively reduce program redundancy, and reduce the granularity of program placement and scheduling overhead between devices by splitting programs. It also provides a deployment scheme with higher resource utilization, demonstrating the practicality of a distributed data plane resource optimization method and system.

Programmable network devices configured to perform various packet processing functions are further configured to use IPsec to secure control and data packets associated with data sessions traversing the UPF. Field-programmable gate arrays (FPGAs) and / or graphics processing units (GPUs) coupled with network interfaces are configured to perform user plane functions and secure data packet within a compact and modular hardware unit to minimize excessive communication while maintaining control and user plane separation (CUPS).

The invention provides a digital body feature application method and system based on traffic analysis training, and relates to the technical field of data processing, and the method comprises the steps: carrying out the capturing and preprocessing of an original data package at an edge node; converting the preprocessed traffic data into feature vectors by adopting feature coding; establishing a human-equipment-behavior three-dimensional mapping relation, and generating a digital body portrait; analyzing the digital body portrait to obtain a behavior prediction result; selecting an optimal path according to a behavior prediction result, and establishing a virtual channel through a tunnel encapsulation method; and monitoring the network flow, outputting an attack classification result, calculating a flow deviation degree, outputting a threat level and generating a corresponding defense strategy when the flow deviation degree exceeds a preset threshold value, and updating a flow table through programmable network equipment to realize attack defense. The technical problems that in the prior art, network resource configuration lacks behavior perception ability, and a service channel cannot be dynamically generated and precise safety protection cannot be implemented according to a user behavior mode can be solved.

The invention discloses a cloud software adaptation method and device, electronic equipment and a storage medium, and relates to the technical field of cloud networks, and the method constructs a cloud software module of a network chip switch. The network chip switch comprises a universal chip and a programmable network chip. And detecting the coupling relationship between the cloud software module and the programmable network chip, and determining the cloud software module as a first module and a second module according to the coupling relationship. And executing specific adaptation on the first module to obtain a third module, and generating cloud software according to the second module and the third module. According to the technical scheme, only the first module which is strongly coupled with the programmable chip needs to be subjected to specific adaptation, cloud software does not need to be fully modified, and the adaptation development amount can be reduced; the second module can be reused across chips, and repeated development is avoided. The cloud software is generated by combining the two methods, different programmable chips can be adapted, smooth switching of the cloud software on different hardware is achieved, and then the development efficiency and the hardware adaptation flexibility are improved.

The invention relates to a programmable network resource and heterogeneous computing power adaptive scheduling method based on reinforcement learning. The method comprises the steps of obtaining a network and computing power state data set, processing a network topology structure through GNN to generate an observation space of reinforcement learning, adopting a reinforcement learning method to generate an optimal scheduling strategy, and adjusting a data flow path and computing power distribution. The invention relates to a programmable network resource and heterogeneous computing power adaptive scheduling device based on reinforcement learning. The programmable network resource and heterogeneous computing power adaptive scheduling device comprises an acquisition module, a first generation module, a second generation module and an adjustment module. The invention further relates to electronic equipment and a storage medium. The invention designs a programmable network resource and heterogeneous computing power adaptive scheduling method and device based on reinforcement learning, electronic equipment and a storage medium. The problems of lack of joint optimization, difficulty in coping with dynamic topology and burst load, difficulty in balancing target conflicts and inconsistency of data aperture and time sequence caused by splitting of a network side and a calculation side in a traditional scheme can be solved.

Systems and methods for determining primary and failover paths in a programmable communication network are disclosed herein. In one embodiment, a system to identify a plurality of communication paths may operate in conjunction with a programmable communication network connecting a source and a destination. A path discovery subsystem may discover both a first and a second completed communication path between the source and the destination. A cost calculation subsystem may calculate a first cost for the first completed communication path and a second cost for the second completed communication path. A routing subsystem may identify a primary communication path based on the first cost and the second cost, and program the plurality of nodes to implement the primary communication path.

A computer implemented method is provided for streaming media from a media server to a client web application running in a client web engine. The method involves, by the client web application, initiating a programmable network proxy in the client web engine. The method further comprises, by the programmable network proxy, intercepting a request from the client web application to retrieve the streaming media from the media server and / or intercepting a response comprising the streaming media from the media server. The method further includes, by the programmable network proxy, performing at least one of: i) injecting metadata into the intercepted request; ii) extracting metadata from the intercepted request; iii) injecting metadata into the intercepted response; and iv) extracting metadata from the intercepted response; and respectively forwarding the intercepted request to the media server and / or forwarding the intercepted response to the client web application.

The application relates to an in-network neural network deployment method based on an SDN mode, which maps input features and output results of a deep neural network model into flow table entries of network equipment, realizes deep neural network reasoning through table entry matching, and further realizes network functions such as traffic classification and anomaly detection. The application realizes efficient network data plane reasoning by compressing and converting the deep neural network model into a table entry matching task suitable for programmable network equipment. The application optimizes the utilization of storage and computing resources, significantly reduces the computing complexity of the network equipment, and improves the throughput and real-time performance. Through the innovative table entry compression and adaptive matching mechanism, the application supports high-precision applications such as traffic classification and anomaly detection, and significantly improves the intelligent management and optimization capability of the network. The application can realize efficient deployment of deep neural networks in in-network equipment, and provides an effective solution for the development of intelligent network technology.

The invention provides a network flow confusion method and system, and relates to the technical field of network security, and the method comprises the steps: responding to a received attack detection trigger signal, triggering and generating a confusion parameter, which comprises the steps: employing an IPv6 flow label permutation matrix generated by a quantum random number generator and an MPLS label stack containing multiple layers of random labels, the encryption seed key is generated based on QKD negotiation; writing the confusion parameters into a matching-action table of the programmable network equipment; when the target data packet enters a matching-action pipeline of the programmable network equipment, performing an obfuscation operation based on the obfuscation parameter, the obfuscation operation comprising: rewriting a flow label field of the target data packet by using an IPv6 flow label permutation matrix; performing bitwise exclusive-or operation on the load of the target data packet by using the encrypted seed key; and performing path encapsulation processing on the target data packet by using the MPLS label stack. According to the invention, network traffic protection is realized.

PCI Express (PCIE) is an IO interconnect standard that is developed and implemented as a tree network within Computers and servers for connecting to peripheral devices. Currently PCIE has achieved stability such that PCIE can be used as a basis for other applications. A PCIE based scheme inter-connecting multiple PCIE enabled processing systems as a cluster with at least one PCIE root complex controlling at least a PCIE bus, enabling the scalability of PCIE architecture to be applied for data transport between the connected system. The interconnection uses an outbound port enabled for system interconnection on the PCIE bus of each PCIE enabled computer connecting to one inbound port on an independently programmable network switch having a plurality of inbound ports. The interconnection is using PCIE protocol for data transfer within the cluster to interconnect processors, memory controllers, storage and other network components in Data centers.

The techniques described herein address the challenges encountered when using host-executed software to manage vector databases by providing vector database accelerator and shard management offload logic implemented within hardware and software running on device processors and programmable data layers of a programmable network interface device. In one embodiment, a programmable network interface device includes an infrastructure management circuitry designed to enable data access for a neural network inference engine with a distributed data model through dynamic management of a node associated with the neural network inference engine, where the node contains a database shard of a vector database.

Methods and systems for programmable network API monetization are described herein. A network-as-a-service (NaaS) function may receive, from the application running on a computing device associated with a customer of a wireless service provider, a request for a network resource, the request including an application ID, a device ID, and a time period for using the network resource. The NaaS may authenticate the application ID and the device ID. Upon authenticating the application ID and the device ID being successful, the NaaS may grant the network resource to the application for the time period. Further, the NaaS may generate, based on granting the network resource to the application for the time period, charging data directed to the customer. In implementations, the NaaS may generate the charging data based at least in part on a number of API calls from the application.