Abstract: A computer program product, method and mobile device, the computer program product comprising a non-transitory computer readable storage medium retaining program instructions configured to cause a processor to perform actions, wherein the processor is a processor of a mobile device of a user, wherein the mobile device is in communication with a server associated with an entity other than the user, wherein the server is in communication with a plurality of mobile devices, each of which retaining the computer program product, wherein the program instructions implement: subject to an occurrence of an event associated with the user of the mobile device, obtaining data to be transmitted to the server, wherein the event is of interest to the entity, wherein the data to be transmitted comprises demographic information of the user and a property of the event, wherein the data excludes identifying information; and transmitting the data to the server.

Abstract: 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.

Abstract: A network device includes one or more ports, and action-select circuitry. The ports are to exchange packets over a network. The act-ion-select circuitry is to determine, for a given packet, a first search key based on a first header field of the given packet, and a second search key based on a second header field of the given packet, to compare the first search key to a first group of compare values, to output a multi-element vector responsively to a match between the first search key and a first compare value, to generate a composite search key by concatenating the second search key and the multi-element vector, to compare the composite search key to a second group of compare values, and, responsively to a match between the composite search key and a second compare value, to output an action indicator for applying to the given packet.

Abstract: Pelvic implant having a frame with two arms and a sheet are disclosed. The sheet may be held under tension in the assembled implant. The implant may be planar (flat) or may be non-planar. The implant may be contoured laterally. A curved non-planar implant may be convex or concave in a rostro-caudal direction. The implants may (optionally) include two additional arms and a second sheet for supporting a urethra and/or a bladder neck. Methods for constructing and assembling the implants are disclosed. A method ultrasonically welding the frame of the implant without thermally damaging the sheet is disclosed. Methods of implantation of the implants are disclosed.

Abstract: A network device, system-on-a-chip, and method of performing packet handling are described. A packet is received, and data associated with the packet is processed, using a configurable artificial intelligence engine, to generate a size classification for a flow associated with the packet. An action is performed based, at least in part, on the size classification for the flow associated with the packet.

Abstract: In one embodiment, a communication apparatus, including a network interface configured to receive over a network a sequence of data packets of a network flow having a defined packet order, wherein the network interface is configured to receive an out-of-order data packet instead of multiple missing data packets according to the defined packet order, a timer, and packet processing circuitry configured to activate the timer responsively to receiving the out-of-order data packet, and set the time period over which the timer is activated responsively to a quantity of the multiple missing data packets.

Abstract: A classification apparatus includes a memory and a processor. The memory is configured to store rules corresponding to a corpus of rules in respective rule entries, each rule includes a respective set of unmasked bits having corresponding bit values, and at least some of the rules include masked bits. The rules in the corpus conform to respective Rule Patterns (RPs), each RP defining a respective sequence of masked and unmasked bits. The processor is configured to cluster the RPs, using a clustering criterion, into extended Rule Patterns (eRPs) associated with respective hash tables including buckets for storing rule entries. The clustering criterion aims to minimize an overall number of the eRPs while meeting a collision condition that depends on a specified maximal number of rule entries per bucket.

Abstract: A network device includes multiple ports, a Shared Buffer (SB) and a SB controller. The ports to connect to a communication network. The SB to temporarily store packets received from the communication network via the ports, the packets belonging to multiple flows. The SB controller to allocate one or more flow-specific storage regions in the SB, a given flow-specific storage region being allocated to store the packets that (i) belong to respective one or more of the flows and (ii) are to be transmitted via a respective egress queue. In response to detecting that an occupancy level in the given flow-specific storage region exceeds a specified occupancy threshold, the SB controller to report the flows in the given flow-specific storage region as congested.

Abstract: A networking device and system are described, among other things. An illustrative system is disclosed to include a shared buffer and at least a flow controller. In some embodiments, the system and/or flow controller may be configured to measure a packet flow's bandwidth consumption of the shared buffer, assign a flow-type attribute to the packet flow based on the packet flow's bandwidth consumption of the shared buffer, select a shared buffer schema for the packet flow based on the flow-type attribute assigned to the packet flow, and apply the selected shared buffer schema to the packet flow. For example, the flow-type attribute assigned to the packet flow may comprise a mice flow state or an elephant flow state, and a reserve attribute may be assigned to the flow based on the packet flow being assigned the mice flow state or the elephant flow state.

Abstract: A network element includes one or more ports and a packet processor. The one or more ports are to transmit and receive packets over a network. The packet processor is to apply a plurality of rules to the packets, each rule specifying (i) expected values for each header field of a group of header fields of the packets, including, for a given header field in the group, at least a set of multiple expected values, (ii) a group ID associated with the set, and (iii) an action to be applied to the packets whose header fields match the expected values.

Abstract: In one embodiment, a communication apparatus, including a network interface configured to receive over a network a sequence of data packets of a network flow having a defined packet order, wherein the network interface is configured to receive an out-of-order data packet instead of multiple missing data packets according to the defined packet order, a timer, and packet processing circuitry configured to activate the timer responsively to receiving the out-of-order data packet, and set the time period over which the tinier is activated responsively to a quantity of the multiple missing data packets.

Abstract: Devices, methods, and systems are provided. In one example, a method is described to include measuring a cardinality of actual data flows at a flow-processing resource, determining that the cardinality of the actual data flows triggers a congestion control action, and, in response to determining that the cardinality of the actual data flows triggers the congestion control action, implementing the congestion control action with respect to the flow-processing resource.

Abstract: 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.

Abstract: A method, apparatus and product for automatic accident detection. The method comprising: obtaining readings from a mobile device of a user carried thereby and not affixed to a vehicle in which the user is riding; determining, based on the readings obtained from the mobile device, that the user is riding in the vehicle; obtaining data from the mobile device of the user; and determining automatically, based on the data obtained from the mobile device, that the vehicle was involved in an accident.

Abstract: A parsing apparatus includes a packet-type identification circuit and a parser. The packet-type identification circuit is to receive a packet to be parsed, and to identify a packet type of the packet by extracting a packet-type identifier from a defined field in the packet. The parser is to store one or more parsing templates that specify parsing of one or more respective packet types. When the packet type of the packet corresponds to a parsing template among the stored parsing templates, the parser is to parse the packet in accordance with the stored parsing template. When the packet type of the packet does not correspond to any of the stored parsing templates, the parser is to parse the packet using an alternative parsing scheme.

Abstract: A hashing apparatus includes a memory and circuitry. The memory stores (i) multiple hash tables storing associative entries, each including at least one entry key and a respective value, the hash tables are associated with respective different hash functions, and an associative entry is accessible by applying the relevant hash function to a key matching an entry key in the associative entry, and (ii) an affinity table that stores table-selectors for selecting hash tables with which to start a key lookup. The circuitry receives a key, reads from the affinity table, by applying an affinity function to the key, a table-selector that selects a hash table, accesses in the selected hash table an associative entry by applying the hash function associated with the selected hash table to the key, and in response to detecting that the key matches an entry key in the associative entry, outputs the respective value.

Abstract: A method, apparatus and product for automatic accident detection. The method comprising: obtaining readings from a mobile device of a user carried thereby and not affixed to a vehicle in which the user is riding; determining, based on the readings obtained from the mobile device, that the user is riding in the vehicle; obtaining data from the mobile device of the user; and determining automatically, based on the data obtained from the mobile device, that the vehicle was involved in an accident.

Abstract: A computer program product, method and mobile device, the computer program product comprising a non-transitory computer readable storage medium retaining program instructions configured to cause a processor to perform actions, wherein the processor is a processor of a mobile device of a user, wherein the mobile device is in communication with a server associated with an entity other than the user, wherein the server is in communication with a plurality of mobile devices, each of which retaining the computer program product, wherein the program instructions implement: subject to an occurrence of an event associated with the user of the mobile device, obtaining data to be transmitted to the server, wherein the event is of interest to the entity, wherein the data to be transmitted comprises demographic information of the user and a property of the event, wherein the data excludes identifying information; and transmitting the data to the server.

Abstract: A network device includes one or more ports, and action-select circuitry. The ports are to exchange packets over a network. The act-ion-select circuitry is to determine, for a given packet, a first search key based on a first header field of the given packet, and a second search key based on a second header field of the given packet, to compare the first search key to a first group of compare values, to output a multi-element vector responsively to a match between the first search key and a first compare value, to generate a composite search key by concatenating the second search key and the multi-element vector, to compare the composite search key to a second group of compare values, and, responsively to a match between the composite search key and a second compare value, to output an action indicator for applying to the given packet.

Abstract: A classification apparatus includes a memory and a processor. The memory is configured to store rules corresponding to a corpus of rules in respective rule entries, each rule includes a respective set of unmasked bits having corresponding bit values, and at least some of the rules include masked bits. The rules in the corpus conform to respective Rule Patterns (RPs), each RP defining a respective sequence of masked and unmasked bits. The processor is configured to cluster the RPs, using a clustering criterion, into extended Rule Patterns (eRPs) associated with respective hash tables including buckets for storing rule entries. The clustering criterion aims to minimize an overall number of the eRPs while meeting a collision condition that depends on a specified maximal number of rule entries per bucket.