CN113242302A - Data access request processing method and device, computer equipment and medium - Google Patents
Data access request processing method and device, computer equipment and medium Download PDFInfo
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L67/00—Network arrangements or protocols for supporting network services or applications
- H04L67/01—Protocols
- H04L67/10—Protocols in which an application is distributed across nodes in the network
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L41/00—Arrangements for maintenance, administration or management of data switching networks, e.g. of packet switching networks
- H04L41/08—Configuration management of networks or network elements
- H04L41/0803—Configuration setting
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L43/00—Arrangements for monitoring or testing data switching networks
- H04L43/10—Active monitoring, e.g. heartbeat, ping or trace-route
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L67/00—Network arrangements or protocols for supporting network services or applications
- H04L67/01—Protocols
- H04L67/10—Protocols in which an application is distributed across nodes in the network
- H04L67/1001—Protocols in which an application is distributed across nodes in the network for accessing one among a plurality of replicated servers
Abstract
The invention discloses a method and a device for processing a data access request, computer equipment and a storage medium, wherein the method comprises the following steps: when a data access request sent by a client is received, nodes with activated states in a cluster are used as effective nodes, performance data of the effective nodes are collected, performance scores of the effective nodes are calculated based on the collected performance data, a target node is determined based on the performance score of each effective node, the data access request is distributed to the target node for data processing, target node selection and distribution processing of the data access request are achieved, and processing efficiency of the data access request is improved.
Description
Technical Field
The present invention relates to the field of data processing, and in particular, to a method and an apparatus for processing a data access request, a computer device, and a medium.
Background
With the rapid development of computer technology, networks are an indispensable part in daily life, enterprise units issue various information through networks, users access the information to obtain useful information for themselves, and for information issuers, load pressure of servers is increasing with the increase of user access flow.
Disclosure of Invention
The embodiment of the invention provides a method and a device for processing a data access request, computer equipment and a storage medium, which are used for improving the processing efficiency of the data access request.
In order to solve the foregoing technical problem, an embodiment of the present application provides a method for processing a data access request, including:
when a data access request sent by a client is received, taking a node with an activated state in a cluster as an effective node, and collecting performance data of the effective node;
calculating the performance score of the effective node based on the collected performance data;
determining a target node based on the performance score of each effective node;
and distributing the data access request to the target node for data processing.
Optionally, the performance data includes a central processor model, a memory model, a current usage rate of the central processor, and a current usage rate of the memory.
Optionally, the calculating the performance score of the valid node based on the collected performance data includes:
calculating the performance score S of the effective node by adopting the following formula:
wherein, I1Is the central processor model, I of the node2Is the memory model number, P, of the node1Is the current utilization rate, P, of the central processing unit of the node2Is the current utilization rate of the node memory, J1Is the central processor model I1Corresponding preset weight, J2Is the memory model I2And (4) corresponding preset weight.
Optionally, the determining a target node based on the performance score of each valid node includes:
if the data volume contained in the data access request does not exceed a preset threshold value, acquiring an effective node with the highest performance score as the target node;
and if the data volume contained in the data access request exceeds a preset threshold, dynamically determining the number M of target nodes according to the data volume contained in the data access request, and selecting M effective nodes as the target nodes according to the sequence from high to low of the performance score, wherein M is a positive integer greater than 1.
Optionally, after the M effective nodes are selected in the order from high to low according to the performance score and serve as the target node, the method for processing the data access request further includes:
slicing the data contained in the data access request to obtain M pieces of sliced data;
and distributing each piece of fragment data to 1 target node for processing so that each target node processes 1 piece of fragment data in parallel.
In order to solve the foregoing technical problem, an embodiment of the present application further provides a data access request processing apparatus, including:
the node state determining module is used for taking the node with the activated state in the cluster as an effective node when receiving a data access request sent by a client and collecting performance data of the effective node;
the performance score calculation module is used for calculating the performance score of the effective node based on the collected performance data;
the target node determining module is used for determining a target node based on the performance score of each effective node;
and the data distribution processing module is used for distributing the data access request to the target node for data processing.
Optionally, the performance score calculating module includes:
a node score calculating unit, configured to calculate a performance score S of the valid node by using the following formula:
wherein, I1Is the central processor model, I of the node2Is the memory model number, P, of the node1Is the current utilization rate, P, of the central processing unit of the node2Is the current utilization rate of the node memory, J1Is the central processor model I1Corresponding preset weight, J2Is the memory model I2And (4) corresponding preset weight.
Optionally, the target node determining module includes:
the first node determining unit is used for acquiring an effective node with the highest performance score as the target node if the data volume contained in the data access request does not exceed a preset threshold;
and a second node determining unit, configured to dynamically determine, according to the data volume included in the data access request, a target node number M if the data volume included in the data access request exceeds a preset threshold, and select M effective nodes as the target nodes in an order from high to low according to the performance score, where M is a positive integer greater than 1.
Optionally, the apparatus for processing the data access request further includes:
the data slicing module is used for slicing the data contained in the data access request to obtain M sliced data;
and the parallel processing module is used for distributing each piece of fragment data to 1 target node for processing so as to enable each target node to process 1 piece of fragment data in parallel.
In order to solve the above technical problem, an embodiment of the present application further provides a computer device, which includes a memory, a processor, and a computer program stored in the memory and executable on the processor, where the processor implements the steps of the method for processing the data access request when executing the computer program.
In order to solve the above technical problem, an embodiment of the present application further provides a computer-readable storage medium, where a computer program is stored, and the computer program, when executed by a processor, implements the steps of the above data access request processing method.
According to the data access request processing method, the data access request processing device, the computer equipment and the storage medium, when a data access request sent by a client is received, nodes with activated states in a cluster are used as effective nodes, performance data are collected for each effective node, performance scores of the effective nodes are calculated based on the collected performance data, a target node is determined based on the performance score of each effective node, the data access request is distributed to the target node for data processing, the data access request is selected and quickly distributed and responded, and the data access request processing efficiency is improved.
Drawings
In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings needed to be used in the description of the embodiments of the present invention will be briefly introduced below, and it is obvious that the drawings in the following description are only some embodiments of the present invention, and it is obvious for those skilled in the art that other drawings can be obtained according to these drawings without inventive labor.
FIG. 1 is a schematic diagram of an application environment of the present application;
FIG. 2 is a flow diagram of one embodiment of a method of processing a data access request of the present application;
FIG. 3 is a block diagram illustrating one embodiment of a device for processing a data access request according to the present application;
FIG. 4 is a schematic block diagram of one embodiment of a computer device according to the present application.
Detailed Description
Unless defined otherwise, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this application belongs; the terminology used in the description of the application herein is for the purpose of describing particular embodiments only and is not intended to be limiting of the application; the terms "including" and "having," and any variations thereof, in the description and claims of this application and the description of the above figures are intended to cover non-exclusive inclusions. The terms "first," "second," and the like in the description and claims of this application or in the above-described drawings are used for distinguishing between different objects and not for describing a particular order.
Reference herein to "an embodiment" means that a particular feature, structure, or characteristic described in connection with the embodiment can be included in at least one embodiment of the application. The appearances of the phrase in various places in the specification are not necessarily all referring to the same embodiment, nor are separate or alternative embodiments mutually exclusive of other embodiments. It is explicitly and implicitly understood by one skilled in the art that the embodiments described herein can be combined with other embodiments.
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are some, not all, embodiments of the present invention. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
Referring to fig. 1, fig. 1 is a schematic diagram of an application environment for processing a data access request according to this embodiment, in fig. 1(a), a global load balancing device is deployed outside a data center and supports a single machine or redundancy, and in fig. 1(b), the global load balancing device is deployed inside each data center (supports a single machine or redundancy in each center) to form a cluster and provide DNS service to outside uniformly.
All global load balancing will automatically synchronize configuration and performance data. When the servers of any data center are in balance downtime, the whole DNS server is not influenced.
Referring to fig. 2, fig. 2 shows a method for processing a data access request according to an embodiment of the present invention, which is detailed as follows:
s201: and when a data access request sent by a client is received, taking the node with the activated state in the cluster as an effective node, and collecting performance data of the effective node.
Specifically, when a data access request sent by a client is received, activity detection is carried out on each node in the cluster so as to determine the node state.
It should be noted that there are multiple nodes (node servers) in the cluster, and due to some control policies and performance factors of the nodes themselves, the nodes may be dynamically brought online and offline, so that to ensure the effectiveness of subsequent data access request distribution and processing, the state of the nodes needs to be determined first.
The node states include activated, down and not activated.
S202: and calculating the performance score of the effective node based on the collected performance data.
Optionally, the performance data includes a central processor model, a memory model, a current central processor usage rate, and a current memory usage rate.
Specifically, different node servers have different data processing capabilities due to different configurations and different current operating states, and in order to avoid a server failure caused by overload operation of the node servers or an abnormality in a data processing process, a resource state, that is, a performance score, currently available for data processing by the node servers is calculated according to the current operating state of the node servers.
Further, calculating the performance score of the active node based on the collected performance data comprises:
calculating the performance score S of the effective node by adopting the following formula:
wherein, I1Being the centre of a nodeProcessor model, I2Is the memory model, P, of the node1Is the current utilization rate, P, of the central processing unit of the node2Is the current utilization rate of the node memory, J1Is the central processing unit type I1Corresponding preset weight, J2Is the memory model I2And (4) corresponding preset weight.
S203: and determining the target node based on the performance score of each effective node.
The selection manner of the specific target node may refer to the description of the subsequent embodiments, and is not described herein again to avoid repetition.
S204: and distributing the data access request to the target node for data processing.
In this embodiment, when a data access request sent by a client is received, activity detection is performed on each node in a cluster communication manner to obtain a node state, the node state is an activated node and serves as an effective node, performance data is acquired for each effective node, performance scores of the effective nodes are calculated based on the acquired performance data, a target node is determined based on the performance scores of each effective node, the data access request is distributed to the target node for data processing, quick distribution response of the data access request is achieved, and processing efficiency of the data access request is improved.
In a specific optional implementation manner, before a node in a cluster whose state is active is taken as an active node when a data access request sent by a client is received, the method further includes performing activity detection on each node in the cluster in a cluster communication manner to obtain a node state, where the specific implementation process is as follows:
sending a heartbeat packet detection instruction to each node based on cluster communication;
and determining the node state corresponding to each node according to the feedback result of each node aiming at the heartbeat packet detection instruction.
Specifically, whether the link state of the network connection port of the node corresponding to the heartbeat packet is normal is judged by sending a heartbeat packet detection instruction to each node, and when the link state is normal, the node interactively responds with the server according to the heartbeat packet detection instruction.
It should be understood that an anomaly can be timely discovered through heartbeat monitoring, for example, if no feedback of the node server to the heartbeat packet is received within a period of time, it is determined that the link state of the node is abnormal, at this time, the node is removed from the list of the valid nodes, the subsequent data access request is prevented from being distributed to the node, and meanwhile, the abnormal condition is timely displayed on an interactive interface of the server, so that a maintainer can timely analyze and process the related anomaly problem appearing on the corresponding cluster node.
The heartbeat packet is a self-defined command word which is used for regularly informing the self state of the opposite side between the target host and the server, is sent according to a certain time interval, is similar to a heartbeat, and is called as a heartbeat packet. The heartbeat package is used for monitoring the availability of the SOCKET and ensuring the stability of interaction between the server and the target host.
In this embodiment, through the mode that the heartbeat detected, the state of every node is judged fast, selects effective node, promotes the efficiency of effective node screening.
In a specific optional embodiment, in step S203, determining the target node based on the performance score of each valid node includes:
if the data volume contained in the data access request does not exceed a preset threshold value, acquiring an effective node with the highest performance score as a target node;
and if the data volume contained in the data access request exceeds a preset threshold, dynamically determining the number M of target nodes according to the data volume contained in the data access request, and selecting M effective nodes as the target nodes according to the sequence of performance scores from high to low, wherein M is a positive integer greater than 1.
Specifically, the dynamic determination of the number of target nodes may be performed through a preset condition, where the preset condition is set according to an actual requirement, for example, the number M of target nodes is determined according to a ratio of a value exceeding a preset threshold to the preset threshold.
In a specific optional implementation manner, after selecting M valid nodes in an order from high to low according to the performance scores, as target nodes, the method for processing the data access request further includes:
slicing the data contained in the data access request to obtain M sliced data;
and distributing each piece of sliced data to 1 target node for processing so that each target node processes 1 piece of sliced data in parallel.
The dimension of the segment may be set according to actual requirements, for example, the dimension may be set to a geographic area, an administrative area, a time dimension, and the like, and a segmentation strategy such as sequential segmentation and modular segmentation may also be adopted, which is not specifically limited herein.
In the embodiment, concurrent processing is realized by means of data fragmentation, which is beneficial to improving the processing efficiency of the access request.
It should be understood that, the sequence numbers of the steps in the foregoing embodiments do not imply an execution sequence, and the execution sequence of each process should be determined by its function and inherent logic, and should not constitute any limitation to the implementation process of the embodiments of the present invention.
Fig. 3 shows a schematic block diagram of a data access request processing device in one-to-one correspondence with the processing methods of the data access requests of the above-described embodiments. As shown in fig. 3, the data access request processing device includes a node state determination module 31, a performance score calculation module 32, a target node determination module 33, and a data distribution processing module 34. The functional modules are explained in detail as follows:
the node state determining module 31 is configured to, when receiving a data access request sent by a client, use a node in a cluster whose state is activated as an effective node, and acquire performance data of the effective node;
a performance score calculation module 32, configured to calculate a performance score of the valid node based on the collected performance data;
a target node determining module 33, configured to determine a target node based on the performance score of each valid node;
and the data distribution processing module 34 is configured to distribute the data access request to the target node for data processing.
Optionally, the performance score calculation module 32 includes:
a node score calculating unit, configured to calculate a performance score S of the valid node by using the following formula:
wherein, I1Central processor model, I, as a node2Is the memory model, P, of the node1Is the current utilization rate, P, of the central processing unit of the node2Is the current utilization rate of the node memory, J1Is the central processing unit type I1Corresponding preset weight, J2Is the memory model I2And (4) corresponding preset weight.
Optionally, the target node determining module 33 includes:
the first node determining unit is used for acquiring an effective node with the highest performance score as a target node if the data volume contained in the data access request does not exceed a preset threshold;
and the second node determining unit is used for dynamically determining the number M of target nodes according to the data volume contained in the data access request when the data volume contained in the data access request exceeds a preset threshold value, and selecting M effective nodes as the target nodes according to the sequence of the performance scores from high to low, wherein M is a positive integer greater than 1.
Optionally, the apparatus for processing a data access request further includes:
the data slicing module is used for slicing the data contained in the data access request to obtain M sliced data;
and the parallel processing module is used for distributing each piece of fragment data to 1 target node for processing so as to enable each target node to process 1 piece of fragment data in parallel.
The specific definition of the processing device for the data access request may refer to the above definition of the processing method for the data access request, and is not described herein again. The respective modules in the data access request processing apparatus described above may be implemented wholly or partially by software, hardware, and a combination thereof. The modules can be embedded in a hardware form or independent from a processor in the computer device, and can also be stored in a memory in the computer device in a software form, so that the processor can call and execute operations corresponding to the modules.
In order to solve the technical problem, an embodiment of the present application further provides a computer device. Referring to fig. 4, fig. 4 is a block diagram of a basic structure of a computer device according to the present embodiment.
The computer device 4 comprises a memory 41, a processor 42, a network interface 43 communicatively connected to each other via a system bus. It is noted that only the computer device 4 having the components connection memory 41, processor 42, network interface 43 is shown, but it is understood that not all of the shown components are required to be implemented, and that more or fewer components may be implemented instead. As will be understood by those skilled in the art, the computer device is a device capable of automatically performing numerical calculation and/or information processing according to a preset or stored instruction, and the hardware includes, but is not limited to, a microprocessor, an Application Specific Integrated Circuit (ASIC), a Programmable Gate Array (FPGA), a Digital Signal Processor (DSP), an embedded device, and the like.
The computer device can be a desktop computer, a notebook, a palm computer, a cloud server and other computing devices. The computer equipment can carry out man-machine interaction with a user through a keyboard, a mouse, a remote controller, a touch panel or voice control equipment and the like.
The memory 41 includes at least one type of readable storage medium including a flash memory, a hard disk, a multimedia card, a card-type memory (e.g., SD or D interface display memory, etc.), a Random Access Memory (RAM), a Static Random Access Memory (SRAM), a Read Only Memory (ROM), an Electrically Erasable Programmable Read Only Memory (EEPROM), a Programmable Read Only Memory (PROM), a magnetic memory, a magnetic disk, an optical disk, etc. In some embodiments, the memory 41 may be an internal storage unit of the computer device 4, such as a hard disk or a memory of the computer device 4. In other embodiments, the memory 41 may also be an external storage device of the computer device 4, such as a plug-in hard disk, a Smart Media Card (SMC), a Secure Digital (SD) Card, a Flash memory Card (Flash Card), and the like, which are provided on the computer device 4. Of course, the memory 41 may also include both internal and external storage devices of the computer device 4. In this embodiment, the memory 41 is generally used for storing an operating system installed in the computer device 4 and various types of application software, such as program codes for controlling electronic files. Further, the memory 41 may also be used to temporarily store various types of data that have been output or are to be output.
The processor 42 may be a Central Processing Unit (CPU), controller, microcontroller, microprocessor, or other data Processing chip in some embodiments. The processor 42 is typically used to control the overall operation of the computer device 4. In this embodiment, the processor 42 is configured to execute the program code stored in the memory 41 or process data, for example, execute the program code for data access.
The network interface 43 may comprise a wireless network interface or a wired network interface, and the network interface 43 is generally used for establishing communication connection between the computer device 4 and other electronic devices.
The present application provides yet another embodiment, which provides a computer-readable storage medium storing a data access program, the data access program being executable by at least one processor to cause the at least one processor to perform the steps of the method of processing a data access request as described above.
Through the above description of the embodiments, those skilled in the art will clearly understand that the method of the above embodiments can be implemented by software plus a necessary general hardware platform, and certainly can also be implemented by hardware, but in many cases, the former is a better implementation manner. Based on such understanding, the technical solutions of the present application may be embodied in the form of a software product, which is stored in a storage medium (such as ROM/RAM, magnetic disk, optical disk) and includes instructions for enabling a terminal device (such as a mobile phone, a computer, a server, an air conditioner, or a network device) to execute the method according to the embodiments of the present application.
Through the above description of the embodiments, those skilled in the art will clearly understand that the method of the above embodiments can be implemented by software plus a necessary general hardware platform, and certainly can also be implemented by hardware, but in many cases, the former is a better implementation manner. Based on such understanding, the technical solutions of the present application may be embodied in the form of a software product, which is stored in a storage medium (such as ROM/RAM, magnetic disk, optical disk) and includes instructions for enabling a terminal device (such as a mobile phone, a computer, a server, an air conditioner, or a network device) to execute the method according to the embodiments of the present application.
Through the above description of the embodiments, those skilled in the art will clearly understand that the method of the above embodiments can be implemented by software plus a necessary general hardware platform, and certainly can also be implemented by hardware, but in many cases, the former is a better implementation manner. Based on such understanding, the technical solutions of the present application may be embodied in the form of a software product, which is stored in a storage medium (such as ROM/RAM, magnetic disk, optical disk) and includes instructions for enabling a terminal device (such as a mobile phone, a computer, a server, an air conditioner, or a network device) to execute the method according to the embodiments of the present application.
It is to be understood that the above-described embodiments are merely illustrative of some, but not restrictive, of the broad invention, and that the appended drawings illustrate preferred embodiments of the invention and do not limit the scope of the invention. This application is capable of embodiments in many different forms and is provided for the purpose of enabling a thorough understanding of the disclosure of the application. Although the present application has been described in detail with reference to the foregoing embodiments, it will be apparent to one skilled in the art that the present application may be practiced without modification or with equivalents of some of the features described in the foregoing embodiments. All equivalent structures made by using the contents of the specification and the drawings of the present application are directly or indirectly applied to other related technical fields and are within the protection scope of the present application.
Claims (10)
1. A processing method of a data access request is applied to a cluster server, and is characterized in that the processing method of the data access request comprises the following steps:
when a data access request sent by a client is received, taking a node with an activated state in a cluster as an effective node, and collecting performance data of the effective node;
calculating the performance score of the effective node based on the collected performance data;
determining a target node based on the performance score of each effective node;
and distributing the data access request to the target node for data processing.
2. The method of claim 1, wherein the performance data includes a central processor model, a memory model, a central processor current usage, and a memory current usage.
3. The method of processing a data access request of claim 2, wherein the calculating a performance score for the active node based on the collected performance data comprises:
calculating the performance score S of the effective node by adopting the following formula:
wherein, I1Is the central processor model, I of the node2Is the memory model number, P, of the node1Is the current utilization rate, P, of the central processing unit of the node2Is the current utilization rate of the node memory, J1Is the central processor model I1Corresponding preset weight, J2Is the memory model I2And (4) corresponding preset weight.
4. A method of processing data access requests according to any of claims 1 to 3 in which the determining a target node based on the performance score of each of the valid nodes comprises:
if the data volume contained in the data access request does not exceed a preset threshold value, acquiring an effective node with the highest performance score as the target node;
and if the data volume contained in the data access request exceeds a preset threshold, dynamically determining the number M of target nodes according to the data volume contained in the data access request, and selecting M effective nodes as the target nodes according to the sequence from high to low of the performance score, wherein M is a positive integer greater than 1.
5. The method for processing a data access request according to claim 4, wherein after said selecting M valid nodes in the order of the performance scores from high to low as the target node, the method for processing a data access request further comprises:
slicing the data contained in the data access request to obtain M pieces of sliced data;
and distributing each piece of fragment data to 1 target node for processing so that each target node processes 1 piece of fragment data in parallel.
6. A data access request processing apparatus, the data access request processing apparatus comprising:
the node state determining module is used for taking the node with the activated state in the cluster as an effective node and collecting performance data of the effective node;
the performance score calculation module is used for calculating the performance score of the effective node based on the collected performance data;
the target node determining module is used for determining a target node based on the performance score of each effective node;
and the data distribution processing module is used for distributing the data access request to the target node for data processing.
7. The apparatus for processing a data access request of claim 6, wherein said performance score calculation module comprises:
a node score calculating unit, configured to calculate a performance score S of the valid node by using the following formula:
wherein, I1Is the central processor model, I of the node2Is the memory model number, P, of the node1Is the current utilization rate, P, of the central processing unit of the node2Is the current utilization rate of the node memory, J1Is the central processor model I1Corresponding preset weight, J2Is the memory model I2And (4) corresponding preset weight.
8. The apparatus for processing a data access request of claim 6, wherein said target node determination module comprises:
the first node determining unit is used for acquiring an effective node with the highest performance score as the target node if the data volume contained in the data access request does not exceed a preset threshold;
and a second node determining unit, configured to dynamically determine, according to the data volume included in the data access request, a target node number M if the data volume included in the data access request exceeds a preset threshold, and select M effective nodes as the target nodes in an order from high to low according to the performance score, where M is a positive integer greater than 1.
9. A computer device comprising a memory, a processor and a computer program stored in the memory and executable on the processor, characterized in that the processor implements the method of processing a data access request according to any one of claims 1 to 5 when executing the computer program.
10. A computer-readable storage medium, in which a computer program is stored, which, when being executed by a processor, carries out a method of processing a data access request according to any one of claims 1 to 5.
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| CN114422511A (en) * | 2021-12-23 | 2022-04-29 | 北京八分量信息科技有限公司 | Method and device for managing data nodes in heterogeneous network and related products |
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