KR20160081662A - System for setting Knowledge Based Underwater Acoustic Communication Environment and Method of the Same - Google Patents

Abstract

The purpose of the present invention is to provide a system and a method to set a knowledge-based sound navigation and ranging (SONAR) communication environment capable of reconstructing a network by additionally applying the knowledge-based system to an intelligent data link layer system to progress an adaptive method included in an existing SBMAC and by changing an access control method of a network according to a state of a current channel, a type of a traffic, various securities, an attack, a noise, and disaster information. The system to set a knowledge based SONAR communication environment comprises: a knowledge-based reasoning unit to perform a decision making to form a network based on a transmission variable deducted through a SCB, a current network type, and a value of MIB.

Description

BACKGROUND OF THE INVENTION 1. Field of the Invention The present invention relates to a system and method for establishing an underwater acoustic communication environment using a knowledge base,

BACKGROUND OF THE INVENTION 1. Field of the Invention The present invention relates to a wireless sensor network, and more particularly, to a smart decision block mechanism using a knowledge base.

As the necessity of underwater acoustic communication is increased, the availability of acoustic communication suitable for the ground wireless sensor network and other underwater environments is increasing. Compared to the radio frequency band of terrestrial communication, the long transmission distance due to the low propagation loss and the straightness of the waveform can be secured in the sound frequency band. However, the low transmission rate of 1500m / s requires a large transmission delay time, which is five times the difference compared to the ground. Due to the characteristics such as the transmission capacity limit due to the narrow frequency band of several kilohertz, The design, development and development of a new transmission model of the physical layer are continuously required.

In the data link layer in the underwater sensor network, channel access control and multiple access control according to the marine environment should be studied, and an effective technique for handling extremely limited bandwidth and serious transmission delay in the water should be conceived. It seems to be similar to the sensor network on the ground, but the effect on the equipment efficiency is greatly changed because there are so many differences. To this end, a simple and underwater context adaptive media access mechanism has been proposed as follows.

First, Aloha-based method can be applied in water. Second, it is possible to communicate with multiple nodes at the same time using CDMA (Code Division Multiple Access) method. It is a method which is not greatly affected by delay time, In this paper, we propose a distributed CDMA system that is divided into four sub-channels: Slotted Floor Acquisition Multiple Access (FAMA), Slotted Floor Acquisition Multiple Access (FAMA) In the sixth, cluster-based TDMA (Time Division Multiple Access) is a good approach because it is a method of dividing into multiple clusters and minimizing the disadvantages of TDMA by using TDMA only within the unit cluster. In the seventh, based on the concept of cluster-based TDMA, there is a Smart Block MAC (SBMAC) which can adapt to changes in various environmental characteristics.

In the present invention, the adaptive technique of the existing SBMAC is a system in which a knowledge base system is further applied to the intelligent data link layer system. Therefore, since understanding the existing SBMAC is a measure for understanding the purpose and the result of the present invention, the SBMAC among the media access mechanisms adaptive to the existing underwater situation will be described in more detail.

FIG. 1 is a view for explaining the structure of a conventional SBMAC. As shown in FIG. 1, there is a SCB (Smart Calculation Block) 10 for performing main functions of an SBMAC. And the environment variables such as the receiving distance, frequency, channel state, number of nodes, and load of the network are processed, and the transmission policy and element value necessary for transmission are calculated. Indicative values for this transmission are adaptive to the changing network environment, which is recalculated whenever there is a request for periodic network reconfiguration.

As shown in FIG. 2, the various input variables of the marine environment through the SCB 10 include various transmission and error recovery policies, TDMA and congestion control, , And scheduling. The transmission delay time applied by the number of nodes in the unit network, the error rate of the channel, the depth of water, the temperature and the saltiness are measured and input. The information of the MIB, which is a DB storing the variables in the data link layer, do.

Then, the process referring to the data is operated in the SCB 10. The network congestion estimation process 11 for measuring and sampling the congestion of the network, the channel quality estimation process 12 for measuring the channel quality through the transmission error rate, A network scale estimation process 13 for measuring the size of the network and grouping the distances and calculating a TDMA interval, a gain time reference value, and a guard time reference value, are performed. Finally, a smart calculation process 14 is performed to determine transmission and error recovery policies. The response mode, the transmission mode, the TDMA interval, the gain time information, the garage time information, the beacon interval, the distance list, and the NAV flag information are calculated as the result values. That is, according to the transmission environment of the network, a response, a transmission policy, various TDMAs, a beacon interval, a surplus time calculation value generated in transmission, and various transmission indices are obtained.

Registration No. 10-1022054: Adaptive communication environment setting method and apparatus of underwater sensor network

The present invention further applies the knowledge-based system to the intelligent data link layer system in addition to the adaptive technique of the existing SBMAC as described above, thereby to improve the current channel state, traffic type, security, attack, An object of the present invention is to provide an underwater acoustic communication environment setting system and method using a knowledge base capable of changing a connection control method of a network and reconfiguring a network.

Other objects of the present invention are not limited to the above-mentioned objects, and other objects not mentioned can be clearly understood by those skilled in the art from the following description.

According to another aspect of the present invention, there is provided an underwater acoustic communication environment setting system using a knowledge base, the system comprising: a physician for configuring a network based on a transmission parameter derived through the SCB, And a knowledge-based reasoning unit for performing the decision.

Preferably, the information collected through the SCB includes a MIB, a quality of a channel, a distance between nodes, a number of nodes, mobility, and a function of a node.

Preferably, the knowledge-based reasoning unit includes an input unit for collecting the transmission parameters derived through the SCB, the current network type and the value of the MIB, and a function for analyzing functions of the nodes in the network currently configured based on the transmission parameters input from the input unit, Based on the function information of the nodes classified by the node classifier, a node-classifying unit for classifying the nodes into a Reduced Function Device (FFD) and a Full Function Device (FFD) a network type selection unit for selecting a network type selection unit for selecting a network type selection unit from the network type selection unit, And a second electrode.

Preferably, the node analyzer extracts a beacon or a control message transmission through the transmission parameters or device information from a frame to distinguish the FFD or the RFD.

Preferably, the network type selection unit selects the currently configured network type as the ad-hoc network when the node analyzed by the node analysis unit is RFD, and selects the node type from the changed transmission time when the analyzed node is FFD, If the mobility of the node is mobility, the currently configured network type is selected as the ad-hoc network. If there is a gateway moving in the configured network even if the node is not mobility, the selected network type is selected as the ad- When there is no mobility of a node and there is no gateway moving in the network configured, the currently configured network type is selected as an ad hoc network.

According to another aspect of the present invention, there is provided a method for setting up an underwater acoustic communication environment using a knowledge base, the method comprising the steps of: The knowledge-based reasoning unit for performing the decision comprises: (A) collecting the values of the current network type and the MIB derived from the transmission variables derived through the SCB; and (B) Analyzing the functions of nodes in the network that are currently configured and classifying them into RFD (Reduced Function Device) and FFD (Full Function Device); and (C) if the node is RFD in the configured network, Selecting a network type that is currently configured through the network as a cluster-based unit network; and (D) The method comprising the steps of: (a) selecting a network type currently configured through the network type selection unit as an ad hoc network if the node has mobility in the configured network as a result of the detection; (E) (F) checking if there is a gateway moving in the configured network if the node does not have mobility in the configured network as a result of the detection; and (G) if there is a gateway moving in the configured network, Selecting a network type currently configured through the type selection unit as an ad-hoc network; and (H) if the gateway does not exist in the configured network, Selection And configuring the network type from the network type selection unit to the network selected by the decision unit when the network reconfiguration time comes after (I).

As described above, the underwater acoustic communication environment setting system and method using the knowledge base according to the present invention have the following effects.

When the network configuration format is changed, reconfiguration by message exchange is possible so that the determined items are reflected in the network layer of the upper layer. If it is determined that the set values are valid, the network reconfiguration process is not immediately performed It is possible to prevent waste of network resources for control.

Particularly, when the network environment changes greatly or the number of nodes increases, the efficiency increases as the duty cycle increases and the probability of collision increases, thereby increasing the energy efficiency.

1 is a view for explaining a structure of a conventional SBMAC;
2 is a view for explaining the structure of the SCB of FIG. 1; FIG.
3 is a block diagram illustrating the structure of an underwater acoustic communication environment setting system utilizing a knowledge base according to an embodiment of the present invention.
4 is a block diagram illustrating the structure of the knowledge-based reasoning unit of FIG. 3 in detail;
5 is a flowchart for explaining an underwater acoustic communication environment setting method using a knowledge base according to an embodiment of the present invention.

Other objects, features and advantages of the present invention will become apparent from the detailed description of the embodiments with reference to the accompanying drawings.

A preferred embodiment of the underwater acoustic communication environment setting system and method using the knowledge base according to the present invention will be described with reference to the accompanying drawings. The present invention may, however, be embodied in many different forms and should not be construed as limited to the embodiments set forth herein. Rather, these embodiments are provided so that this disclosure will be thorough and complete, and will fully convey the scope of the invention to those skilled in the art. It is provided to let you know. Therefore, the embodiments described in the present specification and the configurations shown in the drawings are merely the most preferred embodiments of the present invention and are not intended to represent all of the technical ideas of the present invention. Therefore, various equivalents It should be understood that water and variations may be present.

3 is a block diagram illustrating a configuration of an underwater acoustic communication environment setting system using a knowledge base according to an embodiment of the present invention.

As shown in FIG. 3, the present invention includes a knowledge-based reasoning unit for deriving transmission variables through the SCB and performing a decision for network configuration based on the derived variables, the current network type, and the value of the MIB 100).

At this time, the network type is initialized at the time of network configuration, and it can be checked as the network configuration is made. Also, when the transmission period of the network is performed once, network congestion estimation through the SCB, channel quality estimation, The information is collected between nodes. The information collected through the SCB includes MIB, channel quality, distance between nodes, number of nodes, mobility, and functions of nodes.

Meanwhile, the method of deriving the transmission parameters through the SCB is a well known technology. Since the technology for selecting a network using the information derived from the present invention corresponds to the core technology, A detailed description of the method of deriving the transmission parameters is omitted here.

As shown in FIG. 4, the knowledge-based reasoning unit 100 includes an input unit 110 for collecting transmission variables derived through the SCB, a current network type and a value of an MIB, A node analyzer 120 for analyzing the functions of nodes in the currently configured network and classifying the nodes into RFD (Reduced Function Device) and FFD (Full Function Device) A network type selection unit 130 for selecting one of a cluster-based unit network (infra-structured network) and an ad-hoc network based on the function information of the nodes, And a decision unit 140 for performing a decision for the configuration of the selected network in the network type selection unit 130 based on the information collected in the network 110.

At this time, the functions of the nodes can distinguish FFD or RFD by extracting a beacon through transmission parameters, transmission of a control message, or device information from a frame. For reference, FFD is a node that can function as a router, and RFD is a node that can not function as a router.

If the node analyzed by the node analysis unit 120 is RFD, the network type selection unit 130 selects the currently configured network type as an ad-hoc network. If the node analyzed by the node analysis unit 120 is FFD, the mobility of the node is determined from the changing transmission time when data is exchanged. If the node has mobility, the currently configured network type is referred to as an ad- hoc network). On the other hand, in the case where there is a gateway moving within the configured network even when there is no node mobility, a configured network type is selected as an ad-hoc network, and also there is a gateway moving in the network configured when there is no mobility of the node , The currently configured network type is selected as an ad-hoc network.

In addition, the decision-making unit 140 can directly apply the role of the data link layer to the upper layer, and can transmit information to the upper layer so as to modify the configuration, strategy, and policy of the entire network. Can play a role.

The operation of the underwater acoustic communication environment setting system utilizing the knowledge base according to the present invention will be described in detail with reference to the accompanying drawings. Like reference numerals in FIG. 1 or FIG. 2 denote the same members performing the same function.

5 is a flowchart illustrating an underwater acoustic communication environment setting method using a knowledge base according to an embodiment of the present invention.

Referring to FIG. 5, first, the knowledge-based reasoning unit 100 collects the transmission parameters derived through the SCB, the current network type, and the value of the MIB (S10). At this time, information collected through SCB includes MIB, channel quality, distance between nodes, number of nodes, mobility, and functions of nodes.

Next, the node analyzer 120 analyzes the functions of nodes in the network that are currently configured based on the function information of the nodes among the collected information, and classifies them into RFD (Reduced Function Device) and FFD (Full Function Device) (S20). At this time, the functions of the nodes can distinguish FFD or RFD by extracting a beacon through transmission parameters, transmission of a control message, or device information from a frame. For reference, FFD is a node that can function as a router, and RFD is a node that can not function as a router.

If the result of the classification (S20) and the node in the configured network is RFD (S30), the currently configured network type is selected as the cluster-based unit network (infra-structured network) through the network type selection unit 130 (S70). If the result of the classification (S20) and the node in the configured network is FFD (S30), it is detected whether the node has mobility (S40).

If the node has mobility in the configured network (S40), the network type selection unit 130 selects the currently configured network type as the ad-hoc network (S60). If the node does not have mobility in the configured network (S40), it is checked whether there is a moving gateway such as a ship of water or an autonomous unmanned vehicle (AUV) in the constructed network (S50) .

If it is determined in step S50 that there is a gateway moving in the network, the network type selection unit 130 selects the currently configured network type as an ad hoc network in step S60. If it is determined in step S50 that the gateway does not exist in the network, the network type selection unit 130 selects the currently configured network type as a cluster-based unit network in step S70.

When the network reconfiguration time arrives (S80), the network type selection unit 130 configures a network type from the network selection unit 130 through the decision unit 140 (S90).

On the other hand, if there is no changed information (change of network type) when the network reconfiguration time arrives, the next network reconfiguration procedure may be omitted and only a procedure for data transmission may be performed.

While the present invention has been particularly shown and described with reference to exemplary embodiments thereof, it is to be understood that the invention is not limited to the disclosed exemplary embodiments. It will be apparent to those skilled in the art that various modifications may be made without departing from the scope of the present invention. Accordingly, the true scope of the present invention should be determined by the technical idea of the appended claims.

Claims (8)

And a knowledge-based reasoning unit for making a decision for the configuration of the network based on the transmission variables derived through the SCB, the current network type, and the value of the MIB. system. The method according to claim 1,
Wherein the information collected through the SCB includes an MIB, a quality of a channel, a distance between nodes, a number of nodes, mobility, and a function of a node. 2. The method of claim 1, wherein the knowledge-
An input unit for collecting the transmission variables derived through the SCB, the current network type and the value of the MIB,
A node analyzer for analyzing a function of nodes in a currently configured network based on the transmission parameters input from the input unit and classifying the functions into an RFD (Reduced Function Device) and an FFD (Full Function Device)
Based on the function information of the nodes classified by the node classifying unit, a network type selection unit selecting either a cluster-based unit network (infra-structured network) or an ad-hoc network;
And a decision unit for performing a decision for a configuration from the network type selection unit to the network selected based on the information collected by the input unit when the network reconfiguration time arrives. Underwater acoustic communication environment setting system. The method of claim 3,
Wherein the node analyzer extracts a beacon through transmission parameters, transmission of a control message, and device information from a frame to distinguish between FFD and RFD. The apparatus of claim 3, wherein the network type selection unit
If the analyzed node is RFD, the currently configured network type is selected as the ad-hoc network. If the analyzed node is FFD, the mobility of the node is determined from the changed transmission time when data is exchanged, If there is a mobility, the currently configured network type is selected as the ad-hoc network. If there is a gateway moving in the configured network even if there is no mobility of the node, the configured network type is selected as the ad-hoc network. And selects a currently configured network type as an ad-hoc network when there is no gateway moving within the configured network. The knowledge-based reasoning part that makes the decision for the configuration of the network based on the transmission variables derived through the SCB, the current network type and the value of the MIB
(A) collecting values of transmission variables derived via SCB, current network type and MIB,
(B) analyzing the functions of nodes in the network that are currently configured based on the node function information among the collected information through the node analyzing unit and classifying the functions into RFD (Reduced Function Device) and FFD (Full Function Device)
(C) selecting a currently configured network type as a cluster-based unit network through a network type selection unit when the node is an RFD in the configured network as a result of the classification,
(D) if the node is FFD in the configured network as a result of the classification, detecting whether the node has mobility;
(E) if the node has mobility in the configured network as a result of the detection, selecting the network type currently configured through the network type selection unit as an ad hoc network;
(F) checking if there is a gateway moving in the configured network if the node does not have mobility in the configured network as a result of the detection;
(G) selecting a network type currently configured through the network type selection unit as an ad-hoc network if there is a gateway moving in the configured network as a result of the checking,
(H) selecting a currently configured network type as a cluster-based unit network through a network type selection unit when there is no gateway moving within the configured network as a result of the checking,
And configuring a network type from the network type selection unit to a network selected through the decision unit when a network reconfiguration time comes after the step (I). The method according to claim 6,
Wherein the information collected through the SCB includes an MIB, a quality of a channel, a distance between nodes, a number of nodes, mobility, and a function of a node. The method according to claim 6,
Wherein the functions of the nodes are classified into FFDs and RFDs by extracting beacons or transmission messages of control messages or device information from transmission parameters through a frame to determine an underwater acoustic communication environment setting using a knowledge base.

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