Design method of adaptive mac protocol based on dynamic hierarchical authorization system in uasn

Abstract

The application discloses a design method of an adaptive MAC protocol based on a dynamic hierarchical authorization system in a UASNs environment, and comprises the following steps: first, all underwater intelligent agent nodes are layered according to their own delay and time slot length to form multiple sub-networks; second, all intelligent agent nodes broadcast their own relevant information in the whole intelligent agent network for the convenience of recording by other intelligent agent nodes; then, a node is selected as a gateway node from the intelligent agent network, the gateway node is trained using a deep Q network (DQN) to learn the idle time slot occupation strategy at the surface sink node, and the gateway node shares the strategy in the network after the training is completed; next, the remaining intelligent agent nodes adjust the strategy according to their own information so that the strategy can be successfully used; finally, all intelligent agent nodes interact using a multi-level authorization system to select appropriate nodes to occupy idle time slots. Through the use of the dynamic hierarchical authorization system, all intelligent agent nodes can conflict-free use the idle time slots of the remaining nodes which are not fully utilized, the overall throughput of the network is improved, the energy consumption between nodes is effectively balanced, and the overall life of the network is prolonged.

Description

TECHNICAL FIELD

[0001] The application belongs to the field of underwater communication and underwater sensor networks, and particularly relates to an adaptive MAC protocol based on a dynamic hierarchical authorization system for heterogeneous networks in a UASNs environment. BACKGROUND

[0002] Underwater acoustic wireless sensor networks have wide application prospects in environmental monitoring, resource exploration, and auxiliary navigation. However, unlike terrestrial wireless sensor networks, UASNs face challenges such as high propagation delay, limited bandwidth, and channel fading. In addition, the problems of high energy consumption and energy limitation are also significant. Therefore, when designing underwater acoustic wireless sensor networks, these factors need to be considered to optimize system performance.

[0003] Underwater acoustic medium access control (MAC) protocol is an important part of underwater wireless communication networks, and its goal is to effectively manage medium access between multiple sensor nodes to optimize network performance such as throughput, delay, and energy consumption. However, due to the high difficulty of designing underwater acoustic MAC protocols, and as the use scenarios of underwater acoustic sensor networks become increasingly diverse and the scale expands, existing traditional underwater MAC protocols have been difficult to adapt to complex and changing underwater environments. SUMMARY

[0004] To solve the above problems, the application designs an adaptive MAC protocol based on a dynamic hierarchical authorization system for heterogeneous networks in a UASNs environment. By utilizing long propagation delay, the throughput of underwater acoustic sensor networks is effectively improved; by using a dynamic hierarchical and multi-level authorization system, the energy consumption between nodes is balanced, and the overall service life of the network is extended.

[0005] To achieve the above purposes and effects, the application realizes the following technical scheme: an adaptive MAC protocol based on a dynamic hierarchical authorization system for heterogeneous networks in a UASNs environment, comprising the following steps:

[0006] (1) During network initialization, all underwater intelligent agent nodes are layered according to their own delay and time slot length to form multiple sub-networks; each intelligent agent node broadcasts its own related information in the intelligent agent network, and stores information from other intelligent agent nodes.

[0007] (2) A node is selected as a gateway node from the intelligent agent network, and a DQN algorithm is used for training to learn the idle time slot occupation strategy at the surface sink node.

[0008] (3) After the gateway node is trained, the strategy is shared in the intelligent agent network. The remaining intelligent agent nodes adjust the strategy according to their own information so that it can be successfully used.

[0009] (4) All intelligent agent nodes use a multi-level authorization system to interact and select suitable nodes to occupy the idle time slots at the water surface convergence nodes.

[0010] All underwater intelligent agent nodes in the above step (1) are layered according to their own delay and time slot length, each node broadcasts its own information and stores other node information, which includes the following steps:

[0011] (1.1) Assuming that the length of a single time slot is t. t is set as the sum of the length of a data packet t d , a protection time t g and a buffer time t b , that is:

[0012] t = t d + t g + t b (1)

[0013] (1.2) For any intelligent agent node, its delay is τ, then the sub-network level n to which the node belongs can be calculated as follows:

[0014]

[0015] Where [] is the integer symbol; the time delay of the nodes in the sub-network of level n satisfies the condition (n-1)t≤τ≤nt.

[0016] (1.3) After the network is layered, all intelligent agent nodes broadcast their own position, delay information, node ID and the level of the sub-network they belong to in the intelligent agent network; each node stores the received broadcast information and specially marks other nodes in the sub-network it belongs to for subsequent communication.

[0017] Preferably, the gateway node in the above step (2) is selected from the intelligent agent network, and the DQN algorithm is used for training to learn the idle time slot occupation strategy at the water surface convergence node, which includes the following steps:

[0018] (2.1) Since the gateway node needs to bear the additional energy consumption caused by training, the node with the minimum energy consumption is selected as the gateway node for training.

[0019] (2.2) There are three kinds of nodes using different MAC protocols in the underwater acoustic sensor network, which are TDMA nodes, ALOHA nodes and intelligent agent nodes using DHAS-MAC protocol. Among them, TDMA nodes and ALOHA nodes are uniformly deployed, while intelligent agent nodes are randomly deployed. During data transmission, each node uses its own MAC protocol to transmit at the beginning of the time slot.

[0020] (2.3) Since the agent nodes are randomly deployed, they may not meet the condition of conflict-free transmission, that is, the data packet sent at the beginning of the time slot is successfully received by the sink node within the length of a single time slot. Therefore, it is necessary to set the advance transmission time dp for the agent node to meet this condition. Assuming that the delay of the agent node is τ and the level of the subnetwork to which it belongs is n, dp is calculated as follows:

[0021] dp=τ-(n-1)t (3)

[0022] Obviously τ≥(n-1)t, so dp always satisfies dp≥0.

[0023] (2.4) The gateway node uses the DQN algorithm for training. The specific algorithm framework is as follows:

[0024] Action space: At the beginning of each time slot, the agent node can independently decide whether to occupy the time slot for data transmission, so the action space A is defined as:

[0025] A={Transmit,Wait} (4)

[0026] State: When the agent node selects action a at time t t After that, we get the observation value o t ∈{Success,Collision,Idle}. However, due to the existence of long propagation delay and advance sending time, the observation value o t Targeting action a t-2[τ+1] , so action a t The observation value of needs to be obtained at time slot t+2[τ+1]. t = Transmit, and the DLMA node receives the ACK packet at time slot t+2[τ+1], then o t+2[τ+1] =Success, otherwise o t+2[τ+1] =Collision; if a t =Wait, and the DLMA node receives the ACK packet corresponding to other nodes at time slot t+2[τ+1], then o t+2[τ+1] =Success, otherwise o t+2[τ+1] =Idle.

[0027] The actions and observations of a node can form action-observation pairs:

[0028] z t+1 ={a t-2[τ+1] ,o t} (5)

[0029] Since DLMA nodes can only observe part of the network state in each time slot, the network state consists of multiple action-observation pairs, defined as:

[0030] s t+1 ={z t-M+2 ,...,z t+1} (6)

[0031] Here, M represents the length of the historical state. A larger M value indicates that the agent can obtain more historical information. However, as M increases, the state space also expands accordingly.

[0032] Reward: In order to maximize the overall throughput of the network, the agent's reward needs to be combined with the observation value, which is defined as follows:

[0033]

[0034] Due to the long propagation delay underwater, the reward obtained by the agent node when taking action is not immediate. When the slot length is less than 2[τ+1], that is, t<2[τ+1], the agent node will receive a reward when taking action a. t After that, no reward can be obtained from the environment. When t≥2[τ+1], the agent node takes action a t After that you can receive the reward r t+1 , the environment state becomes s t+1 However, the reward t+1 It is aimed at the action at time t-2[τ+1], that is, a t-2[τ+1] , not a t Therefore, the agent node needs to wait for 2[τ+1] time slots to receive the reward corresponding to the action. In order to obtain real and usable training experience Need to sample multiple experiences e t Reorganize. t =(s t ,a t ,r t+1 ,s t+1 ), e t+2[τ+1] =(s t+2[τ+1] ,a t+2[τ+1] ,r t+2[τ+1]+1 ,s t+2[τ+1]+1 ), e t With e t+2[τ+1] Reorganization can gain real experience The real experience gained by reorganizing each time slot Put it into the real experience buffer and train the weight parameter θ of the evaluation network by minimizing the following loss function:

[0035]

[0036] Among them, N E is the size of random sampling; y = ri+2[τ+1]+1 + ymax a' Q(s i+2[τ+1]+1 , a'; 0 - ), 0 - is the weight parameter of the target network, which is set as 0 - = 0 every F time slots.

[0037] Preferably, the remaining agent nodes share the strategy learned by the gateway node in step (3) above, and adjust the strategy according to their own information, which specifically includes the following steps:

[0038] (3.1) When the gateway node is trained, it broadcasts the model parameters obtained by training in the entire agent network.

[0039] (3.2) The remaining nodes receive the parameters and update them to their own neural networks.

[0040] (3.3) Since the delays of the agent nodes are different, the strategy of the gateway node cannot be used directly and needs to be adjusted according to the delay of the node. The advance / delay sending time ds is set for each node, which is calculated as follows:

[0041] ds = τ - τ g (9)

[0042] where τ is the delay of the current node, and τ g is the delay of the gateway node.

[0043] If ds > 0, the current node sends data packets ds seconds in advance based on the shared strategy; if ds < 0, the node sends data packets |ds| seconds later based on the shared strategy.

[0044] Preferably, in step (4) above, all agent nodes use a multi-level authorization system to interact and select appropriate nodes to occupy the idle time slots at the water surface convergence node. The multi-level authorization is divided into two levels, both in the form of control packets transmitted between agent nodes. The first level of authorization is transmitted between different hierarchical sub-networks, and its function is to determine which node in the sub-network occupies the current idle time slot; the second level of authorization is transmitted between nodes in the same hierarchical sub-network, and its function is to determine which node occupies the time slot. Each hierarchical sub-network has a second level of authorization belonging to itself, while the entire agent network has only one first level of authorization. The control packets of the multi-level authorization are transmitted after the nodes have finished sending data packets. The multi-level authorization specifically includes the following contents:

[0045] (4.1) Primary authorization: This authorization is used among sub-networks, and is passed from a node in a higher level sub-network to all nodes in a lower level sub-network, for activating the nodes in the sub-network to use the idle time slots. The primary authorization is first passed from a lower level sub-network to a higher level sub-network, and then passed from the higher level sub-network to a lower level sub-network. During the passing of the primary authorization, each level of sub-network has P times of opportunity to use the primary authorization, i.e. the number of times of using the primary authorization. The value of P is determined by the score of the current sub-network (assuming n) n , and the size of score1 n is determined by two parameters, i.e. the total residual energy of the nodes in the sub-network α n , the number of nodes in the sub-network β n and the data packet stack S n . The calculation of score1 n is as follows:

[0046] score1 n = k1α n + k2β n + k3S n (10)

[0047] wherein k1, k2, k3 are weight parameters, which are used to normalize the three indexes to the same order of magnitude, and then to allocate the proportion of each index according to the importance; α n can be calculated by the energy consumption model; the energy consumption model mainly considers the energy consumption of the communication module, and the average power consumption of the communication module is expressed as:

[0048] E = N tx · [P tx · (T tx + T st ) + P out · T tx ] + N rx · [P rx · (T rx + T st )] (11)

[0049] wherein N tx / rx is the working times of the sending / receiving unit; P tx / rx is the average energy consumption of the circuit of the sending / receiving unit; P out is the output power; T sw is the state switching time, which is assumed to be the same; T tx / rx is the working time of the sending / receiving unit, which is mainly determined by the data packet length, the transmission rate and the coding rate, i.e.

[0050] T tx / rx = l / R · R code(12)

[0051] where l is the length of data packet, R is the bit rate, R code is the coding rate.

[0052] When the residual energy of a node in a sub-network is too low or the node has no data to send temporarily, the node sends a control signal to the other nodes in the current sub-network and exits the score calculation. The score of the sub-network is updated after the sub-network has used up the number of primary authorization uses, and the information is stored in the control packet of the primary authorization and passed to the next sub-network for the calculation of the subsequent sub-network.

[0053] The score of each layer of sub-network is normalized, and the normalized score Q n of the nth layer of sub-network is:

[0054]

[0055] where m is the total number of sub-networks; min(score11, score12, …, score1 m ≠ 0, i.e. the sub-networks with a score of 0 are not counted in the calculation of the number of primary authorization uses.

[0056] The number of primary authorization uses P n of the nth layer of sub-network is defined as follows:

[0057]

[0058] (4.2) Secondary authorization: The authorization is used among the nodes in a sub-network to determine which node occupies the idle time slot. The order of use of the secondary authorization depends on the score score2 of each node in the network, which is determined by two parameters, the residual energy R and the data packet stack S of the current node, and is calculated as follows:

[0059]

[0060] where w1 and w2 are weight parameters for balancing the energy consumption and throughput of the nodes; R threshold is the residual energy threshold of the node, and the node no longer sends data packets when the threshold is less than the threshold. The score of each node is updated after each use of the secondary authorization, and the score information is stored in the control packet of the secondary authorization and passed to the next node.

[0061] Each node in the sub-network uses the secondary authorization in turn according to the score size until the number of primary authorization uses is used up. If the number of primary authorization uses of the sub-network is greater than the number of nodes in the network, i.e. P > η, the secondary authorization is used in a loop according to the score size until the number of primary authorization uses is used up.

[0062] (4.3) Each node will send a small control packet after sending the data packet. The control packet contains an information matrix. The specific content of the information matrix is ​​as follows:

[0063]

[0064] The control packet contains the ID of the current sending node sender , residual energy R sender , Data packet stacking amount S sender and the IDs of all other nodes in the agent network i (i≠sender), the corresponding remaining energy R i and packet stacking amount S i The control packet sent by each node contains the energy and data packet stacking information of other nodes. The purpose of including this redundant information is to prevent the loss of control packets from causing untimely updates of node information.

[0065] Each agent node has a local information table, which contains the ID of the current sending node. sender , the subnetwork level, the level of the current subnetwork n sender , Level 1 authorized usage times P sender , Score2 of the current node sender and the IDs of all other nodes i (i≠sender), sub-network level n i , the corresponding first-level authorized usage times P i and score Score2 i The node updates the relevant information in the local information table through the obtained control packet and calculates the corresponding first-level authorization usage count and second-level authorization usage order. BRIEF DESCRIPTION OF THE DRAWINGS

[0066] Figure 1 Flowchart of the embodiment of this article;

[0067] Figure 2 It is the application scenario diagram;

[0068] Figure 3 Transmit scene graph for conflict-free transmission;

[0069] Figure 4 Schematic diagram for setting advance\delay sending time; DETAILED DESCRIPTION

[0070] In order to enable personnel in the technical field to better understand the technical solutions in the present application, the technical solutions in the embodiments of the present application are described clearly and completely below. Obviously, the described embodiments are only some of the embodiments of the present application, not all the embodiments. Based on the embodiments in the present application, all other embodiments obtained by those skilled in the art without creative work should belong to the scope of protection of the present application.

[0071] The application principle of the present application is described in detail below in combination with the drawings.

[0072] As shown in Figure 2 , the TDMA nodes and the ALOHA nodes are uniformly distributed at different depths underwater to form a TDMA+ALOHA node network; the agent nodes are randomly distributed at different depths underwater to form an agent network. Each sensor node collects underwater data and transmits the data packets to the surface sink node directly through single-hop transmission. The TDMA and ALOHA nodes use TDMA and ALOHA protocols respectively, and the agent nodes use the DHASA-MAC protocol. The TDMA nodes and the ALOHA nodes do not interact with other nodes, and the agent nodes interact with each other using a multi-level authorization system.

[0073] A self-adaptive MAC protocol based on a dynamic hierarchical authorization system in a UASNs environment, as shown in Figure 1 , specifically includes the following steps:

[0074] (1) Layering of the agent node network

[0075] (1.1) Assuming that the length of a single time slot is t. t is set as the sum of the length of a data packet t d , a protection time t g , and a buffer time t b , that is:

[0076] t=t d +t g +t b (1)

[0077] (1.2) For any agent node, if the delay of the node is τ, then the sub-network level n to which the node belongs can be calculated as follows:

[0078]

[0079] where [] is the rounding symbol; the time delay of the node in the sub-network at level n satisfies the condition (n-1)t≤τ≤nt.

[0080] (1.3) After the completion of network layering, all agent nodes broadcast their own position, delay information, node ID and the level of the sub-network they belong to in the agent network; each node stores the received broadcast information and marks other nodes in the sub-network it belongs to, so as to facilitate subsequent communication.

[0081] (2) Selection and training of gateway nodes

[0082] The DQN algorithm is used for training to learn the idle time slot occupation strategy at the water surface convergence node, which includes the following steps:

[0083] (2.1) Since the gateway node needs to bear the additional energy consumption caused by training, the node with the minimum energy consumption is selected as the gateway node for training.

[0084] (2.2) There are three types of nodes using different MAC protocols in the underwater acoustic sensor network, which are TDMA nodes, ALOHA nodes and agent nodes using DHAS-MAC protocol. Among them, TDMA nodes and ALOHA nodes are uniformly deployed, while agent nodes are randomly deployed. When transmitting data, each node uses its own MAC protocol to transmit at the beginning of the time slot.

[0085] (2.3) Since the agent nodes are randomly deployed, they may not meet the condition of collision-free transmission, that is, the data packet sent by the agent node at the beginning of the time slot is successfully received by the convergence node within a single time slot length, so the agent node needs to be set with an early sending time dp to meet this condition. Assuming that the time delay of the agent node is τ and the level of the sub-network it belongs to is n, then dp The calculation is as follows:

[0086] dp = τ - (n-1)t (3)

[0087] Obviously τ ≥ (n-1)t, so dp always satisfies dp ≥ 0. The condition of collision-free transmission is shown in Figure 3 (a), where the data packet sent by the agent node at the beginning of the time slot is received by the convergence node in the middle of the time slot. If this condition cannot be met, the scenario shown in Figure 3 (b) will occur, where the data packet sent by agent node 1 collides with the data packet sent by the TDMA node in time slot t = 3, resulting in a decrease in network throughput. After setting the early sending time dp for the agent node, collision-free transmission between nodes can be achieved, as shown in Figure 3 (c).

[0088] (2.4) The gateway node uses the DQN algorithm for training, and the specific algorithm framework is as follows:

[0089] Action space: At the beginning of each time slot, the agent node can autonomously decide whether to occupy the time slot for data transmission, so the action space A is defined as:

[0090] A = {Transmit, Wait} (4)

[0091] State: When the agent node chooses action a t at time t, it will get observation o t ∈ {Success, Collision, Idle}. However, due to the long propagation delay and the existence of early sending time, the observation o t is for action a t-2[τ+1] , so the observation of action a t needs to be obtained at time slot t+2[τ+1]. If a t = Transmit, and the DLMA node receives an ACK packet at time slot t+2[τ+1], then o t+2[τ+1] = Success, otherwise o t+2[τ+1] = Collision; if a t = Wait, and the DLMA node receives an ACK packet corresponding to other nodes at time slot t+2[τ+1], then o t+2[τ+1] = Success, otherwise o t+2[τ+1] = Idle.

[0092] The action and observation of the node can form an action-observation pair:

[0093] z t+1 = {a t-2[τ+1] , o t} (5)

[0094] Since the DLMA node can only observe part of the network state at each time slot, the state of the network is composed of multiple action-observation pairs, defined as:

[0095] s t+1 = {z t-M+2 ,..., z t+1} (6)

[0096] where M represents the length of the historical state. The larger the value of M, the more historical information the agent can obtain. However, as M increases, the state space will also expand accordingly.

[0097] Reward: In order to maximize the overall throughput of the network, the reward of the agent needs to be combined with the observation value, which is defined as follows:

[0098]

[0099] Due to the effect of long propagation delay underwater, the reward obtained by the agent node for taking an action is not immediate. When the time slot length is less than 2[τ+1], i.e., t<2[τ+1], the agent node cannot obtain any reward from the environment after taking an action a t . When t≥2[τ+1], the agent node can receive a reward r t after taking an action a t+1 , and the environment state becomes s t+1 . However, the reward r t+1 is for the action at time t-2[τ+1], i.e., a t-2[τ+1] , not a t , so the agent node needs to wait for 2[τ+1] time slots to receive the reward corresponding to the action. In order to obtain real and available training experience , multiple sampled experiences e t need to be recombined. For example, e t = (s t , a t , r t+1 , s t+1 ) and e t+2[τ+1] = (s t+2[τ+1] , a t+2[τ+1] , r t+2[τ+1]+1 , s t+2[τ+1]+1 ), recombining e t and e t+2[τ+1] can obtain real experience . The real experience obtained by recombining each time slot is put into the real experience buffer, and the weight parameters θ of the evaluation network are trained by minimizing the following loss function:

[0100]

[0101] where N E is the size of random sampling; y = r i+2[τ+1]+1 + γmax a' Q(s i+2[τ+1]+1 , a'; θ - ), θ - is the weight parameter of the target network, which is obtained by setting θ - = θ every F time slots.

[0102] (3) Agent network policy sharing

[0103] (3.1) After the gateway node is trained, it broadcasts the model parameters obtained by training in the entire agent network.

[0104] (3.2) The remaining nodes receive the parameters and update them to their own neural networks.

[0105] (3.3) Since the delay of each agent node is different, the strategy of the gateway node cannot be directly used and needs to be adjusted according to its own delay. The advance / delay sending time ds of each node is set as follows:

[0106] ds = τ - τ g (9)

[0107] where τ is the delay of the current node, τ g is the delay of the gateway node.

[0108] If ds > 0, the current node sends the data packet in advance of ds seconds based on the shared strategy; if ds < 0, the node sends in delay of |ds| seconds based on the shared strategy.

[0109] (4) Use multi-level authorization for interaction

[0110] The multi-level authorization is divided into two levels, which are both in the form of control packets and transmitted between agent nodes. The first level authorization is transmitted between different hierarchical sub-networks, and its role is to determine which node in the sub-network occupies the idle time slot; the second level authorization is transmitted between nodes in the same hierarchical sub-network, and its role is to determine which node occupies the time slot. It should be noted that each hierarchical sub-network has a second level authorization belonging to itself, while the entire agent network has only one first level authorization. The control packets of multi-level authorization are all transmitted after the nodes send the data packets.

[0111] The first and second level authorizations are described in detail as follows:

[0112] First level authorization: This authorization is used between sub-networks and is transmitted by the nodes in the upper layer sub-network to all nodes in the lower layer sub-network, which is used to activate the nodes in the sub-network to use the idle time slot. The first level authorization is first transmitted from the lower hierarchical sub-network to the higher hierarchical sub-network, and then from the higher hierarchical sub-network to the lower hierarchical sub-network. During the transmission of the first level authorization, each hierarchical sub-network has P times of opportunity to use the first level authorization, i.e. the number of times of using the first level authorization. The value of P is determined by the score of the current sub-network (assuming n), score1 n , while the size of score1 n depends on two parameters, which are the total residual energy of the nodes in the sub-network α n , the number of nodes in the sub-network β n and the data packet stacking amount S n . The calculation of score1 n is as follows:

[0113] score1 n = k1α n + k2β n + k3S n(10)

[0114] wherein k1, k2, k3 are weight parameters, which normalize the three indexes to the same order of magnitude, and then allocate the proportion of each index according to the importance; a n The energy consumption model can be calculated; the energy consumption model mainly considers the energy consumption of the communication module, and the average power consumption of the communication module is represented as:

[0115] E=N tx ·[P tx ·(T tx +T st )+P out ·T tx ] +N rx ·[P rx ·(T rx +T st )] (11)

[0116] wherein N tx / rx is the number of times of sending / receiving unit working; P tx / rx is the average energy consumption of the circuit of the sending / receiving unit; P out is the output power; T sw is the state switching time, which is assumed to be the same; T tx / rx is the sending / receiving unit working time, which is mainly determined by the data packet length, transmission rate, and coding rate, i.e.:

[0117] T tx / rx =l / R·R code (12)

[0118] wherein l is the data packet length, R is the bit rate, and R code is the coding rate.

[0119] When the residual energy of a node in a subnetwork is too low or there is no sending task temporarily, the node will send a control signal to the remaining nodes in the current subnetwork to exit the score calculation. The score of the subnetwork is updated after the subnetwork uses up the number of primary authorization uses, and the information is stored in the control packet of the primary authorization and passed to the next layer subnetwork for subsequent subnetwork calculation.

[0120] The scores of each layer of subnetworks are standardized, and the standardized score Q n of the nth layer of subnetworks is:

[0121]

[0122] wherein m is the total number of subnetworks; min(score11, score12,..., score1 m)≠0, that is, the sub-network with a score of 0 is not included in the calculation of the number of times the first-level authorization is used.

[0123] The number of times P the first-level authorized usage of the n-th layer sub-network n The definition is as follows:

[0124]

[0125] (4.2) Secondary authorization: This authorization is used between nodes in a sub-network to determine which node will occupy an idle time slot. The order in which the secondary authorization is used depends on the score 2 of each node in the network. The score is determined by two parameters: the remaining energy R of the current node and the amount of data packet stacking S. It is calculated as follows:

[0126]

[0127] Among them, w1 and w2 are weight parameters used to balance the energy consumption and throughput of the node; R threshold The node's remaining energy threshold is less than this threshold, and the node will no longer send data packets. The score of each node is updated after each use of the secondary authorization, and the score information is stored in the secondary authorization control packet and passed to the next node.

[0128] Each node in the sub-network uses the secondary authorization in turn according to its score until the primary authorization is used up. If the primary authorization usage count of the sub-network is greater than the number of nodes in the network, that is, P > η, the secondary authorization will continue to be used in a circular manner according to the score until the primary authorization is used up.

[0129] (4.3) Each node will send a small control packet after sending the data packet. The control packet contains an information matrix. The specific content of the information matrix is ​​as follows:

[0130]

[0131] The control packet contains the ID of the current sending node sender , residual energy R sender , Data packet stacking amount S sender and the IDs of all other nodes in the agent network i (i≠sender), the corresponding remaining energy R i and packet stacking amount S i The control packet sent by each node contains the energy and data packet stacking information of other nodes. The purpose of including this redundant information is to prevent the loss of control packets from causing untimely updates of node information.

[0132] Each agent node has a local information table, and the specific information is shown in Table 1. The information table includes the ID ID of the current sending node sender , the sub-network level n sender to which the node belongs sender , the primary authorized use times P of the current sub-network sender , the score Score2 of the current node i , and the ID ID of all other nodes (i≠sender), the sub-network level n i to which the node belongs i , the corresponding primary authorized use times P i , and the score Score2. The node updates the relevant information in the local information table through the obtained control packet, and calculates the corresponding primary authorized use times and secondary authorized use order.

[0133] Table 1. Local information table of an agent node

[0134] ID sender ]]> n sender ]]> P sender ]]> Score2 sender ]] ID i ]]> n i ]]> P i ]]> Score2 i ]] ... ... ... ...

[0135] Finally, it should be noted that the method steps described in combination with the embodiments disclosed in the present application can be configured to build a programming environment for implementation. Obviously, those skilled in the art can make various modifications and variations to the present application without departing from the scope of the present application. Thus, if these modifications and variations of the present application fall within the scope of the claims of the present application and their equivalent technologies, the present application also intends to include these modifications and variations.

Claims

1. A method for designing an adaptive MAC protocol based on a dynamic hierarchical authorization system in a UASN environment, characterized by: The following steps are involved: (1) During network initialization, all underwater intelligent nodes are layered according to their own delays and time slot lengths to form multiple sub-networks. Each intelligent node broadcasts its own relevant information in the intelligent network and stores information from other intelligent nodes. (2) Select a node from the agent network as the gateway node and use the DQN algorithm for training to learn the idle time slot occupation strategy at the water surface aggregation node; (3) After the gateway node is trained, the strategy described in step (2) is shared in the agent network, and the remaining agent nodes adjust the strategy described in step (2) based on their own information so that it can be successfully used; (4) All intelligent nodes interact using a multi-level authorization system to select appropriate nodes to occupy the idle time slots at the surface aggregation node; The multi-level authorization in step (4) is divided into two levels, both of which are transmitted between intelligent body nodes in the form of control packets, wherein the first-level authorization is transmitted between sub-networks of different levels, and its function is to determine which node in the sub-network occupies the current idle time slot; the second-level authorization is transmitted between nodes in the sub-network of the same level, and its function is to determine which node occupies the time slot; each layer of sub-network has its own second-level authorization, and the entire intelligent body network has only one first-level authorization, and the control packets of the multi-level authorization are all transmitted after the node sends the data packet.

2. The method for designing an adaptive MAC protocol based on a dynamic hierarchical authorization system in UASNs according to claim 1, characterized in that: The step (1) specifically includes the following steps: (2.1) Assume that the length of a single time slot is t, and t is set to the packet length t d , protection time t g and buffer time t b The sum is: t=t d +t g +t b (1) (2.2) For any agent node, whose delay is τ, the subnetwork level n to which the node belongs is calculated as follows: Where [] is a rounding symbol; the delay of the nodes in the sub-network of level n satisfies the condition (n-1)t≤τ≤nt; (2.3) After the network layering is completed, all intelligent nodes broadcast their own location, delay information, node ID and the level of the sub-network to which they belong in the intelligent network; each node stores the received broadcast information and specially marks other nodes in its own sub-network for subsequent communication.

3. The method for designing an adaptive MAC protocol based on a dynamic hierarchical authorization system in UASNs according to claim 1, characterized in that: The step (2) specifically includes the following steps: (3.1) Since the gateway node needs to bear the additional energy overhead caused by training, the node with the lowest sending energy consumption is selected as the gateway node for training; (3.2) There are three types of nodes using different MAC protocols in the underwater acoustic sensor network: TDMA nodes, ALOHA nodes, and agent nodes using the DHAS-MAC protocol. TDMA nodes and ALOHA nodes are uniformly deployed, while agent nodes are randomly deployed. During data transmission, each node uses its own MAC protocol and transmits at the beginning of the time slot. (3.3) Since the agent nodes are randomly deployed, it is necessary to set the advance sending time dp for the agent nodes to ensure that the data packets sent at the beginning of the time slot are successfully received by the sink node within the length of a single time slot. Assuming that the delay of the agent node is τ and the level of the subnetwork to which it belongs is n, dp is calculated as follows: dp=τ-(n-1)t (3) Obviously τ≥(n-1)t, so dp always satisfies dp≥0; (3.4) The gateway node uses the DQN algorithm for training. The specific algorithm framework is as follows: Action space: At the beginning of each time slot, the agent node can independently decide whether to occupy the time slot for data transmission, so the action space A is defined as: A={Transmit,Wait} (4) State: When the agent node selects action a at time t t After that, we get the observation value o t ∈{Success,Collision,Idle}, however, due to the existence of long propagation delay and advance sending time, the observation value o t Targeting action a t-2[τ+1] , so action a t The observation value needs to be obtained at time slot t+2[τ+1]. If a t = Transmit, and the DLMA node receives the ACK packet at time slot t+2[τ+1], then o t+2[τ+1] =Success, otherwise o t+2[τ+1] =Collision; if a t =Wait, and the DLMA node receives the ACK packet corresponding to other nodes at time slot t+2[τ+1], then o t+2[τ+1] =Success, otherwise o t+2[τ+1] =Idle; The actions and observations of a node constitute an action-observation pair: from t+1 ={a t-2[τ+1] ,o t } (5) Since DLMA nodes can only observe part of the network state in each time slot, the network state consists of multiple action-observation pairs, defined as: s t+1 ={z t-M+2 ,...,z t+1 } (6) Among them, M represents the length of the historical state. The larger the M value, the more historical information the agent can obtain. However, as M increases, the state space will also expand accordingly. Reward: In order to maximize the overall throughput of the network, the agent's reward needs to be combined with the observation value, which is defined as follows: When the slot length is less than 2[τ+1], that is, t<2[τ+1], the agent node takes action a t After that, no reward can be obtained from the environment. When t≥2[τ+1], the agent node takes action a t After that, you can receive the reward r t+1 , the environment state becomes s t+1 ; However, the reward r t+1 It is aimed at the action at time t-2[τ+1], that is, a t-2[τ+1] , not a t Therefore, the agent node needs to wait for 2[τ+1] time slots to receive the reward corresponding to the action. In order to obtain real and usable training experience Need to sample multiple experiences e t to reorganize; The reorganization is as follows: e t =(s t ,a t ,r t+1 ,s t+1 )、e t+2[τ+1] =(s t+2[τ+1] ,a t+2[τ+1] ,r t+2[τ+1]+1 ,s t+2[τ+1]+1 ) e t With e t+2[τ+1] Reorganize and gain real experience The real experience gained by reorganizing each time slot Put it into the real experience buffer and train the weight parameters θ of the evaluation network by minimizing the following loss function: Among them, N E is the size of random sampling; y = r i+2[τ+1]+1 +γmax a' Q(s i+2[τ+1]+1 ,a';θ - ),θ - is the weight parameter of the target network, which is set by setting θ every F time slots - =θ to obtain.

4. The method for designing an adaptive MAC protocol based on a dynamic hierarchical authorization system in UASNs according to claim 1, wherein: The step (3) specifically includes the following steps: (4.1) When the gateway node is trained, it broadcasts the trained model parameters to the entire agent network; (4.2) The remaining nodes receive the parameter and update it into their own neural network; (4.3) Since the delay of each agent node is different, the strategy of the gateway node cannot be used directly. It needs to be adjusted according to its own delay and set the advance / delay sending time ds for each node. The calculation is as follows: ds=τ-τ g (9) Where τ is the delay of the current node, τ g is the delay of the gateway node; If ds>0, the current node sends the data packet ds seconds in advance based on the sharing strategy; if ds<0, the node delays sending the data packet by |ds| seconds based on the sharing strategy.

5. The method for designing an adaptive MAC protocol based on a dynamic hierarchical authorization system in UASNs according to claim 1, characterized in that: The multi-level authorization in step (4) specifically includes the following: (5.1) Level 1 authorization: This authorization is used between sub-networks and is passed from the nodes in the upper sub-network to all nodes in the lower sub-network. It is used to activate the nodes in the sub-network to use the idle time slots. The level 1 authorization is first passed from the lower sub-network to the higher sub-network, and then from the higher sub-network to the lower sub-network. During the level 1 authorization transmission process, each sub-network has P opportunities to use the level 1 authorization, that is, the number of times the level 1 authorization is used. The value of P is determined by the score of the current sub-network. n Decision, the current sub-network is assumed to be n; and score1 n The size of depends on three parameters, namely the total residual energy of nodes in the sub-network α n , the number of nodes in the sub-network β n and packet stacking amount S n , score1 n The calculation of is as follows: score1 n =k1α n +k2β n +k3S n (10) Among them, k1, k2, and k3 are weight parameters, which are used to normalize the three indicators to the same order of magnitude and then allocate the proportion of each indicator according to its importance; α n Calculated through the energy consumption model; the energy consumption model takes into account the energy consumption of the communication module. The average working power consumption of the communication module is expressed as: E=N tx ·[P tx ·(T tx +T st )+P out ·T tx ]+N rx ·[P rx ·(T rx +T st )] (11) Among them, N tx / rx is the number of times the sending / receiving unit works; P tx / rx is the average energy consumption of the circuit of the sending / receiving unit; P out is the output power; T st is the state switching time, assuming that the state switching time is the same; T tx / rx It is the working time of the sending / receiving unit, which is determined by the data packet length, transmission rate, and coding rate, that is: T tx / rx =l / R·R code (12) Among them, l is the packet length, R is the bit rate, R code is the coding rate; When the remaining energy of a node in a sub-network is too low or there is no task to send temporarily, the node will send a control signal to the other nodes in the current sub-network to exit the score calculation. The score of the sub-network will be updated after the network has used up the number of times the first-level authorization is used, and the information will be stored in the control packet of the first-level authorization and passed to the next-level sub-network for calculation of subsequent sub-networks. The scores of each layer of sub-network are standardized, and the standardized score Q of the nth layer of sub-network is n for: Where m is the total number of sub-network layers; min(score11, score12, K, score1 m )≠0, that is, the sub-network with a score of 0 is not included in the calculation of the number of times the first-level authorization is used; The number of times P the first-level authorized usage of the n-th layer sub-network n The definition is as follows: (5.2) Secondary authorization: This authorization is used between nodes in a sub-network to determine which node will occupy an idle time slot. The order in which the secondary authorization is used depends on the score 2 of each node in the network. The score is determined by two parameters: the remaining energy R of the current node and the amount of data packet stacking S. It is calculated as follows: Among them, w1 and w2 are weight parameters used to balance the energy consumption and throughput of the node; R threshold The node's remaining energy threshold is less than this threshold, and the node will no longer send data packets. The score of each node is updated after each use of the secondary authorization, and the score information is stored in the secondary authorization control packet and passed to the next node. Each node in the sub-network uses the secondary authorization in turn according to the size of the score until the primary authorization is used up. If the number of times the primary authorization has been used in the sub-network is greater than the number of nodes in the network, that is, P>η, the secondary authorization will continue to be used in a circular manner according to the size of the score until the primary authorization is used up. (5.3) Each node will send a small control packet after sending the data packet. The control packet contains an information matrix. The specific content of the information matrix is ​​as follows: The control packet contains the ID of the current sending node. sender , residual energy R sender , Data packet stacking amount S sender And the ID information of all other nodes in the agent network is ID i , where i≠sender, the corresponding residual energy R i and packet stacking amount S i The control packet sent by each node contains the energy and packet stacking information of other nodes. The purpose of including this redundant information is to prevent the loss of control packets and the untimely update of node information. Each agent node has a local information table, which contains the ID of the current sending node. sender , the subnetwork level, the level of the current subnetwork n sender , Level 1 authorized usage times P sender , Score2 of the current node sender And the ID information of all other nodes is ID i , where i≠sender, belongs to the sub-network level n i , the corresponding first-level authorized usage times P i and score Score2 i ; The node updates the relevant information in the local information table through the obtained control packet, and calculates the corresponding first-level authorization usage times and second-level authorization usage order.

Images