Energy consumption optimization method and system based on seabed data center environment monitoring

Abstract

The invention relates to an energy consumption optimization method and system based on seabed data center environment monitoring. The method comprises the following steps: a seabed center node converts an energy consumption optimization electric signal into an information packet comprising positioning information of each underwater mobile node and node ID information through a split beam sonar; broadcasting the information packet to each underwater mobile node in the seabed center node communication area; performing non-cooperative game clustering on each underwater mobile node by adopting an energy consumption balance optimization clustering algorithm based on the game theory to realize energy balance among the underwater mobile nodes; the shore station monitoring platform is connected with the sea surface floating platform, and a power distribution system is arranged on the sea surface floating platform and provides uninterrupted electric energy for the seabed data center cabin. And each underwater mobile node performs non-cooperative game clustering in the clustering process by adopting an energy consumption balance optimization clustering algorithm based on the game theory so as to balance the energy consumption of each underwater mobile node and guarantee the continuity of data monitoring of the submarine data center.

Description

Technical Field

[0001] The present invention relates to the technical field of submarine environment monitoring, and in particular to an energy consumption optimization method and system based on submarine data center environment monitoring. Background Art

[0002] With the development of society, people pay more and more attention to the protection of the submarine environment. The submarine data center environmental monitoring system can effectively collect submarine environmental information in real time, and promptly warn of abnormal situations. It has the advantages of high real-time data monitoring, flexible deployment, and strong stability. The "Neptune" submarine observation network program (NEPTUNE) jointly established by the United States and Canada is the world's largest submarine data center observation network. It realizes the monitoring of various biological, chemical, and physical elements on the seabed. It has the characteristics of scalability, large transmission capacity, high data rate, sufficient energy, and strong interactivity. The Global Ocean Observing System (GOOS) is currently highly comprehensive, with a total of more than 9,000 observation devices in normal operation, providing reliable data for protecting the marine environment, predicting climate change, and disaster warning.

[0003] Among the domestic submarine environmental monitoring systems, an underwater environmental monitoring system for submarine data centers has been invented to solve the problem that the communication signals of submarine data centers are easily interfered with in the prior art. However, this type of fixed monitoring method for submarine data centers still has shortcomings such as scattered monitoring data and weak real-time monitoring. To this end, based on the underwater data center, an integrated underwater environmental monitoring and communication device and a three-dimensional marine monitoring network are designed, which can be carried on underwater mobile nodes and send underwater environmental monitoring information in real time through hydroacoustic communication, solving the shortcomings of traditional underwater fixed equipment with scattered monitoring ranges and the inability to perform hydroacoustic communication while monitoring. However, underwater mobile nodes still have insufficient battery power and shortened network life caused by the death of a single node, which leads to discontinuity of monitoring data and waste of energy in the submarine data center.

[0004] However, the above underwater center data monitoring methods often monitor scattered areas, and the continuity of submarine data center monitoring is insufficient. Summary of the invention

[0005] Based on this, in order to solve the above technical problems, an energy consumption optimization method and system based on submarine data center environmental monitoring are provided, which can cluster mobile nodes in the underwater acoustic network to balance node energy consumption and ensure the continuity of submarine data center data monitoring.

[0006] An energy consumption optimization method based on submarine data center environmental monitoring, the method comprising:

[0007] The submarine central node converts the energy consumption optimization electrical signal into an acoustic signal through the split beam sonar, wherein the acoustic signal contains an information packet consisting of the positioning information and node ID information of each underwater mobile node; and broadcasts the information packet to each underwater mobile node in the communication area of ​​the submarine central node;

[0008] Each underwater mobile node uses a game theory-based energy consumption balance optimization clustering algorithm to perform non-cooperative game clustering according to the broadcast information packet, so as to achieve energy balance among each underwater mobile node, and collect seabed environment data through each underwater mobile node after energy balance;

[0009] Each of the underwater mobile nodes transmits the collected seabed environmental data to the seabed central node, converts the seabed environmental data acoustic signal into an electrical signal through the hydrophone on the seabed central node, compresses and encodes the seabed environmental data, and transmits it to the main control computer in the seabed data center cabin through a watertight joint, pushes it to the sea surface floating platform through the main control computer, and finally transmits it to the monitoring switch on the shore station monitoring platform;

[0010] The shore station monitoring platform is connected to the sea surface floating platform, and a power distribution system is arranged on the bearing plate of the sea surface floating platform to provide uninterrupted power for the submarine data center cabin;

[0011] If the shore station monitoring platform receives a control instruction sent from the user monitoring terminal and sends a seabed monitoring task to the seabed data center cabin, the seabed data center cabin processes the seabed environmental data and pushes it to the user monitoring terminal.

[0012] In one embodiment, the method further comprises:

[0013] In the communication area corresponding to the seabed central node, each of the underwater mobile nodes is divided into ordinary member nodes and cluster head nodes;

[0014] The common member nodes communicate with the cluster head nodes by acoustic waves, and the cluster head nodes transmit information to the seabed central node through multi-hop mode with other cluster head nodes as relays.

[0015] In one embodiment, the method further comprises:

[0016] Construct an underwater acoustic clustering network system model;

[0017] Based on the underwater acoustic clustering network system model, an underwater channel model is established;

[0018] According to the underwater channel model, the channel correlation distance between each of the ordinary member nodes and the cluster head node is calculated based on the underwater channel condition to determine the channel correlation distance metric;

[0019] Based on the channel correlation distance metric, the flow weight generated by each of the ordinary member nodes in the cluster to the cluster head node is calculated, and the total weight of the cluster head node is calculated;

[0020] The energy consumption of the common member nodes and the cluster head nodes is calculated based on the underwater channel model, and an energy consumption model is established.

[0021] In one embodiment, the method further comprises:

[0022] Defining each of the underwater mobile nodes as a set of competition participants, defining a set of strategies for the current game of each of the underwater mobile nodes, and defining a set of revenue functions of the game nodes;

[0023] Determine the corresponding benefit function when each of the underwater mobile nodes selects different game strategies, calculate the cost and benefit based on the energy consumption model according to the benefit function, and construct a node game model.

[0024] An energy consumption optimization system based on submarine data center environmental monitoring, the system comprises: a shore station monitoring platform, a submarine data center cabin, a submarine central node, and an underwater mobile node, wherein:

[0025] The shore station monitoring platform is connected to a sea surface floating platform, and a power distribution system is arranged on the bearing plate of the sea surface floating platform, which is connected to the seabed data center cabin through an underwater cable to provide uninterrupted power to the seabed data center cabin;

[0026] The submarine data center cabin is connected to each of the submarine central nodes and receives submarine monitoring information transmitted from each of the submarine central nodes;

[0027] Each of the submarine central nodes is used to broadcast a clustering notification to each of the underwater mobile nodes in the communication area corresponding to the submarine central node, notifying each of the underwater mobile nodes to adopt an energy consumption balance optimization clustering algorithm based on game theory to perform non-cooperative game clustering;

[0028] The seabed central node is connected to a hydrophone and a split-beam sonar. The hydrophone is used to receive the acoustic signal collected by the underwater mobile node and convert it into an electrical signal for transmission to the seabed central node; the split-beam sonar is used to convert the electrical signal emitted by the seabed central node into an acoustic signal and broadcast it to the underwater mobile node.

[0029] In one of the embodiments, the system further includes a shore station server and a user monitoring terminal;

[0030] Each of the submarine central nodes is provided with a digital-to-analog converter, which converts the received submarine monitoring information into a digital signal, and compresses and encodes the digital signal before transmitting it to the submarine data center cabin through a watertight joint;

[0031] The main control computer in the submarine data center cabin performs communication protocol analysis on the transmitted data, and pushes the analyzed data to the sea surface floating platform respectively;

[0032] The sea surface floating platform transmits the parsed data to the shore station server at the shore station monitoring platform, and the shore station server pushes it to the user monitoring terminal.

[0033] In one embodiment, a monitoring switch is provided at the shore station monitoring platform, a switch is provided in the submarine data center cabin, the switch is connected to the main control machine via a network cable; and the monitoring switch communicates with the switch via an optical fiber; the monitoring switch is connected to communicate with the user monitoring terminal;

[0034] The sea surface floating platform performs data transmission with the shore station server via the monitoring switch;

[0035] The main control machine is connected to the watertight joint via a cable;

[0036] The main control machine is connected to the power distribution system via a cable.

[0037] In one embodiment, the hydrophone and split-beam sonar are connected to the seabed central node via an RJ45 Ethernet port;

[0038] The submarine central node and the watertight joint, as well as the watertight joint and the main control machine are connected by a composite Combo interface;

[0039] The main control machine is connected to the switch via an RJ45 Ethernet port, and the switch is connected to the monitoring switch via an optical fiber SPF interface;

[0040] The input interface of the power distribution system is an AC plug, and the output is a UPS plug; the power distribution system is connected to the watertight joint;

[0041] The monitoring switch is connected to the user monitoring terminal via an RJ45 Ethernet port; the monitoring switch is connected to the shore station server via an RS232 serial port.

[0042] In one embodiment, the sea surface floating platform includes columns and double-layer bearing plates;

[0043] There are three columns, and the three columns constitute a platform support structure;

[0044] The double-layer bearing plate is arranged on the top of the three columns;

[0045] The power distribution systems are evenly arranged on the double-layer supporting plate, and each power distribution system is provided with an identification mark, and is connected to the corresponding submarine data center cabin through each identification mark.

[0046] In one of the embodiments, a plurality of the submarine data center cabins are provided, and each of the submarine data center cabins is evenly distributed around the sea surface floating platform and is connected to the sea surface floating platform.

[0047] The above-mentioned energy consumption optimization method and system based on submarine data center environmental monitoring provide electric energy by setting up a power distribution system on the floating platform on the sea surface. The underwater mobile nodes in the hydroacoustic network are clustered through sound wave transmission to balance the node energy consumption. In the clustering process, an energy consumption balance optimization clustering algorithm based on game theory is used to perform non-cooperative game clustering to balance the energy consumption of each underwater mobile node, thereby ensuring the continuity of data monitoring of the submarine data center. BRIEF DESCRIPTION OF THE DRAWINGS

[0048] Figure 1 This is an application environment diagram of an energy consumption optimization method based on submarine data center environment monitoring in one embodiment;

[0049] Figure 2 It is a flowchart of an energy consumption optimization method based on submarine data center environment monitoring in one embodiment;

[0050] Figure 3 is a schematic diagram of a simulation scene graph in one embodiment;

[0051] Figure 4 A schematic diagram of a process flow of a GTCA algorithm for energy consumption balance optimization clustering based on game theory in one embodiment;

[0052] Figure 5 It is a structural schematic diagram of an energy consumption optimization system based on submarine data center environment monitoring in one embodiment;

[0053] Figure 6 A schematic diagram of a system networking interface of an energy consumption optimization system based on submarine data center environmental monitoring in one embodiment;

[0054] Figure 7 This is a schematic diagram of the structure of the sea surface floating platform 112 in one embodiment;

[0055] Figure 8 Schematic diagram for comparing the performance of different algorithms in terms of network lifetime;

[0056] Fig. 9 The bar chart shows the number of simulation rounds corresponding to different node death ratios;

[0057] Fig.10 Schematic diagram of the change in the number of simulation rounds for the average remaining energy of nodes;

[0058] Fig.11 A comparative diagram of data packets received by a sink node. DETAILED DESCRIPTION

[0059] In order to make the purpose, technical solution and advantages of the present application more clearly understood, the present application is further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present application and are not used to limit the present application.

[0060] The energy consumption optimization method based on submarine data center environment monitoring provided in the embodiment of the present application can be applied to Figure 1 In the application environment shown. Figure 1 As shown, the application environment includes a shore station monitoring platform 110, a sea surface floating platform 112, a submarine data center cabin 120, a submarine central node 130, and an underwater mobile node 140; wherein the shore station monitoring platform 110 is wirelessly connected and communicated with the sea surface floating platform 112, a power distribution system is arranged on the sea surface floating platform 112, the power distribution system is connected with the submarine data center cabin 120 through an underwater cable, and the submarine data center cabin 120 is connected and communicated with the submarine central node 130 through a cable; a plurality of underwater mobile nodes 140 are arranged, and information is transmitted between each underwater mobile node 140 through sound waves, and information is transmitted between the submarine central node 130 and each underwater mobile node 140 through sound waves.

[0061] In one embodiment, Figure 2 As shown, a method for optimizing energy consumption based on submarine data center environment monitoring is provided, comprising the following steps:

[0062] Step 202: The seabed central node converts the energy-optimized electrical signal into an acoustic signal through the split-beam sonar, wherein the acoustic signal contains an information packet consisting of the positioning information and node ID information of each underwater mobile node; and broadcasts the information packet to each underwater mobile node within the communication area of ​​the seabed central node.

[0063] There can be multiple submarine central nodes, distributed at locations on the seabed where submarine environmental data needs to be collected. The function of the submarine central node is to monitor and collect submarine data information. Among them, the acoustic signal contains information such as the location and node ID of each underwater mobile node. The submarine central node can control each underwater mobile node through the positioning information and node ID information in the information packet of the acoustic signal.

[0064] In one embodiment, a provided energy consumption optimization method based on submarine data center environmental monitoring may also include a process of dividing cluster head nodes, and the specific process includes: in the communication area corresponding to the submarine central node, each underwater mobile node is divided into ordinary member nodes and cluster head nodes; the ordinary member nodes communicate with the cluster head nodes by acoustic waves, and the cluster head nodes transmit information to the submarine central node through a multi-hop manner with other cluster head nodes as relays.

[0065] Specifically, in this embodiment, the submarine central node can first broadcast a notification of starting clustering to each underwater mobile node in its communication area. Each underwater mobile node that receives the information is clustered into a cluster through an energy consumption balance optimization clustering algorithm based on game theory. In the clustered cluster, ordinary member nodes only communicate with the cluster head node. In addition to communicating with ordinary member nodes in the cluster, the cluster head node also transmits the data information it receives and integrates through multi-hop means and uses other cluster head nodes as relays, and finally transmits it to the submarine central node.

[0066] A split-beam sonar is installed on the central node on the seabed, which can convert electrical signals into sound signals and then broadcast them to each underwater mobile node.

[0067] In step 204, each underwater mobile node performs non-cooperative game clustering according to the broadcast information packets using an energy consumption balance optimization clustering algorithm based on game theory to achieve energy balance among each underwater mobile node, and collects seabed environmental data through each underwater mobile node after energy balance.

[0068] In one embodiment, a provided energy consumption optimization method based on submarine data center environmental monitoring may also include a clustering and energy consumption optimization process of submarine central nodes and underwater mobile nodes. The specific process may include: constructing an underwater acoustic clustering network system model; establishing an underwater channel model based on the underwater acoustic clustering network system model; according to the underwater channel model, calculating the channel correlation distance between each ordinary member node and the cluster head node based on the underwater channel conditions, and determining the channel correlation distance measurement; based on the channel correlation distance measurement, calculating the flow weight generated by each ordinary member node in the cluster to the cluster head node, and calculating the total weight of the cluster head node; calculating the energy consumption of the ordinary member nodes and the cluster head nodes based on the underwater channel model, and establishing an energy consumption model.

[0069] Among them, the channel correlation distance between the ordinary member node and the cluster head node can be used to represent the relative distance after adding the channel information and channel conditions, and also includes the actual distance between the two nodes. Specifically, in the central node area of ​​the seabed, a hydroacoustic clustering network system model is constructed, and the ns-3 simulator is used to set specific scenarios such as Figure 3As shown in the figure, the simulation only considers the nodes randomly deployed in the 6*6*6 3D cube area. The number of submarine central nodes corresponding to the data cabins of the three data centers is also 3. The total number of ordinary nodes in the network is 30 to 50, and each node has its own location information and unique ID. Supported by the design of the water power distribution system, the submarine central node is a node that is not energy-restricted. Assuming that the weight factor α of the channel correlation distance metric is 0.6, the adjustable range of the submarine central node traffic weight is θ∈(0,1), the length of the control packet is 180 bits, and the length of the data packet itself is 1024 bits. The transmission power can be adjusted according to the communication distance requirements. The single run duration of the simulation is 15000 seconds.

[0070] After establishing the simulation scenario of the underwater acoustic clustering network system model, each underwater mobile node uses the energy consumption balance optimization clustering algorithm based on game theory to perform non-cooperative game clustering. The specific process is as follows: Figure 4 Specifically, it is necessary to first establish an underwater channel model and distance measurement:

[0071] The attenuation of the underwater acoustic channel caused by underwater channel noise can be expressed as: A(d,f)=d ε [a(f)] d ; where the variable d represents the distance between any two nodes, ε represents the water sound propagation coefficient, and the ocean absorption coefficient a(f) can be expressed as: The channel gain can be expressed as:

[0072] The distance and channel status of each common member node to the cluster head (CH) node are calculated, and the compromise between the two is used as the distance metric. Specifically, the channel of the i-th common member node can be expressed as h i =[h i1 ,h i2 ,…h iL ], then the autocorrelation matrix of common member node i can be expressed as R HH =E{HH H}, by eigendecomposing the autocorrelation matrix, R HH It can be expressed as: R ii V i =ΛV i ; Among them, R ii represents the autocorrelation matrix, V i represents the moving speed of node i, Λ represents the adjustment parameter, if the eigenvalue is regarded as a coefficient, the multipath channel information can be expressed by the eigenvector R i It is expressed as: The channel correlation between common member node i and CH can be expressed as:

[0073] Next, the actual distance d from the ordinary member node i to the cluster head node CH can be calculated i,CH for: Among them, n i -CH m Represents a common member node n i With cluster head node CH m Based on this, the distance metric that combines the actual distance from the common member node to the CH and the channel status is designed as: i,CH =αd i,CH +(1-α)(-E i,CH ), where α∈(0,1) is the weight factor, 1-α is the weight coefficient, -E i,CH is the channel correlation parameter, and any node in the network can be assigned to the cluster with the smallest D value from other nodes.

[0074] When performing node traffic analysis, we can assume that the traffic of the i-th node is x(i), and each node has a different impact on the CH node; assuming that the node traffic weight coefficient is θ∈(0,1), if the distance metric D between nodes is considered, the comprehensive weight of the ordinary member node i on the CH node is: The total weight generated by summing the traffic weight generated by each ordinary member node in the cluster to the cluster head and the weight of the CH itself can be used as the weight of the CH node, denoted as W:

[0075] Next, an energy consumption model can be established. The energy consumption of an underwater mobile node sending a data packet can be expressed as: E sent (l,d)=P*A(d,f)*T; where P is the receiving power of the underwater mobile node, T is the sending delay of the underwater mobile node; W i is the flow weight when the underwater mobile node i is the cluster head, then the energy consumption received by the underwater mobile node i can be expressed as: E rec =W i E1; Similarly, the energy consumed by fusing data when the underwater mobile node i is used as the cluster head can be expressed as: E integ =W i E2; The energy consumption of underwater mobile node i forwarding data can be expressed as: E forward =W i E3+ηDE4; where η is the reduction adjustment coefficient, which is used to adjust the energy consumption change, and the ordinary member node only has the energy consumption of forwarding data, specifically:

[0076] In one embodiment, a provided energy consumption optimization method based on submarine data center environmental monitoring may also include a process of constructing a node game model, the specific process including: defining each underwater mobile node as a set of competing participants, defining a strategy set for the current game of each underwater mobile node, and defining a set of profit functions for the game nodes; determining the profit function corresponding to each underwater mobile node when it selects different game strategies, and calculating the cost and profit based on the energy consumption model according to the profit function to construct a node game model.

[0077] In this embodiment, the underwater mobile nodes can be defined as a set of competition participants: N = {N1, N2, ..., N n}, the strategy set of the underwater mobile node at the current moment is: S = {S1, S2, ..., S n}, the set of game node profit functions is expressed as: U = {U1, U2, ..., U n}.

[0078] When underwater mobile node i selects strategy S i =CH, its profit function is: Where a>0 is a positive correlation coefficient, C i For cost, is the remaining energy of node i. According to the energy consumption model, the cost C i It can be further expressed as: C i =W i E1+W i E2+E forward (W i ,D)=W i ((E1+E2+E3)+ηDE4); If the node selects an ordinary member node, since ordinary member nodes only consume energy when forwarding data, the benefit of ordinary member node i can be expressed as: Obviously, when the remaining energy of ordinary member node i is the same, the cost of choosing the ordinary member node strategy is much less than the cost of choosing the cluster head node CH, and the benefit is also much greater than the benefit of choosing CH. Therefore, it is necessary to give a certain penalty to the ordinary member node that chooses the NCH strategy in order to encourage more nodes to compete for the cluster head. The penalty r i It can be specifically expressed as: After punishing ordinary member nodes, their benefits are: in, is the energy of the node with the largest remaining energy among the neighboring nodes of ordinary member node i.

[0079] It can be seen that when the residual energy of ordinary member node i is closer to the largest residual energy among neighboring nodes, the ratio of the two The closer it is to 1, the greater the penalty for ordinary member node i. At this time, ordinary member node i will be more inclined to choose the strategy of becoming a CH node in order to obtain greater benefits for itself. i The role of is to make the node with the largest remaining energy in the cluster be elected as the cluster head with the greatest probability during the game.

[0080] Therefore, in a round of game, the node with greater energy is more likely to become the cluster head, thereby obtaining the maximum benefit for itself. The node with smaller energy will have a smaller penalty value r in the game. i is smaller, at this time, the benefit of choosing the NCH strategy is greater. Finally, nodes with different energies reach a balance in the game process with each other. After a certain period of time, the energy of the node that originally chose to adopt the CH strategy drops rapidly due to the excessive load. Other ordinary nodes only send data, and the long-term low energy consumption causes the energy of a certain NCH node with the largest residual energy to begin to be greater than the previous CH, thus replacing the original cluster head and becoming the new cluster head. Through the continuous cycle of this process, the energy consumption of the entire cluster can be balanced.

[0081] In step 206, each underwater mobile node transmits the collected seabed environmental data sound to the seabed central node, converts the seabed environmental data sound signal into an electrical signal through the hydrophone on the seabed central node, compresses and encodes the seabed environmental data and transmits it to the main control computer in the seabed data center cabin through a watertight joint, pushes it to the sea surface floating platform through the main control computer, and finally transmits it to the monitoring switch on the shore station monitoring platform.

[0082] Step 208, the shore station monitoring platform is connected to the sea surface floating platform, and a power distribution system is set on the supporting plate of the sea surface floating platform to provide uninterrupted power for the submarine data center cabin.

[0083] Step 210: If the shore monitoring platform receives a control instruction sent from the user monitoring terminal and sends a seabed monitoring task to the seabed data center cabin, the seabed data center cabin processes the seabed environmental data and pushes it to the user monitoring terminal.

[0084] In this embodiment, an energy consumption optimization method based on environmental monitoring of a submarine data center is provided. A power distribution system is set on a supporting plate of a floating platform on the sea surface to provide electric energy. Each underwater mobile node in the hydroacoustic network is clustered through acoustic wave transmission to balance the node energy consumption. In the clustering process, an energy consumption balance optimization clustering algorithm based on game theory is used to perform non-cooperative game clustering to balance the energy consumption of each underwater mobile node, thereby ensuring the continuity of data monitoring of the submarine data center.

[0085] It should be understood that, although the various steps in the above-mentioned flow chart are displayed in sequence according to the indication of the arrows, these steps are not necessarily executed in sequence according to the order indicated by the arrows. Unless there is a clear explanation in this article, the execution of these steps is not strictly limited in order, and these steps can be executed in other orders. Moreover, at least a part of the steps in the above-mentioned flow chart may include a plurality of sub-steps or a plurality of stages, and these sub-steps or stages are not necessarily executed at the same time, but can be executed at different times, and the execution order of these sub-steps or stages is not necessarily to be carried out in sequence, but can be executed in turn or alternately with other steps or at least a part of the sub-steps or stages of other steps.

[0086] In one embodiment, Figure 1 As shown, an energy consumption optimization system based on submarine data center environmental monitoring is provided, including: a shore station monitoring platform 110, a submarine data center cabin 120, a submarine central node 130, and an underwater mobile node 140, wherein:

[0087] The shore station monitoring platform 110 is connected to the sea surface floating platform 112. The sea surface floating platform 112 is provided with a power distribution system on its bearing plate, which is connected to the submarine data center cabin 120 through an underwater cable to provide uninterrupted power to the submarine data center cabin 120.

[0088] The submarine data center cabin 120 is connected to each submarine central node 130 and receives submarine monitoring information transmitted from each submarine central node 130;

[0089] Each submarine central node 130 is used to broadcast a clustering notification to each underwater mobile node 140 in the communication area corresponding to the submarine central node 130, and notify each underwater mobile node 140 to adopt an energy consumption balance optimization clustering algorithm based on game theory to perform non-cooperative game clustering;

[0090] The seabed central node 130 is connected to a hydrophone and a split-beam sonar. The hydrophone is used to receive the acoustic signals collected by the underwater mobile nodes and convert them into electrical signals for transmission to the seabed central node 130; the split-beam sonar is used to convert the electrical signals emitted by the seabed central node 130 into acoustic signals and broadcast them to the underwater mobile nodes 140.

[0091] In one embodiment, a digital-to-analog converter (ADC) is built into the submarine central node, which can first convert the collected analog signal data into digital signals for subsequent data processing and analysis, and then compress and encode the converted data, and connect it to the watertight connector set on the bulkhead of the submarine data center through the submarine network cable. The watertight connector is connected to the main control machine in the submarine data center cabin through a composite cable of signal and cable. The main control machine first parses the collected data for communication protocol, and then uses two interfaces, one end of the interface is connected to the power distribution system matching the corresponding cabin number on the sea surface floating platform, and the other end of the interface is connected to the switch in the submarine data center cabin through the network cable, and the parsed digital signal data is converted into an optical signal through the switch, and then output by optical fiber, and the data is pushed to the monitoring switch of the sea surface floating platform. The main control machine is connected to one end of the cable interface, and the power distribution system corresponding to the data cabin number on the sea surface floating platform load board is powered. The main control machine in the data center cabin n is powered by the power distribution system n, and the main control machine in the submarine data center cabin 1 is powered by the power distribution system 1.

[0092] Finally, the optical signal data uploaded to the monitoring switch of the sea surface floating platform can be converted into digital signals through appropriate chips or circuits, and finally transmitted to the shore server at the shore monitoring platform through the network cable. When the user monitoring terminal interface of the sea surface floating platform receives the user's control, query or configuration instructions, and sends a request task such as seabed monitoring to the shore server, the shore server will store, integrate and process the seabed environment information collected in the above process, and push the processed valid data required by the user to the user monitoring terminal. The push process can be implemented by using reliable protocols such as TCP / IP, or real-time network communication protocols such as UDP, according to the characteristics of the transmitted data itself. According to the response results of the user terminal, the server can further perform operations such as monitoring screen display and alarm information processing.

[0093] like Figure 1 , Figure 5 As shown, in one embodiment, an energy consumption optimization system based on submarine data center environmental monitoring may further include a shore station server 150 and a user monitoring terminal 160;

[0094] Each submarine central node 130 is provided with a digital-to-analog converter, which converts the received submarine monitoring information into a digital signal, and compresses and encodes the digital signal and transmits it to the submarine data center cabin 120 through a watertight joint;

[0095] The main control computer in the submarine data center cabin 120 performs communication protocol analysis on the transmitted data, and pushes the analyzed data to the sea surface floating platform 112 respectively;

[0096] The sea surface floating platform 112 transmits the parsed data to the shore station server 150 at the shore station monitoring platform 110 , and the shore station server 150 pushes it to the user monitoring terminal 160 .

[0097] In one embodiment, a monitoring switch is provided at the shore station monitoring platform, and a switch is provided in the submarine data center cabin. The switch is connected to the main control machine through a network cable; the monitoring switch and the switch are connected and communicated through optical fiber; the monitoring switch is connected and communicated with the user monitoring terminal; the surface floating platform transmits data with the shore station server through the monitoring switch; the main control machine is connected to the watertight joint through a cable; and the main control machine is connected to the power distribution system through a cable.

[0098] like Figure 6 As shown, in one embodiment, the hydrophone and the split-beam sonar are connected to the submarine central node through the RJ45 Ethernet port; the submarine central node and the watertight joint, and the watertight joint and the main control machine are connected by a composite Combo interface; the main control machine is connected to the switch through the RJ45 Ethernet port, and the switch is connected to the monitoring switch through the optical fiber SPF interface; the input interface of the power distribution system is an AC plug, and the output is a UPS plug; the power distribution system is to the watertight joint; the monitoring switch is connected to the user monitoring terminal through the RJ45 Ethernet port; the monitoring switch is connected to the shore station server through the RS232 serial port.

[0099] In this embodiment, specifically, the networking interfaces of each module of the submarine data center environment monitoring system are:

[0100] The interfaces between the hydrophone and the classification wave velocity sonar and the seabed central node are both RJ45 Ethernet ports;

[0101] The interfaces between the submarine central node and the watertight connector, and between the watertight connector and the main control machine are all composite Combo interfaces for composite transmission of electronic signals and electrical signals. The interface from the main control machine to the switch in the submarine data center cabin is an RJ45 Ethernet port, and the output interface from the switch in the submarine data center cabin to the monitoring switch is an optical fiber SPF interface.

[0102] The outlet of the power distribution system is a UPS plug, and the power input interface from the power distribution system to the main control machine is an AC plug;

[0103] The input interface of the power distribution system is AC, the output is UPS plug, and the interface from the power distribution system to the watertight connector is AC plug;

[0104] The interface from the station monitoring switch to the user terminal is an RJ45 Ethernet port, and the interface from the monitoring switch to the server is an RS232 serial port.

[0105] In one embodiment, Figure 7 As shown, the sea surface floating platform 112 includes a column 114 and a double-layer bearing plate 116;

[0106] There are three columns 114, and the three columns 114 constitute the platform support structure;

[0107] The double-layer bearing plate 116 is arranged on top of the three columns 114;

[0108] The double-layer bearing plate 116 is evenly provided with various power distribution systems, and each power distribution system is provided with an identification mark, and is connected to the corresponding submarine data center cabin 120 through each identification mark.

[0109] In one embodiment, a plurality of submarine data center cabins are provided, and each submarine data center cabin is evenly distributed around the sea surface floating platform and is connected to the sea surface floating platform.

[0110] Specifically, Figure 7 As shown, the sea surface floating platform 112 is composed of three columns 114 and a double-layer bearing plate 116 located above the sea level. The three-column sea surface floating platform 112 support structure can reduce the impact of water flow and waves on the platform. The shore station monitoring platform is fixed to the first layer of the two-layer bearing plate 116. Both layers of the bearing plate 116 are equipped with multiple power distribution systems. Each power distribution system is marked with a corresponding data cabin number and is connected to the corresponding numbered submarine data center cabin 120 through an underwater cable. n submarine data center cabins 120 are arranged around the sea surface floating platform 112. The sea surface floating platform 112 can be anchored in different geographical locations to achieve environmental monitoring in a wider sea area.

[0111] By removing the power distribution system from the submarine data center cabin 120, the power supply system can provide uninterrupted and sufficient power to the main control machine in the submarine data center cabin 120 and the submarine central node connected to the watertight joint outside the cabin. So that the number of underwater mobile nodes in the submarine central node area and the equipment in the submarine data center cabin 120 is not limited. At the same time, the power distribution system is a vulnerable equipment and is placed on the surface platform 112 in the water for regular maintenance. It is placed in the submarine data center cabin 120, which is not only difficult to take out for a long time, but also difficult to repair when various connected devices fail. The submarine central node n connected to the bulkhead of the submarine data center cabin 120 can correspond one-to-one with the above-mentioned power distribution system n, and can be regarded as a wireless energy aggregation node. It is equipped with a camera to form a video resource for submarine monitoring information, and is connected to a hydrophone and a split-beam sonar. The hydrophone can receive the sound signal of the underwater mobile node, and then convert it into an electrical signal and transmit it to the submarine central node. The split-beam sonar can convert the electronic signal of the task instruction such as node clustering issued by the submarine central node into a sound signal and broadcast it to the underwater mobile node.

[0112] In this embodiment, the Figure 7The structural design shown in the figure can realize monitoring of different sea areas by moving the floating platform on the sea surface, avoiding the shortcomings of the traditional fixed submarine environmental monitoring center with fixed monitoring position and small monitoring range; on the other hand, the method of placing the power distribution system on the water-bearing part of the floating platform on the sea surface not only solves the problem of difficult maintenance of vulnerable equipment such as the power distribution system, but also makes the power supply of various equipment inside and outside the underwater data center cabin not limited by the number of equipment, and it is easy to realize the system upgrade and expansion of the system capacity of the submarine data center. Through layered collaboration between the modules, the monitoring of the environmental information of the submarine data center is better realized.

[0113] In one embodiment, in order to compare the performance of the energy consumption balance optimization clustering GTCA algorithm based on game theory in the energy consumption optimization method based on submarine data center environment monitoring provided in this application and the system in terms of network life cycle, as shown in FIG. Figure 8 As shown, compared with the other three algorithms, the GTCA algorithm proposed in this application has the latest occurrence time of the first node death. The first node death time of the LEACH, cDBR, GTC and GTCA algorithms is the 484th, 616th, 900th and 1000th rounds respectively, and the first node death time of the GTCA algorithm is 207%, 162% and 111% later than that of the LEACH, cDBR and GTC protocols respectively. Therefore, the GTCA algorithm can effectively reduce network energy consumption.

[0114] like Fig. 9 As shown in the figure, the number of simulation rounds of the four algorithms is compared when the node death ratio is 1%, 30%, 50%, and 80% respectively. The larger the number of simulation rounds experienced when the node dies, the longer the life cycle of the network is under the GTCA algorithm. Therefore, under different conditions of the number of node deaths, the life cycle of the underwater acoustic network of the GTCA algorithm is much longer than that of the other three.

[0115] like Fig.10As shown, with the increase of the number of simulation rounds, the average residual energy of the GTCA and GTC algorithms decreases much slower than that of the other two algorithms, and the GTCA algorithm proposed in this application decreases the slowest. This is because the algorithm takes the correlation of the underwater channel into account in the distance measurement between cluster nodes, and further integrates the distance measurement and the weight of the node flow into the clustering game model, and then replaces the nodes with larger residual energy with new CH nodes through the penalty mechanism, thereby greatly reducing energy consumption and obtaining the slowest energy consumption decrease rate. Although the GTC algorithm uses the Nash equilibrium of the game between nodes as the standard for CH selection and adopts a reward mechanism to obtain the optimal solution of the Nash equilibrium, it rarely considers the impact of complex underwater channel information on clustering, which results in its average energy consumption decreasing slower than the LEACH and cDBR algorithms, but faster than the algorithm proposed in this application. Among the two algorithms, LEACH and cDBR, which have faster average energy consumption reduction rates, the average energy consumption of the cDBR algorithm is better than that of the LEACH scheme, which only relies on random numbers to obtain CHs and has the fastest average energy consumption reduction rate, because it considers the CH degree, residual energy and actual distance between nodes.

[0116] like Fig.11 As shown in the figure, the GTCA algorithm makes the sink node receive the largest number of data packets, followed by GTC, cDBR and LEACH. Moreover, as the network load increases, the central node of the GTCA algorithm can receive more data packets than the other three algorithms. This is because the algorithm adds the node's traffic weight to its energy consumption model, and the nodes in the cluster can rotate as CHs through a penalty mechanism and competitive game, thereby improving the overall life of the network and obtaining a higher packet reception rate than the other three algorithms.

[0117] Those skilled in the art can understand that some of the processes in the above-mentioned embodiments can be completed by instructing the relevant hardware through a computer program, and the computer program can be stored in a non-volatile computer-readable storage medium. When the computer program is executed, it can include the processes of the embodiments of the above-mentioned methods. Among them, any reference to memory, storage, database or other media used in the embodiments provided in this application can include non-volatile and / or volatile memory. Non-volatile memory can include read-only memory (ROM), programmable ROM (PROM), electrically programmable ROM (EPROM), electrically erasable programmable ROM (EEPROM) or flash memory. Volatile memory can include random access memory (RAM) or external cache memory. As an illustration and not limitation, RAM is available in many forms, such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), double data rate SDRAM (DDRSDRAM), enhanced SDRAM (ESDRAM), synchronous link (Synchlink) DRAM (SLDRAM), memory bus (Rambus) direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and memory bus dynamic RAM (RDRAM).

[0118] The technical features of the above embodiments may be combined arbitrarily. To make the description concise, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0119] The above-mentioned embodiments only express several implementation methods of the present application, and the descriptions thereof are relatively specific and detailed, but they cannot be understood as limiting the scope of the invention patent. It should be pointed out that, for a person of ordinary skill in the art, several variations and improvements can be made without departing from the concept of the present application, and these all belong to the protection scope of the present application. Therefore, the protection scope of the patent of the present application shall be subject to the attached claims.

Claims

1. An energy consumption optimization method based on submarine data center environmental monitoring, characterized in that: The method comprises: The submarine central node converts the energy consumption optimization electrical signal into an acoustic signal through the split beam sonar, wherein the acoustic signal contains an information packet consisting of the positioning information and node ID information of each underwater mobile node; and broadcasts the information packet to each underwater mobile node in the communication area of ​​the submarine central node; Each underwater mobile node uses a game theory-based energy consumption balance optimization clustering algorithm to perform non-cooperative game clustering according to the broadcast information packet, so as to achieve energy balance among each underwater mobile node, and collect seabed environment data through each underwater mobile node after energy balance; Each of the underwater mobile nodes transmits the collected seabed environmental data to the seabed central node, converts the seabed environmental data acoustic signal into an electrical signal through the hydrophone on the seabed central node, compresses and encodes the seabed environmental data, and transmits it to the main control computer in the seabed data center cabin through a watertight joint, pushes it to the sea surface floating platform through the main control computer, and finally transmits it to the monitoring switch on the shore station monitoring platform; The shore station monitoring platform is connected to the sea surface floating platform, and a power distribution system is arranged on the bearing plate of the sea surface floating platform to provide uninterrupted power for the submarine data center cabin; If the shore station monitoring platform receives a control instruction sent from the user monitoring terminal and sends a seabed monitoring task to the seabed data center cabin, the seabed data center cabin processes the seabed environmental data and pushes it to the user monitoring terminal.

2. The energy consumption optimization method based on submarine data center environmental monitoring according to claim 1 is characterized in that: The method further comprises: In the communication area corresponding to the seabed central node, each of the underwater mobile nodes is divided into ordinary member nodes and cluster head nodes; The common member nodes communicate with the cluster head nodes by acoustic waves, and the cluster head nodes transmit information to the seabed central node through multi-hop mode with other cluster head nodes as relays.

3. The energy consumption optimization method based on submarine data center environmental monitoring according to claim 2 is characterized in that: The method further comprises: Construct an underwater acoustic clustering network system model; Based on the underwater acoustic clustering network system model, an underwater channel model is established; According to the underwater channel model, the channel correlation distance between each of the ordinary member nodes and the cluster head node is calculated based on the underwater channel condition to determine the channel correlation distance metric; Based on the channel correlation distance metric, the flow weight generated by each of the ordinary member nodes in the cluster to the cluster head node is calculated, and the total weight of the cluster head node is calculated; The energy consumption of the common member nodes and the cluster head nodes is calculated based on the underwater channel model, and an energy consumption model is established.

4. The energy consumption optimization method based on submarine data center environmental monitoring according to claim 3 is characterized in that: The method further comprises: Defining each of the underwater mobile nodes as a set of competition participants, defining a set of strategies for the current game of each of the underwater mobile nodes, and defining a set of revenue functions of the game nodes; Determine the corresponding benefit function when each of the underwater mobile nodes selects different game strategies, calculate the cost and benefit based on the energy consumption model according to the benefit function, and construct a node game model.

5. An energy consumption optimization system based on submarine data center environmental monitoring, characterized in that: The system includes: a shore station monitoring platform, a submarine data center cabin, a submarine central node, and an underwater mobile node, wherein: The shore station monitoring platform is connected to a sea surface floating platform, and a power distribution system is arranged on the bearing plate of the sea surface floating platform, which is connected to the seabed data center cabin through an underwater cable to provide uninterrupted power to the seabed data center cabin; The submarine data center cabin is connected to each of the submarine central nodes and receives submarine monitoring information transmitted from each of the submarine central nodes; Each of the submarine central nodes is used to broadcast a clustering notification to each of the underwater mobile nodes in the communication area corresponding to the submarine central node, notifying each of the underwater mobile nodes to adopt an energy consumption balance optimization clustering algorithm based on game theory to perform non-cooperative game clustering; The seabed central node is connected to a hydrophone and a split-beam sonar. The hydrophone is used to receive the acoustic signal collected by the underwater mobile node and convert it into an electrical signal for transmission to the seabed central node; the split-beam sonar is used to convert the electrical signal emitted by the seabed central node into an acoustic signal and broadcast it to the underwater mobile node.

6. The energy consumption optimization system based on submarine data center environmental monitoring according to claim 5 is characterized in that: The system also includes a shore station server and a user monitoring terminal; Each of the submarine central nodes is provided with a digital-to-analog converter, which converts the received submarine monitoring information into a digital signal, and compresses and encodes the digital signal before transmitting it to the submarine data center cabin through a watertight joint; The main control computer in the submarine data center cabin performs communication protocol analysis on the transmitted data, and pushes the analyzed data to the sea surface floating platform respectively; The sea surface floating platform transmits the parsed data to the shore station server at the shore station monitoring platform, and the shore station server pushes it to the user monitoring terminal.

7. The energy consumption optimization system based on submarine data center environmental monitoring according to claim 6 is characterized in that: A monitoring switch is provided at the shore station monitoring platform, a switch is provided in the submarine data center cabin, the switch is connected to the main control machine via a network cable; and the monitoring switch is connected and communicated with the switch via an optical fiber; the monitoring switch is connected and communicated with the user monitoring terminal; The sea surface floating platform performs data transmission with the shore station server via the monitoring switch; The main control machine is connected to the watertight joint via a cable; The main control machine is connected to the power distribution system via a cable.

8. The energy consumption optimization system based on submarine data center environmental monitoring according to claim 7 is characterized in that: The hydrophone and split-beam sonar are connected to the seabed central node via an RJ45 Ethernet port; The submarine central node and the watertight joint, as well as the watertight joint and the main control machine are connected by a composite Combo interface; The main control machine is connected to the switch via an RJ45 Ethernet port, and the switch is connected to the monitoring switch via an optical fiber SPF interface; The input interface of the power distribution system is an AC plug, and the output is a UPS plug; the power distribution system is connected to the watertight joint; The monitoring switch is connected to the user monitoring terminal via an RJ45 Ethernet port; the monitoring switch is connected to the shore station server via an RS232 serial port.

9. The energy consumption optimization system based on submarine data center environmental monitoring according to claim 5 is characterized in that: The sea surface floating platform comprises columns and double-layer bearing plates; There are three columns, and the three columns constitute a platform support structure; The double-layer bearing plate is arranged on the top of the three columns; The power distribution systems are evenly arranged on the double-layer supporting plate, and each power distribution system is provided with an identification mark, and is connected to the corresponding submarine data center cabin through each identification mark.

10. The energy consumption optimization system based on submarine data center environmental monitoring according to claim 5, characterized in that: There are a plurality of submarine data center cabins, and each of the submarine data center cabins is evenly distributed around the sea surface floating platform and is connected to the sea surface floating platform.

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