A fully directional hybrid topology control method for mobile ad hoc networks

Abstract

The present invention discloses a fully directional hybrid topology control method for mobile self-organizing networks, which mainly solves the problems of low network connectivity and poor robustness when using a single antenna for topology control in the existing technology. Its implementation scheme is: 1) nodes interact with their node IDs and location information to establish a local K-connected subgraph; 2) each node calculates the minimum power of the local K-connected subgraph; 3) each node constructs a local topology subgraph based on the calculated minimum power; 4) each node interacts with the local topology subgraph and deletes the unidirectional edges therein; 5) the node solves the minimum power required for the local topology subgraph after deleting the unidirectional edges, and obtains the power allocation result and the direction of the directional antenna. Compared with the existing topology control method, the present invention improves the connectivity and robustness of the network topology, and on this basis reduces the transmission power of the node and the number of channels occupied by the network, and can be used in mobile self-organizing networks.

Description

Technical Field

[0001] The present invention belongs to the technical field of wireless communications, and further relates to an omnidirectional hybrid topology control method for enhancing network connectivity, which can be used in a mobile self-organizing network. Background Art

[0002] For mobile ad hoc networks, topological connectivity is the physical foundation for inter-node communication. To ensure network connectivity, numerous topology control methods have been proposed. These methods improve the connectivity of mobile ad hoc networks by adjusting node power or channels and adding redundant links to the topology. However, existing topology control technologies primarily operate based on a single antenna transmission mode, using either directional or omnidirectional antennas to transmit data, without considering combining the two. If nodes transmit signals using only omnidirectional antennas, connectivity in the mobile ad hoc network is difficult to ensure due to the short communication range. Furthermore, omnidirectional antennas can cause severe interference to surrounding nodes when transmitting signals, leading to an excessive number of nodes interfering with each other within the network, an increase in the number of orthogonal channels occupied, and a low channel reuse rate. If nodes transmit data using only directional antennas, the limited number of directional antenna beams means that the number of neighbors a network node can connect to is limited, resulting in poor network connectivity and robustness. The network can easily be fragmented into isolated subsets, and nodes in different subsets cannot communicate properly. Therefore, studying the joint transmission technology of omnidirectional antennas and directional antennas is of great significance to ensuring the performance of mobile ad hoc networks.

[0003] Ning Li et al. proposed the K-point connectivity algorithm FLSS in their paper "Localized fault-tolerant topology control in wireless ad hoc networks." Its main implementation steps are: (1) Nodes exchange information with neighboring nodes at maximum power; (2) Nodes use the information obtained from the interactions to construct a local K-point connected subgraph; (3) Nodes determine logical neighboring nodes and adjust their own transmission power. This method uses only omnidirectional antennas to transmit signals and allows any K-1 nodes in the network to fail. The prerequisite for the network to remain connected is that the network's maximum power topology must meet the K-point connectivity requirements. When the node density is low, the network's maximum power topology cannot meet the K-point connectivity requirements, and the network's connectivity cannot be guaranteed.

[0004] In her master's thesis, "Research on Topology Control Technology of Distributed Wireless Networks" (Xi'an University of Electronic Science and Technology, April 2018), Chen Wen proposed a minimum channel allocation algorithm. Its main implementation steps are: (1) Before allocating channels, a node first detects whether nodes with a higher conflict degree than its own have completed channel allocation; (2) If a node finds that a node with a higher conflict degree than its own has not completed channel allocation, it rechecks after a period of time; (3) When a node finds that all nodes with a higher conflict degree than its own have completed channel allocation, it selects an unoccupied channel and broadcasts the message. Although this method only uses omnidirectional antennas to send signals and can achieve conflict-free nodes within the network, it does not consider reducing the number of conflicting neighbors of the node, resulting in a large number of channels being occupied in the network.

[0005] Umesh Kumar et al. proposed a topology control method based on directional antennas in their paper “A Topology Control Approach to Using Directional Antennas in Wireless Mesh Networks”. The main implementation steps are: (1) Generate any tree T based on the maximum power graph G, where the degree of tree T is d, and the set S represents the set of nodes in T with degrees d and d-1; (2) Obtain subtrees T1, ..., T from ST. r , if there is an edge between the two subtrees, then add the edge to the tree T and remove another suitable edge; (3) until there are no edges connecting the subtrees, and the algorithm ends. This method reduces the node degree of the network topology so that the node degree is no greater than the number of directional antennas, thereby meeting the requirement of using directional antennas to build the network topology. However, this method cannot guarantee that the node degree of the final generated topology will not be greater than the number of directional antennas, and cannot guarantee the connectivity requirements of the mobile ad hoc network. Summary of the Invention

[0006] The purpose of the present invention is to address the deficiencies of the above-mentioned existing technologies and provide a fully directional hybrid topology control method for mobile ad hoc networks to improve the connectivity and robustness of mobile ad hoc networks and reduce the transmission power of nodes and the number of channels occupied by the entire network.

[0007] The idea of ​​the present invention is: through the interaction of nodes' own node IDs and location information, nodes can obtain the local maximum power subgraph, and based on the local maximum power subgraph, a local topology subgraph is generated with the goal of maximizing network connectivity; through the interaction of nodes in the local topology subgraph, the unidirectional edges in the local topology subgraph are deleted; and the connectivity of the local topology subgraph is maintained by adjusting the power of the node antenna.

[0008] According to the above ideas, the implementation scheme of the present invention includes the following:

[0009] (1) Any node u in the mobile ad hoc network sends a Hello packet containing its own information at maximum power and receives Hello packets from other nodes to establish a local K-connected subgraph

[0010] (2) Node u on the local K-connected subgraph Solve the power and get Minimum power required

[0011]

[0012] in, is the neighbor set of node u, P i o is the power of node u using omnidirectional antenna to communicate with node i, P i d is the power of node u communicating with node i using directional antenna, a i Indicates the communication mode between node u and node i, a i = 0 means node u uses omnidirectional antenna to communicate with neighbor node i, a i =1 means node u communicates with neighbor node i using directional antenna;

[0013] (3) With its maximum power P max For comparison:

[0014] like Then execute (4),

[0015] Otherwise, let the local topological subgraph Execute (5);

[0016] (4) Node u generates a local topology subgraph with the goal of maximizing network connectivity. Execute (5);

[0017] (5) Node u interaction local topology subgraph delete The unidirectional links in the local generated subgraph S are obtained u ;

[0018] (6) Node u generates a local subgraph S u Perform power calculation to obtain the power distribution result and the direction of the directional antenna.

[0019] Compared with the prior art, the present invention has the following advantages:

[0020] First, the present invention uses omnidirectional antennas and directional antennas to jointly send information, taking advantage of the longer transmission distance of directional antennas and the wider propagation range of omnidirectional antennas, and generates a local topology subgraph with the goal of maximizing network connectivity. Compared with other methods, the present invention effectively improves the connectivity and robustness of the network.

[0021] Second, since the present invention provides a method for calculating the minimum required power for a given topology structure, by using directional antennas to communicate with farther nodes and using omnidirectional antennas to communicate with closer nodes, the present invention effectively reduces the power of nodes and the number of channels occupied by the entire network while ensuring network connectivity and robustness, compared with other comparison methods. BRIEF DESCRIPTION OF THE DRAWINGS

[0022] Figure 1 It is a general flow chart for realizing the present invention;

[0023] Figure 2 It is a sub-flowchart for generating a local topology subgraph in the present invention;

[0024] Figure 3 This is a simulation result diagram of the relationship between network connectivity and the number of nodes of the present invention;

[0025] Figure 4 is a simulation result diagram of the relationship between the average number of paths and the number of nodes of the present invention;

[0026] Figure 5 1 is a simulation result diagram of the relationship between the average transmission power of nodes and the number of nodes of the present invention;

[0027] Figure 6 This is a simulation result diagram of the relationship between the number of channels occupied by the entire network and the number of nodes of the present invention. DETAILED DESCRIPTION

[0028] The embodiments and effects of the present invention are further described in detail below with reference to the accompanying drawings.

[0029] The working scenario of this embodiment is a mobile ad hoc network with N nodes, where each node is equipped with an omnidirectional antenna and N A The total signal transmission power of the node is limited. Each node can act as a source node and a destination node, and can also provide a relay for other nodes to communicate.

[0030] Reference Figure 1 , the implementation steps of this example are as follows.

[0031] Step 1: Generate a local K-connected subgraph

[0032] (1.1) Any node u in the mobile ad hoc network concentrates all its power on a directional antenna and sends Hello packets to the surrounding space. After sending Hello packets in one area, node u adjusts the direction of the antenna and sends Hello packets to the next area until all areas have been sent. The Hello packets contain the ID and location information of node u.

[0033] (1.2) Node u receives the Hello packets sent by other nodes, extracts the information therein, and uses the FLSS algorithm to generate a local K-connected subgraph.

[0034] (1.2.1) Node u obtains the maximum power subgraph according to the node ID and location information in the Hello packets.

[0035] (1.2.2) Node u makes the local K-connected subgraph and sorts all the edges in the maximum power subgraph in ascending order of length.

[0036] (1.2.3) Node u traverses the edges in the maximum power subgraph in order, calculates the number m of disjoint paths between the two nodes of this edge, and compares the size of m with K:

[0037] If m < K, then add this edge to the local K-connected subgraph.

[0038] Otherwise, node u discards this edge.

[0039] Step 2: Solve the minimum power of the local K-connected subgraph. of the local K-connected subgraph.

[0040] (2.1) Node u first obtains the set of neighbor nodes according to the local K-connected subgraph and then calculates the minimum power P required to communicate with any neighbor node i using an omnidirectional antenna = βd i o = βd λ and the minimum power required to communicate with any neighbor node i using a directional antenna where β is the receiver sensitivity, d is the distance between node u and its neighbor i, λ is the path loss coefficient, and θ is the beam width of the directional antenna.

[0041] (2.2) Calculate the total power for node u to communicate with its neighbor nodes according to the results of (2.1).

[0042]

[0043]

[0044] a i ={0,1}.

[0045] Among them, N A is the number of directional antennas at node u, a i Indicates the communication mode between node u and node i, a i = 0 means node u uses omnidirectional antenna to communicate with neighbor node i, a i =1 indicates that node u communicates with neighbor node i using a directional antenna.

[0046] Step 3: Determine how node u generates the local graph.

[0047] Will With its maximum power P max For comparison:

[0048] like Then execute step 4.

[0049] Otherwise, let the local topology subgraph Go to step 5.

[0050] Step 4: Generate local topology subgraph

[0051] Reference Figure 2 , this step is specifically implemented as follows:

[0052] (4.1) Node u sets the target topology K0=K-1;

[0053] (4.2) Node u uses the FLSS algorithm to generate the basic topology of K0 connectivity according to Get its neighbor set Again Solve the power to get the minimum required power

[0054]

[0055] (4.3) The maximum power P of node u max For comparison:

[0056] like Then let K0=K0-1 for node u, Return (4.2);

[0057] like Then execute (4.4);

[0058] (4.4) Node u is the local topological subgraph get The set of neighbor nodes in as well as The set of neighbor nodes in

[0059] (4.5) Let the candidate neighbor set calculate The set of all subsets Pair Collection Any member of By local topological subgraph Add edges (u, v) and (v, u) to obtain alternative topological subgraphs where v is Any member node in ;

[0060] (4.6) Calculate the alternative topological subgraphs separately Corresponding minimum power Network connectivity and the average number of paths in the network

[0061] Calculate the minimum power using the same method as step 2

[0062] Calculating network connectivity in for The number of nodes in the largest connected subgraph, N is The total number of nodes in ;

[0063] Calculate the average number of paths in the network using the maximum flow algorithm

[0064] (4.7) In all cases where Alternative topological subgraphs of conditions Find the member with the greatest connectivity

[0065] (4.7.1) For any two members in the alternative topology subgraph and If any of the following three conditions are met, it is considered

[0066] ①

[0067] ②

[0068] ③

[0069] (4.7.2) Compare the size of all members of the candidate topology subgraph one by one according to the method of (4.7.1) and select the one with the best connectivity.

[0070] The largest member

[0071] (4.8) Let the local topological subgraph Go to step 5.

[0072] Step 5: Delete the one-way edges to obtain a symmetric local spanning subgraph.

[0073] Node u generates a local subgraph And with S u All neighbor nodes v interact in the local topology subgraph Determine whether the edge (u,v) belongs to both and

[0074] If so, node u retains the edge (u, v), and nodes u and v are neighbors.

[0075] If not, then node u deletes S u The unidirectional edge (u,v) in the symmetric local generated subgraph S is obtained u .

[0076] Step 6: Calculate the power allocation results and antenna directions.

[0077] (6.1) Node u first generates a subgraph S based on the local u Get the neighbor node set N u , and then calculate the minimum power required to communicate with any neighbor node j using an omnidirectional antenna and the minimum power required to communicate with any neighbor node j using a directional antenna

[0078] where β is the receiver sensitivity, d is the distance between node u and its neighbor i, λ is the path loss coefficient, θ is the beamwidth of the directional antenna, and j∈N u ;

[0079] (6.2) According to the result of (6.1), calculate the total power P of communication between node u and its neighbor nodes u :

[0080]

[0081]

[0082] a j ={0,1};

[0083] Among them, a j Indicates the communication mode between node u and node j, a j = 0 means node u uses omnidirectional antenna to communicate with neighbor node j, aj =1 means node u uses directional antenna to communicate with neighbor node j;

[0084] (6.3) Node u sets the power of the omnidirectional antenna to: to a j = 1, node u sets the power of the directional antenna to The direction of the directional antenna is adjusted to point to the direction of neighbor node j, completing the full directional hybrid topology control of the mobile ad hoc network.

[0085] The following is a further explanation of the effect of this example combined with simulation experiments:

[0086] 1. Simulation experiment conditions:

[0087] The application platform of the simulation experiment of the present invention is: the processor is a 64-core AMD Ryzen Threadripper 3990X64-bit CPU with a main frequency of 3.7GHz and a memory of 128GB.

[0088] The simulation experiment software platform of the present invention is: Windows 10 operating system, Matlab r2020a.

[0089] The network scenario of the simulation experiment of the present invention is that N network nodes are randomly and evenly distributed in a space of 2000m×2000m. Each node is equipped with an omnidirectional antenna and N A directional antennas, each of which can only track one neighboring node.

[0090] The simulation parameter settings are shown in Table 1.

[0091] Table 1 Simulation parameters

[0092] Maximum power 24dBm Receiver sensitivity -110dBm Beamwidth 30° Number of directional antennas 3 Number of nodes 10～100 Path loss factor 4 Region size 2000m×2000m K 3

[0093] 2. Simulation content and result analysis:

[0094] Simulation 1: In the above network scenario, the present invention, the existing method using omnidirectional antennas, the method using directional antennas, and a greedy omnidirectional hybrid method are used to control the network topology under different numbers of nodes. The connectivity of the network topology generated by the four methods is compared. The results are as follows: Figure 3 .

[0095] from Figure 3It can be seen that the present invention significantly outperforms the other three comparison methods in terms of network connectivity. When the number of network nodes is 20, the network connectivity of the present invention can reach 95.5%, and the network is close to being fully connected. The existing method using directional antennas and the greedy method have network connectivity of 78.9% and 74.1%, respectively, which can only keep most of the network nodes connected. The network connectivity of the existing omnidirectional antenna is only 40.7%, and the network nodes are less than half connected. This excellent effect of the present invention is due to the construction of a topological structure that maximizes network connectivity, which can effectively improve the network connectivity when the network is in a weak connection state.

[0096] Simulation 2: In the above network scenario, the present invention, the existing method using omnidirectional antennas, the method using directional antennas, and a greedy omnidirectional hybrid method are used to control the network topology under different numbers of nodes. The average number of network paths generated by the four methods is compared. The results are as follows: Figure 4 .

[0097] from Figure 4 As can be seen from the results, the present invention can better ensure network robustness than the other three comparison algorithms. When the number of nodes is 30, the average number of paths in the network of the present invention is 2.38, the average number of paths for the greedy method is 1.87, and the average number of paths for directional antennas and omnidirectional antennas is 0.91 and 0.69, respectively. The network of the present invention has the largest average number of paths and the best robustness. This shows that the maximizing network connectivity method proposed in the present invention can effectively increase the number of paths in the network, thereby improving the robustness of the network.

[0098] Simulation 3: In the above network scenario, the present invention, the existing method using omnidirectional antennas, the method using directional antennas, and a greedy omnidirectional hybrid method are used to control the network topology under different numbers of nodes. The average node transmission power generated by the four methods is compared. The results are as follows: Figure 5 .

[0099] from Figure 5 It can be seen that compared with the other three comparison methods, the present invention can reduce the transmission power of nodes on the basis of ensuring network connectivity and robustness. When the number of nodes is 100, the average transmission power of the nodes of the present invention is 13.95dBm, while the average transmission powers of the method using omnidirectional antennas and the greedy method are 20.41dBm and 19.49dBm respectively. The present invention effectively reduces the transmission power of nodes. Although the node transmission power of the method using directional antennas is the smallest, the network topology generated by this method has extremely poor robustness and cannot meet the robustness requirements of the network. The reason why the present invention can reduce the average power of nodes is that the present invention proposes a method for calculating the minimum required power for a given topology.

[0100] Simulation 4: In the above network scenario, the present invention, the existing method using omnidirectional antennas, the method using directional antennas, and a greedy omnidirectional hybrid method are used to control the network topology under different numbers of nodes. The number of channels occupied by the networks generated by the four methods is compared. The results are as follows: Figure 6 .

[0101] from Figure 6 It can be seen that compared with the other three comparison methods, the present invention can reduce the number of channels occupied by the network on the basis of ensuring network connectivity and robustness. When the number of nodes is 100, the number of channels occupied by the present invention is 11.43, and the number of channels occupied by the omnidirectional antenna and the greedy method are 16.78 and 14.23 respectively. The number of channels occupied by the present invention is even less. The number of channels occupied by the directional antenna method is 4.96. Although it occupies the least number of channels, the network robustness is extremely poor and cannot meet the robustness requirements of the network topology. The present invention can reduce the number of channels occupied by the network. On the one hand, it is because the present invention uses directional antennas to reduce mutual interference within the network. On the other hand, it is because the present invention reduces the transmission power of the node, thereby allowing more channel multiplexing.

[0102] Based on the above four comparison results, it can be concluded that the present invention uses directional antennas and omnidirectional antennas for joint transmission, which effectively improves the connectivity and robustness of the network topology compared to the existing comparison method of using a single antenna for topology control. On this basis, it reduces the node's transmission power and the number of channels occupied by the network. It is an omnidirectional hybrid topology control method for mobile self-organizing networks.

Claims

1. A topology control method for fully directional hybrid mobile ad hoc networks, characterized in that: include: (1) Any node u in the mobile ad hoc network sends a Hello packet containing its own information at maximum power and receives Hello packets from other nodes to establish a local K-connected subgraph (2) Node u on the local K-connected subgraph Solve the power and get Minimum total power required for communication in, is the neighbor set of node u, P i o is the power of node u using omnidirectional antenna to communicate with node i, P i d is the power of node u communicating with node i using directional antenna, a i Indicates the communication mode between node u and node i, a i = 0 means node u uses omnidirectional antenna to communicate with neighbor node i, a i =1 means node u communicates with neighbor node i using directional antenna; (3) With its maximum power P max For comparison: like Then execute (4), Otherwise, let the local topological subgraph Execute (5); (4) Node u generates a local topology subgraph with the goal of maximizing network connectivity. Execute (5); (5) Node u interaction local topology subgraph delete The unidirectional links in the local generated subgraph S are obtained u ; (6) Node u generates a local subgraph S u Perform power calculation to obtain the power distribution result and the direction of the directional antenna.

2. The method according to claim 1, wherein The node u in (2) is The power solution is implemented as follows: (2a) Node u is first connected according to the local K subgraph Get the neighbor node set Then calculate the omnidirectional antenna and any neighbor node The minimum power P required for communication i o =βd λ and use directional antennas to communicate with any neighboring node Minimum power required for communication Where β is the receiver sensitivity, d is the distance between node u and its neighbor i, λ is the path loss coefficient, and θ is the beamwidth of the directional antenna; (2b) Calculate the minimum total power for node u to communicate with its neighbor nodes based on the result of (2a) a i ＝{0,1}。 3. The method according to claim 1, wherein (4) Node u generates a local topology subgraph with the goal of maximizing network connectivity The implementation is as follows: (4a) Node u sets the target topology K0=K-1; (4b) Node u uses the FLSS algorithm to generate the basic topology of K0 connectivity according to Get its neighbor set Again Solve the power to get the minimum required power (4c) The maximum power P of node u max For comparison: like Then let K0=K0-1 for node u, Return (4b); like Then execute (4d); (4d) Node u is the local topological subgraph get The set of neighbor nodes in as well as The set of neighbor nodes in (4e) Let the candidate neighbor set calculate The set of all subsets Pair Collection Any member of By local topological subgraph Add edges (u, v) and (v, u) to obtain alternative topological subgraphs where v is Any member node in (4f) Calculate the alternative topological subgraphs respectively Corresponding minimum power Network connectivity and the average number of paths in the network (4g) In all cases where Alternative topological subgraphs of conditions Find the member with the greatest connectivity (4g1) For any two members in the alternative topology subgraph and If any of the following three conditions are met, it is considered ① ② ③ (4g2) Compare the sizes of all members of the candidate topology subgraph one by one according to the method in (4g1) and select the member with the greatest connectivity (4h) Let the local topological subgraph 4. The method according to claim 1, wherein The node u in (6) generates a local subgraph S u Perform power calculation to obtain the power distribution result and the direction of the directional antenna, which can be achieved as follows: (6a) Node u first generates a subgraph S based on the local u Get the neighbor node set N u , and then calculate the minimum power required to communicate with any neighbor node j using an omnidirectional antenna and the minimum power required to communicate with any neighbor node j using a directional antenna where β is the receiver sensitivity, d is the distance between node u and its neighbor i, λ is the path loss coefficient, θ is the beamwidth of the directional antenna, and j∈N u ; (6b) Calculate the local minimum communication power P between node u and its neighbor nodes based on the result of (6a) u : a j ＝{0,1}； Among them, a j Indicates the communication mode between node u and node j, a j = 0 means node u uses omnidirectional antenna to communicate with neighbor node j, a j =1 means node u uses directional antenna to communicate with neighbor node j; (6c) Node u sets the power of the omnidirectional antenna to: to a j = 1, node u sets the power of the directional antenna to The direction of the directional antenna is adjusted to point towards the neighbor node j.

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