Optimization method of gpsr routing protocol based on node space-time connectivity index

Abstract

This invention provides a GPSR routing protocol optimization method based on node spatiotemporal connectivity index. The method includes: Step 1: The source node obtains the location information of the destination node; Step 2: Determine whether there is a neighbor node closer to the destination node in the current node's neighbor node set. If yes, a greedy forwarding strategy is used for data transmission; otherwise, proceed to Step 3; Step 3: Calculate the spatiotemporal connectivity index of each neighbor node in the current node's neighbor node set, and use the node with the largest spatiotemporal connectivity index value as the current node's next-hop routing node for data transmission; Step 4: Determine whether there is a destination node in the current node's neighbor node set. If yes, the current node directly sends the data to the destination node; otherwise, return to Step 2 until the data is transmitted to the destination node.

Description

Technical Field

[0001] This invention relates to the field of mobile ad hoc network technology, and in particular to a GPSR routing protocol optimization method based on node spatiotemporal connectivity index. Background Technology

[0002] Greedy Perimeter Stateless Routing protocol (GPSR), as a typical location-based routing protocol, completes data transmission by employing two forwarding strategies: greedy forwarding and perimeter forwarding. Figure 1 As shown. Before sending a data packet, the source node first obtains the destination node's real location information through GPS positioning service. Then, it searches among the current node's neighboring nodes for a node with a shorter distance to the destination node. If such a node exists, it uses a greedy forwarding mode for transmission; otherwise, it means the greedy routing algorithm has fallen into a local optimum (i.e., encountered a routing hole, such as...). Figure 2 As shown, GPSR uses a perimeter-based forwarding strategy to bypass holes. When the bypass reaches a point where the greedy condition is met, it reverts to the greedy forwarding mode; this process repeats until the packet reaches its destination. Using both greedy and perimeter-based forwarding strategies to establish routes is efficient, concise, and scalable. However, GPSR also has some limitations. While the perimeter-based forwarding mode ensures that data packets can escape routing holes, each forwarding requires topology flattening to eliminate cross edges, increasing the forwarding hop count to reduce routing loops. Furthermore, in most cases, the forwarding path is not optimal; therefore, frequent routing holes can cause a significant drop in the performance of the GPSR algorithm. Summary of the Invention

[0003] To address the problems of GPSR routing protocol, which is typically based on geographic location information and suffers from single routing decision criteria, easy encounters with routing holes, and increased hop counts due to surrounding forwarding patterns, this invention provides a GPSR routing protocol optimization method based on node spatiotemporal connectivity index.

[0004] The GPSR routing protocol optimization method based on node spatiotemporal connectivity index provided by this invention includes:

[0005] Step 1: The source node obtains the location information of the destination node;

[0006] Step 2: Determine if there is a neighbor node closer to the destination node in the current node's neighbor node set. If yes, use a greedy forwarding strategy to transmit data; otherwise, proceed to step 3.

[0007] Step 3: Calculate the spatiotemporal connectivity index of each neighbor node in the current node's neighbor node set, and use the node with the largest spatiotemporal connectivity index value as the next-hop routing node for data transmission. The calculation process for the spatiotemporal connectivity index of each neighbor node includes: calculating the velocity similarity of the neighbor node at adjacent time points and recording the result as the temporal correlation index; calculating the velocity similarity between the current node and the neighbor node and recording the result as the spatial correlation index; calculating and comparing the distances between the current node, the neighbor node, and the destination node, and recording the comparison result as the relative position offset index; obtaining the spatiotemporal connectivity index of the neighbor node based on the temporal correlation index, spatial correlation index, and relative position offset index.

[0008] Step 4: Determine if the destination node exists in the set of neighboring nodes of the current node. If yes, the current node will send the data directly to the destination node; otherwise, return to step 2 and continue until the data is transmitted to the destination node.

[0009] Furthermore, the time correlation index D of node i is calculated according to formula (1). temporal (i,t,t′):

[0010]

[0011] Among them, the time correlation index D temporal (i,t,t′) represents the degree of similarity between the velocities of node i at time t and time t′. Represents velocity vector and The relative directions between them Represents velocity vector and The speed ratio between them This represents the velocity vector of node i at time t. This represents the velocity vector of node i at time t′. and These represent the velocity values ​​of node i at time t and time t′, respectively.

[0012] Furthermore, the spatial correlation index D between the current node i and its neighboring node j is calculated according to formula (2). spatial (i,j,t):

[0013]

[0014] Among them, the spatial correlation index D spatial (i,j,t) represents the degree of similarity in speed between the current node i and its neighbor node j at time t. Represents velocity vector and The relative directions between them Represents velocity vector and The speed ratio between them This represents the velocity vector of the current node i at time t. This represents the velocity vector of neighbor node j at time t. and These represent the velocity values ​​of the current node i and its neighboring node j at time t, respectively.

[0015] Furthermore, if the communication distance D between the current node i and its neighbor node j at time t... i,j If (t) is greater than the communication radius R of the current node i, then D spatial (i,j,t)=0.

[0016] Furthermore, the relative position offset index D is calculated according to formula (3). distance (j):

[0017]

[0018] Where l(i,d) represents the Euclidean distance between the current node i and the destination node d, and l(j,d) represents the Euclidean distance between the neighbor node j and the destination node d.

[0019] Further, in step 3, the temporal-spatial connectivity index (TSC) of the neighbor node j is obtained according to formula (4) based on the temporal correlation index, spatial correlation index, and relative position offset index:

[0020] TSC=αD temporal (j)+βD spatial (j)+γD distance (j) (4)

[0021] Among them, D temporal D is the time correlation index. spatial D is the spatial correlation index. distance The relative position offset index is α, β, and γ, which are given weighted judgment coefficients.

[0022] The beneficial effects of this invention are:

[0023] (1) The GPSR routing protocol optimization method based on node spatiotemporal connectivity index provided by the present invention firstly ensures the efficiency of node route selection before encountering routing holes by using a greedy algorithm. Secondly, by introducing the node spatiotemporal connectivity index, the spatiotemporal connectivity index can reflect the movement characteristics and topological characteristics of network nodes in time and space. When encountering a routing hole, by selecting the next-hop node with good spatiotemporal connectivity from the neighboring nodes, the probability of falling into the hole again can be reduced while solving the routing hole, and the forwarding delay of data packets can be reduced.

[0024] (2) As a preferred method for calculating spatiotemporal connectivity, spatiotemporal connectivity can be calculated by using three indices (including time correlation index, spatial correlation index and relative position offset index) that reflect the relative speed, relative direction and time correlation between neighboring nodes and the current node. This can further improve the efficiency of the selected path and ensure the efficiency and success rate of data packet transmission. Attached Figure Description

[0025] Figure 1 A flowchart of node routing for the existing GPSR protocol;

[0026] Figure 2 This is a diagram showing the node locations when a routing hole is encountered.

[0027] Figure 3 This is a flowchart illustrating the GPSR routing protocol optimization method based on node spatiotemporal connectivity index provided in an embodiment of the present invention.

[0028] Figure 4 A schematic diagram comparing the data paths when forwarding encounters routing holes using the traditional GPSR protocol forwarding method and the method of the present invention, provided for embodiments of the present invention.

[0029] Figure 5 This diagram illustrates a comparison of routing and forwarding paths when a node is moving, using a traditional GPSR protocol forwarding method and the method of this invention, as provided in an embodiment of the present invention. Detailed Implementation

[0030] To make the objectives, technical solutions, and advantages of this invention clearer, the technical solutions of the embodiments of this invention will be clearly described below with reference to the accompanying drawings. Obviously, the described embodiments are only some, not all, of the embodiments of this invention. All other embodiments obtained by those skilled in the art based on the embodiments of this invention without creative effort are within the scope of protection of this invention.

[0031] Example 1

[0032] like Figure 3As shown, this embodiment of the invention provides a GPSR routing protocol optimization method based on node spatiotemporal connectivity index, including the following steps:

[0033] S101: The source node obtains the location information of the destination node;

[0034] S102: Determine whether there is a neighbor node closer to the destination node in the current node's neighbor node set. If yes, use a greedy forwarding strategy to transmit data; otherwise, proceed to step S103.

[0035] S103: Calculate the spatiotemporal connectivity index of each neighbor node in the set of neighbor nodes of the current node, and use the node with the largest spatiotemporal connectivity index value as the next hop routing node for data transmission of the current node;

[0036] Specifically, based on the analysis of the temporal and spatial motion characteristics and topological characteristics of network nodes, this embodiment of the invention designs and obtains the calculation index of the time-space connectivity function (TSC) of neighboring nodes, thereby assisting nodes in making next-hop decisions when encountering routing holes.

[0037] As one possible implementation, the calculation process of the spatiotemporal connectivity index of each neighboring node includes: calculating the velocity similarity of the neighboring node at adjacent time points and recording the calculation result as the temporal correlation index; calculating the velocity similarity between the current node and the neighboring node and recording the calculation result as the spatial correlation index; calculating and comparing the distances between the current node, the neighboring node, and the destination node respectively, and recording the comparison result as the relative position offset index; and obtaining the spatiotemporal connectivity index of the neighboring node based on the temporal correlation index, the spatial correlation index, and the relative position offset index.

[0038] Among them, the temporal correlation index reflects the movement characteristics of nodes in time, the spatial correlation index reflects the movement characteristics of nodes in space, and the relative position offset index reflects the topological characteristics of nodes.

[0039] S104: Determine whether the destination node exists in the set of neighboring nodes of the current node. If yes, the current node will send the data directly to the destination node; otherwise, return to step S102 until the data is transmitted to the destination node.

[0040] The routing method provided in this embodiment of the invention can adjust the routing strategy based on the connectivity and movement states of neighboring nodes. Figure 1Based on the standard GPSR protocol, this invention comprehensively considers the temporal and spatial movement relationship of nodes, topological relationship, and surrounding forwarding patterns in routing and forwarding, calculates the temporal-spatial connectivity between the current node and neighboring nodes, and selects the more critical and stable nodes among the neighboring nodes as the next hop when encountering routing holes, thereby reducing the number of packet forwarding hops, reducing the latency of network packet propagation, and improving the network packet delivery rate.

[0041] Example 2

[0042] Based on the above embodiments, the present invention specifically illustrates the design method of the spatiotemporal connectivity index.

[0043] In the above embodiments, the spatiotemporal connectivity index is mainly determined by three index indicators: time correlation index, spatial correlation index, and relative position offset index. The following are the calculation methods of each of the three index indicators.

[0044] (1) Time correlation index

[0045] In this invention, the temporal correlation index is defined as the similarity of a node's velocity at time t and time t′. It is a function of the mobile node's acceleration and geographical constraints, serving as a measure of the dependence of a node's motion velocity on its velocity at a previous time in the network. If a node's current velocity is completely independent of its velocity at the previous time, then the mobile node has a small temporal correlation index; however, if the current velocity strongly depends on the velocity at a previous time, then the mobile node has a higher temporal correlation index.

[0046] Based on the above properties, as one preferred calculation method, the time correlation index D of node i from time t to t′ is... temporal The formula for calculating (i,t,t′) is as follows:

[0047]

[0048] Among them, the time correlation index D temporal (i,t,t′) represents the degree of similarity between the velocities of node i at time t and time t′. Represents velocity vector and The relative directions between them Represents velocity vector and The speed ratio between them This represents the velocity vector of node i at time t. This represents the velocity vector of node i at time t′. and These represent the velocity values ​​of node i at time t and time t′, respectively.

[0049] Due to the complexity of the environment, limited resources, and finite node energy that ad hoc networks may face, communication links between nodes are susceptible to failure due to factors such as inter-node communication interference, node dormancy, and power depletion. This leads to decreased link stability, increased packet loss rate, and end-to-end latency. Therefore, the impact of a single node's moment-to-moment motion state on network performance needs to be incorporated into routing decisions. Nodes with stable motion characteristics have a higher time dependence index. When a node experiences sudden stops, accelerations, or failures during its motion, its motion lacks correlation. If such a node is used as the destination node for packet forwarding, it may lead to packet routing failures, compromising the accuracy and reliability of node selection and link establishment. The time dependence index can effectively determine the time dependence of a single node's motion. Incorporating time dependence into routing decisions can ensure the stability of the selected next-hop neighbor node, thereby improving link reliability.

[0050] (2) Spatial correlation index

[0051] In this invention, the spatial correlation index refers to the similarity of the speeds of two communication nodes, reflecting the extent to which the movement of the nodes is influenced by each other. The spatial correlation index value is high when two communication nodes move in roughly the same direction and at almost similar speeds; however, the spatial correlation index value is low if the two communication nodes move in opposite directions or at significantly different speeds.

[0052] Based on the above properties, as one preferred calculation method, the spatial correlation index D between the current node i and its neighboring node j is... spatial The formula for calculating (i,j,t) is as follows:

[0053]

[0054] Among them, the spatial correlation index D spatial (i,j,t) represents the degree of similarity in speed between the current node i and its neighbor node j at time t. Represents velocity vector and The relative directions between them Represents velocity vector and The speed ratio between them This represents the velocity vector of the current node i at time t. This represents the velocity vector of neighbor node j at time t. and These represent the velocity values ​​of the current node i and its neighboring node j at time t, respectively.

[0055] It should be noted that, due to the limited communication range of each node in a wireless network, the movement of a node rarely depends spatially on distant nodes. Therefore, the following constraint is set: only the relationships between nodes within a node's communication range are considered. That is, if the communication distance D between the current node i and its neighbor node j at time t is... i,j If (t) is greater than the communication radius R of the current node i, then D spatial (i,j,t)=0.

[0056] Therefore, if the moving nodes move independently of each other, then the D between the moving nodes... spatial The value of (i,j,t) will be smaller. On the other hand, if a node's movement is influenced by its neighboring nodes, causing them to move in similar directions and speeds, D... spatial The (i,j,t) value will be higher. In the GPSR protocol, nodes obtain the geographical location information of neighboring nodes by periodically receiving broadcast signals from all neighbors. When routing and forwarding neighboring nodes, the location information of surrounding neighbors obtained in the previous time period is used. At this time, the neighbor may have moved out of the communication range of the node, causing the transmission link to break, which in turn leads to packet loss or backhaul, and the overall network performance degrades. Considering that the movement speed and direction of a single node cannot fully reflect the spatial relationship between nodes. When a single neighboring node moves at a high speed, if the sending node moves at a similar speed and direction, the relative position change between the two is small. Conversely, when a single neighboring node moves at a low speed, but the sending node moves in the opposite direction, the relative position change between the two is large. Therefore, the relationship between the movement speed and direction of the sending node and neighboring nodes should be considered comprehensively. The spatial correlation index can effectively determine the spatial position change relationship between two moving nodes. When a neighboring node with a large index is selected as the next hop, it can alleviate the link instability caused by node movement and reduce routing failures caused by obtaining the location through HELLO packets at fixed time intervals.

[0057] (3) Relative position offset index

[0058] In this invention, the relative position offset index is defined as the ratio of the distance between the current node i and the destination node d of the data packet to be forwarded to the distance between node i's neighbor node j and the destination node d, that is:

[0059]

[0060] Where l(i,d) represents the Euclidean distance between the current node i and the destination node d, and l(j,d) represents the Euclidean distance between the neighbor node j and the destination node d.

[0061] When node i encounters a routing hole during forwarding, node i is the closest node to the destination node within its communication range. Therefore, at this time, the D of neighboring node j... distance (j)<1, and the farther the neighbor node j is from the destination node, the better D distance The smaller the value of (j), the better. According to the right-hand rule used in traditional GPSR for handling route holes, when a hole is encountered at node i, if... Figure 2 As shown, data packets are forwarded in the order of ixyz; however, in this invention, the relative position offset index D of node y is... distance If (y) is greater than node x, then according to the relative position offset index, node y should be the next hop destination node. This shows that the relative position offset index can guide the forwarding of data packets, reduce the number of forwardings when encountering routing holes, and avoid the occurrence of routing loops.

[0062] In this embodiment of the invention, the time-space connectivity function (TSC) index is calculated using the above three decision factors: time correlation index, spatial correlation index, and relative position offset index. Then, appropriate weighting coefficients α, β, and γ are assigned to these three decision factors. Finally, the value of the node's time-space connectivity function (TSC) is calculated according to the following formula:

[0063] TSC=αD temporal (j)+βD spatial (j)+γD distance (j) (4)

[0064] Among them, D temporal D is the time correlation index. spatial D is the spatial correlation index. distance The relative position offset index is α, β, and γ, which are given weighted judgment coefficients (different weighted judgment coefficients α, β, and γ are given according to different influencing factors in different application scenarios of the network).

[0065] Example 3

[0066] Based on the above embodiments, the GPSR routing protocol optimization method of the present invention will be further illustrated below through specific forwarding scenarios.

[0067] As one type of forwarding scenario, such as Figure 4 As shown, the current node i will forward the data packet to the destination node d. Because there are no neighboring nodes closer to the destination node than itself (i.e., a routing hole is encountered), according to the traditional GPSR routing protocol, the perimeter forwarding mode is activated. That is, node i selects node x to forward the data packet according to the perimeter forwarding rules, thus following the path shown. Figure 4The path ixabcyefgd shown will pass the data packet to the destination node d.

[0068] However, according to the method of this invention, after encountering a routing hole at node i, node y is the neighboring node closest to the destination node d, and its When the value is maximum, after calculating the TSC index of the neighboring node at node i, node y will be selected as the next-hop forwarding node as the forwarding choice when the route hole is in place. After the data packet is forwarded to node y, the greedy forwarding strategy is restored at y by restarting step S102. The data packet is forwarded according to the iyefgd path under the method of the present invention.

[0069] This shows that while traditional perimeter forwarding strategies can solve the problem of routing holes, they cannot effectively select the optimal path for data forwarding. However, the method of this invention, by introducing the TSC index, can effectively improve the data packet path forwarding efficiency when facing holes.

[0070] In another forwarding scenario, the nodes move during the transmission of GPSR protocol data packets from the source node to the destination node. For example... Figure 5 As shown, node i is the node currently forwarding the data packet, d is the destination node, and x and y are both within node i's communication range. Node i is currently facing a routing hole. According to the perimeter forwarding rules of the traditional GPSR routing protocol, node i should choose node x as its next hop. Due to the movement characteristics of nodes, and the different directions and speeds of their movement, the position of node x changes drastically during the time it takes to update the neighbor node table. Node x continuously moves away from the destination node d, and... and In the opposite direction, the distance between node i and node x gradually exceeds the communication radius of node i. According to the GPSR forwarding rules, node x is selected as the forwarding node. At this time, the transmission link may break, which greatly reduces the probability of successful forwarding.

[0071] However, according to the method of this invention, when node i faces a routing hole, after calculating the TSC index value of the neighboring nodes of node i according to equation (4), the TSC... y >TSC x Node y will be selected as the next-hop forwarding node of node i. After y is selected as the forwarding node, the data packets can reach the destination node faster, effectively reducing the probability of link breakage.

[0072] The GPSR routing protocol forwarding method provided by this invention first obtains the location and speed information of the source node, destination node, and neighboring nodes through HELLO packets. It then calculates the temporal-spatial connectivity index (TSC) of the neighboring nodes and stores it in the packet header. This index serves as the basis for designing the GPSR optimization protocol. Next, based on the TSC, the GPSR routing protocol forwarding method is optimized. According to the positional relationship between the current node, neighboring nodes, and the destination node, a greedy forwarding strategy is adopted when a neighboring node is closer to the destination node; otherwise, based on the TSC index value of the neighboring nodes, the neighboring node with the largest TSC index value is selected as the next-hop forwarding node. This invention can reduce the number of forwarding hops when encountering routing "holes," reducing the forwarding latency of node data packets. Furthermore, by selecting a node with a large TSC index as the next hop, the probability of encountering routing holes can be effectively reduced, improving the success rate of data packet transmission.

[0073] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, and not to limit them; although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features; and these modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. A GPSR routing protocol optimization method based on node spatiotemporal connectivity index, characterized in that, include: Step 1: The source node obtains the location information of the destination node; Step 2: Determine if there is a neighbor node closer to the destination node in the current node's neighbor node set. If yes, use a greedy forwarding strategy to transmit data; otherwise, proceed to step 3. Step 3: Calculate the spatiotemporal connectivity index of each neighbor node in the set of neighbor nodes of the current node, and use the node with the largest spatiotemporal connectivity index value as the next-hop routing node for data transmission of the current node; wherein, the calculation process of the spatiotemporal connectivity index of each neighbor node includes: calculating the speed similarity of the neighbor node at adjacent time points, and recording the calculation result as the time correlation index; calculating the speed similarity between the current node and the neighbor node, and recording the calculation result as the spatial correlation index; calculating and comparing the distances between the current node, the neighbor node and the destination node respectively, and recording the comparison result as the relative position offset index; obtaining the spatiotemporal connectivity index of the neighbor node according to the time correlation index, spatial correlation index and relative position offset index; specifically including: obtaining the spatiotemporal connectivity index TSC of the neighbor node j according to formula (4): TSC=αD temporal (j)+βD spatial (j)+γD distance (j) (4) Among them, D temporal D is a time-related index. spatial D is the spatial correlation index. distance The relative position offset index is α, β, and γ, which are given weighted judgment coefficients. Step 4: Determine if the destination node exists in the set of neighboring nodes of the current node. If yes, the current node will send the data directly to the destination node; otherwise, return to step 2 and continue until the data is transmitted to the destination node.

2. The GPSR routing protocol optimization method based on node spatiotemporal connectivity index according to claim 1, characterized in that, The time correlation index D of node i is calculated according to formula (1). temporal (i,t,t′): Among them, the time correlation index D temporal (i,t,t′) represents the degree of similarity between the velocities of node i at time t and time t′. Represents velocity vector and The relative directions between them Represents velocity vector and The speed ratio between them This represents the velocity vector of node i at time t. This represents the velocity vector of node i at time t′. and These represent the velocity values ​​of node i at time t and time t′, respectively.

3. The GPSR routing protocol optimization method based on node spatiotemporal connectivity index according to claim 1, characterized in that, Calculate the spatial correlation index D between the current node i and its neighbor node j according to formula (2). spatial (i,j,t): Among them, the spatial correlation index D spatial (i,j,t) represents the degree of similarity in speed between the current node i and its neighbor node j at time t. Represents velocity vector and The relative directions between them Represents velocity vector and The speed ratio between them This represents the velocity vector of the current node i at time t. This represents the velocity vector of neighbor node j at time t. and These represent the velocity values ​​of the current node i and its neighboring node j at time t, respectively.

4. The GPSR routing protocol optimization method based on node spatiotemporal connectivity index according to claim 3, characterized in that, If the communication distance D between the current node i and its neighbor node j at time t... i,j If (t) is greater than the communication radius R of the current node i, then D spatial (i,j,t)=0.

5. The GPSR routing protocol optimization method based on node spatiotemporal connectivity index according to claim 1, characterized in that, Calculate the relative position offset index D according to formula (3). distance (j): Where l(i,d) represents the Euclidean distance between the current node i and the destination node d, and l(j,d) represents the Euclidean distance between the neighbor node j and the destination node d.

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