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CN-122002444-A - Dynamic route cooperative optimization method for wireless ad hoc network

CN122002444ACN 122002444 ACN122002444 ACN 122002444ACN-122002444-A

Abstract

The invention discloses a dynamic route collaborative optimization method of a wireless ad hoc network, which comprises the following steps of S1, forming a multi-hop network by a plurality of sensing nodes and gateways, S2, sending a test packet after each sensing node is electrified, acquiring RSSI values of neighbor nodes, calculating relative distances between nodes based on the RSSI values, S3, newly adding an accumulated distance field in a routing protocol, constructing a composite cost function with the minimum total distance of paths as a target, setting an early warning threshold and a breaking threshold, S4, starting local route repair when any sensing node detects that the RSSI value of the sensing node and the adjacent node in the current route is reduced to an early warning interval, and S5, triggering a source node to reconstruct a global path when any sensing node detects that the RSSI value of the sensing node and the adjacent node in the current route is lower than the breaking threshold. The invention can realize the active prediction of the route, the self-repair of the route and the dynamic optimization of the signal intensity drive.

Inventors

  • AN SEN
  • SHI TAILONG
  • ZHU XIAOYU

Assignees

  • 上海埃威信息科技有限公司

Dates

Publication Date
20260508
Application Date
20251217

Claims (10)

  1. 1. A dynamic route cooperative optimization method of a wireless ad hoc network is characterized by comprising the following steps: S1, forming a multi-hop network by a plurality of sensing nodes and a gateway; s2, after each sensing node is electrified, sending a test packet, acquiring RSSI values of neighbor nodes, and calculating the relative distance between the nodes based on the RSSI values; S3, a cumulative distance field is newly added in a routing protocol, a composite cost function which aims at minimizing the total distance of a path is constructed, and an early warning threshold value and a fracture threshold value are set; s4, when any sensor node detects that the RSSI value of the adjacent node in the current route is reduced to an early warning interval, local route repair is started; and S5, when any sensing node detects that the RSSI value of the sensing node and the adjacent node in the current route is lower than the breaking threshold value, triggering the source node to reconstruct the global path.
  2. 2. The method for dynamic route collaborative optimization of wireless ad hoc network according to claim 1, wherein the sensing node in the step S1 comprises at least one of a temperature and humidity sensor, a door and window magnetic sensor and an illumination sensor, and performs wireless ad hoc network communication with a gateway through a 2.4GHz frequency band.
  3. 3. The method for dynamic route collaborative optimization of wireless ad hoc networks according to claim 1, wherein the specific manner of calculating the relative distance in step S2 comprises: Performing moving average filtering or Kalman filtering on the obtained RSSI value; Based on the filtered RSSI values, the inter-node distances are calculated by the logarithmic path loss model: ; wherein PL (d) is path loss at distance d, PL # ) For reference distance Where the path loss, n is the path loss index, Is a shadow fading factor.
  4. 4. The method for dynamic route collaborative optimization of a wireless ad hoc network according to claim 3, wherein the path loss index n is set as follows according to the type of deployment environment: Free space environment n=2.0; Indoor office environment n=3.0-4.0; dense building environment n=4.0-6.0.
  5. 5. The method for dynamic route collaborative optimization of wireless ad hoc networks according to claim 1, wherein the composite cost function constructed in step S3 is: 。
  6. 6. The method for dynamic route collaborative optimization of a wireless ad hoc network according to claim 1, wherein the early warning threshold and the breaking threshold are dynamically set based on a distance value of a current stable link: The early warning threshold value is 1.2 to 1.4 times of the current link distance; the break threshold is 1.5 to 2.0 times the current link distance.
  7. 7. The method for dynamic route collaborative optimization of wireless ad hoc networks according to claim 1, wherein the local route repair in step S4 comprises: When the current node detects that the signal is reduced to the early warning interval, a substitute node is selected from the neighbor nodes based on the composite cost function, a local optimization path is constructed, and the relevant node is informed to update the routing table.
  8. 8. The method for dynamic route co-optimization of wireless ad hoc network according to claim 1, wherein the global path reconstruction in step S5 comprises: And after receiving the path breakage notification, the source node reinitiates a route discovery process, and selects a new path with the smallest cumulative distance according to the composite cost function.
  9. 9. The method according to claim 1, wherein the routing protocol of step S3 is based on AODV, zigBee, BLE Mesh, or a routing protocol framework using Wi-Fi Mesh.
  10. 10. The method of dynamic route co-optimization for wireless ad hoc networks according to any of claims 1 to 9, further comprising constructing an "RSSI-distance" mapping table based on historical RSSI data for fast estimation of inter-node distances in the same deployment environment type.

Description

Dynamic route cooperative optimization method for wireless ad hoc network Technical Field The invention relates to a dynamic routing method, in particular to a dynamic routing collaborative optimization method of a wireless ad hoc network. Background In a wireless Ad-hoc Network (Ad-hoc Network) system with a frequency band of 2.4GHz, such as ZigBee, wi-Fi Mesh, bluetooth Mesh and other networks, the communication between nodes is limited by factors such as signal attenuation, reflection, multipath interference and the like. The existing AODV (Ad hoc On-DEMAND DISTANCE Vector Routing protocol), and other protocols take hop count as main measures, but links with weak signals and long distances are easy to select in a complex wireless environment, so that the packet loss rate is high and the energy consumption is high. Although attempts have been made to introduce RSSI as a link quality indicator, many stay in the threshold decision stage, failing to achieve a mapping from signal strength to spatial distance, and lack a predictive route maintenance mechanism based on distance. RSSI (received signal strength indicator) is a commonly provided parameter of all 2.4GHz radio frequency chips (such as CC2530, ESP32, nRF52840, etc.), which reflects the signal propagation strength between nodes. However, the prior art uses RSSI for link detection or simple weighting only and does not implement closed loop optimization from RSSI to distance to routing decisions. Therefore, how to combine the RSSI ranging with the dynamic routing mechanism in the 2.4GHz band to achieve low-cost and high-robustness link selection and maintenance is a technical problem to be solved. Disclosure of Invention The technical problem to be solved by the invention is to provide a dynamic route collaborative optimization method of a wireless ad hoc network, which can realize the dynamic optimization of route active prediction, path self-repair and signal intensity driving. The invention provides a dynamic route collaborative optimization method of a wireless ad hoc network, which comprises the following steps of S1, forming a multi-hop network by a plurality of sensing nodes and gateways, S2, sending a test packet and recording the average value of neighbor RSSIs after the sensing nodes are electrified, calculating the relative distance, S3, adding a newly accumulated distance field in a communication protocol, constructing a composite cost function by taking the minimum total distance as a path selection criterion and combining hop weight, setting an early warning threshold and a breaking threshold, S4, carrying out local route repair in advance when each sensing node finds that the RSSIs of the adjacent sensing nodes of the current route are reduced to the early warning interval, and S5, immediately notifying a source node to reconstruct a path when any sensing node finds that the RSSIs of the adjacent sensing nodes of the current route are smaller than the breaking threshold. Further, the sensing node in the step S1 includes at least one of a temperature and humidity sensor, a door and window magnetic sensor, and an illumination sensor, and performs wireless ad hoc network communication with the gateway through a 2.4GHz frequency band. Further, the specific way of calculating the relative distance in the step S2 includes performing a moving average filtering or a kalman filtering on the obtained RSSI value, and calculating the distance between nodes through the following log path loss model based on the filtered RSSI value: wherein PL (d) is path loss at distance d, PL # ) For reference distanceWhere the path loss, n is the path loss index,Is a shadow fading factor. Further, the path loss index n is set according to the type of the deployment environment, namely, a free space environment n=2.0, an indoor office environment n=3.0-4.0, and a dense building environment n=4.0-6.0. Further, the composite cost function constructed in the step S3 is:。 further, the early warning threshold and the breaking threshold are dynamically set based on the distance value of the current stable link, wherein the early warning threshold is 1.2 to 1.4 times of the current link distance, and the breaking threshold is 1.5 to 2.0 times of the current link distance. Further, the local route repair in the step S4 comprises the steps of selecting a substitute node from the neighbor nodes based on the composite cost function when the current node detects that the signal falls to the early warning interval, constructing a local optimized path, and notifying the related node to update the routing table. Further, the global path reconstruction in step S5 includes that the source node re-initiates the route discovery process after receiving the path break notification, and selects a new path with the smallest cumulative distance according to the composite cost function. Further, the routing protocol of the step S3 is based on AODV, zigBee, BLE Mesh, or a routing protocol fra