CN-122028135-A - Underwater wireless sensor network routing method based on cavity prediction and MARCOS multi-attribute decision

CN122028135ACN 122028135 ACN122028135 ACN 122028135ACN-122028135-A

Abstract

The invention discloses an underwater wireless sensing network routing method based on hole prediction and MARCOS multi-attribute decision, which comprises the steps of establishing a neighbor list, storing and updating information received from neighbor nodes, predicting whether the neighbor nodes possibly escape from the node communication radius by establishing a safety area and escape area division in the node communication range, quantitatively evaluating the communication performance of the neighbor nodes based on the neighbor list information from a safety area score, an escape area score and a forwarding performance score, dynamically fusing the safety area score, the escape area score and the forwarding performance score by introducing a multi-attribute decision method, calculating comprehensive forwarding priority, adding the data packet into a candidate node list sequenced according to the multi-attribute decision when the node forwards the data packet, waiting for a next stage of time slice by the next stage of node, and starting a second stage of time slice waiting according to whether forwarding is successful or not. The routing decision self-adaptation method is strong in routing decision self-adaptation, and the problems of high processing overhead and the like caused by routing holes are avoided from the root.

Inventors

SHI WEI
MENG SHUYU
WANG JINGJING
NIU QIUNA
ZHANG JINGRUI
LUAN WENHUI
Xu Dunze

Assignees

青岛科技大学

Dates

Publication Date: 20260512
Application Date: 20260107

Claims (6)

1. The underwater wireless sensor network routing method based on cavity prediction and MARCOS multi-attribute decision is characterized by comprising the following steps: Step 1, network initialization and neighbor information maintenance, wherein nodes discover neighbor nodes and establish neighbor lists through periodically broadcasting Hello packets and exchanging information; step 2, constructing a hole evaluation index based on node movement trend prediction, namely predicting whether a neighboring node is likely to escape from the node communication radius by establishing a safety area division and an escape area division in the node communication range, and quantitatively evaluating the communication performance of the neighboring node from three dimensions of a safety area score, an escape area score and a forwarding performance score based on the neighbor list information obtained in the step 1; Step 3, calculating a cavity index based on an entropy weight MARCOS algorithm, namely dynamically fusing three indexes of a safety zone score, an escape zone score and a forwarding performance score by introducing a multi-attribute decision method, and calculating comprehensive forwarding priority; step 4, a routing decision and secondary forwarding waiting mechanism is that when a node forwards a data packet, a candidate node list ordered according to a multi-attribute decision is added into the data packet, a next node receives and waits for a first time slice, so that the data packet is ensured to be forwarded in sequence, and meanwhile, the secondary time slice waiting is started according to whether forwarding is successful or not so as to ensure that the data packet is not trapped in a routing hole; The specific calculation formula of the safe region score SNP in the step 2 is as follows: ; the escape area score ENP specifically comprises the following calculation formula: ; Wherein, the In order to escape the total number of risk area nodes, Is a risk assessment function; ; wherein ERI is escape risk index, K is penalty coefficient; ; ; Wherein, the Is made use of At the current time And received from Position information of data packet and last received from the same Time of the data packet of (2) Calculated with the position information To the point of Within the time period Relative to Is a constant axial velocity; Is a very small positive number, and is used for preventing the numerical explosion caused by zero or too small denominator; The forwarding performance score The specific calculation formula is as follows: ; Wherein, the And Respectively nodes In the past The number of data packets that are attempted to be forwarded and successfully forwarded in time; The step 3 specifically comprises the following steps: Step 3.1, constructing an initial decision matrix Defining ideal solution and anti-ideal solution, adding the ideal solution and the anti-ideal solution into a decision matrix to form an expansion matrix X, and carrying out normalization processing on the expansion matrix to obtain a standardized matrix U; Step 3.2, introducing an objective entropy weight vector W, constructing a weighted standardized matrix V, and calculating each neighbor node Comprehensive utility value of ideal solution and anti-ideal solution : ; Step 3.3, according to the utility value of each neighbor node Respectively calculating the utility ratio of the solution to the ideal solution And the utility ratio of the anti-ideal solution Constructing two utility functions And ; Step 3.4, calculating the final comprehensive evaluation value, i.e. the hole index, of each neighbor node based on the two utility functions of step 3.3 : 。
2. The method for routing an underwater wireless sensor network based on hole prediction and MARCOS multi-attribute decision as recited in claim 1, wherein the step 1 of storing and updating the information received from the neighboring nodes is specifically implemented by the node Upon receipt from a neighboring node After the data packet of the neighboring node, the transmission time stamp and the depth are extracted from the data packet of the neighboring node, and the node N1 depth itself And (3) with Depth of (2) For comparison, if Then Unsuitable as a next hop forwarding node if Already present in the N 1 candidate forwarding list, it is rejected if it is Then N 1 will As a candidate forwarding node; N 1 will The relevant parameters are calculated and placed in a candidate forwarding list, and named as And sets a timer for it, for Already in the N 1 candidate forwarding list, its relevant parameters are updated and the timer is redesigned if N 1 does not receive information from the timer before it expires And then cull it from the candidate forwarding list after the timer expires.
3. The method for routing an underwater wireless sensor network based on hole prediction and MARCOS multi-attribute decision according to claim 1, wherein the safety area and escape risk area division criteria in step 2 are: as a safety zone, in the case of a safety zone, To escape risk region, where R 0 is the communication radius of node N 1 , R' is the safety radius, ; Is a node The euclidean distance from node N 1 , , For the current time period of time, Is the speed of sound under water, Is the transmission time stamp of the data packet.
4. The underwater wireless sensor network routing method based on the hole prediction and MARCOS multi-attribute decision according to claim 1, wherein the specific calculation process of the objective entropy weight vector W in the step 3.2 is as follows: Standardized processing is carried out on the initialization matrix X to obtain a matrix M represents the number of neighbor nodes, and the characteristic proportion of the ith node under the jth index is calculated : : Calculating information entropy of jth index : ; Calculating entropy weight of j index according to information entropy : ; Wherein E k represents the information entropy of the kth index; finally obtaining objective entropy weight vector And meet the following 。
5. The underwater wireless sensor network routing method based on the cavity prediction and MARCOS multi-attribute decision as set forth in claim 4, wherein the normalization process of the initialization matrix X comprises the following steps: For SNP and PFP very large index, it The calculation formula is as follows: ; For ENP very small index, it The calculation formula is as follows: 。
6. The method for routing an underwater wireless sensor network based on hole prediction and MARCOS multi-attribute decision as recited in claim 1, wherein the utility ratio with respect to ideal solution in step 3.3 And the utility ratio of the anti-ideal solution The calculation formula is as follows: ; ; Wherein, the As the utility value of the ideal solution, Utility values for non-ideal solutions; the two utility functions And The method comprises the following steps: ; 。

Description

Underwater wireless sensor network routing method based on cavity prediction and MARCOS multi-attribute decision Technical Field The invention relates to the technical field of routing of an underwater wireless sensor network, in particular to a routing method of the underwater wireless sensor network based on cavity prediction and MARCOS multi-attribute decision. Background The underwater wireless sensor network is a key technology in the fields of ocean resource development, underwater military countermeasure, ocean environment monitoring and the like. However, due to the characteristics of high mobility and limited communication range of the underwater node, the network topology is dynamically changed, the problems of unstable transmission links and prominent hole problems are caused, and the design of a high-reliability underwater wireless sensor network routing protocol is a key technology. At present, the opportunistic routing protocol based on the geographic position becomes a hotspot for underwater routing research because the opportunistic routing protocol does not need to establish an end-to-end complete path, has strong adaptability and the like. For example, classical vector-based forwarding protocol (VBF) utilizes virtual pipes to limit the forwarding range, while depth-based routing protocol (DBR) utilizes depth information only for greedy forwarding. These protocols can achieve better performance in ideal environments. Since 2006, research on routing protocols of an underwater wireless sensor network has become a research hotspot more and more, and due to the high mobility of underwater nodes and limited communication range of the underwater nodes, network topology changes dynamically, so that routing void problems in a node sparse network or a node sparse area in the network are frequent. At present, various routing protocols consider that methods such as hole node marking, hole node dormancy and the like are adopted to handle hole problems so as to avoid the influence of known holes on subsequent routing, but a routing method for predictively avoiding the root causes generated by the routing hole problems is lacked. For the processing of the hole problem, the conventional methods for the routing protocol include data packet retransmission, backhaul and the like, and the processing methods for the processing of the hole problem can generate additional data packet transmission, cause additional signaling overhead, cause larger communication delay and energy consumption, even cause early death of nodes, and cause more hole problems. Finally, for the existing routing protocol with multi-attribute decision, the overall optimal linear combination is often sought under a specific network to perform fixed linear weighted summation on multiple parameters, and the optimal effect of the method is often difficult to obtain in the time-varying communication environment of the underwater wireless sensor network. In summary, the problems of difficult predictive avoidance of the hole problem, high hole processing overhead, poor route decision adaptability and the like exist in the existing routing protocol design of the underwater wireless sensor network, and the problems greatly restrict the network performance of the underwater wireless sensor network. Disclosure of Invention In order to overcome the problems in the prior art, the invention provides an underwater wireless sensor network routing method based on cavity prediction and MARCOS multi-attribute decision. The technical scheme adopted by the invention for solving the technical problems is that the routing method of the underwater wireless sensor network based on cavity prediction and MARCOS multi-attribute decision comprises the following steps: Step 1, network initialization and neighbor information maintenance, wherein nodes discover neighbor nodes and establish neighbor lists through periodically broadcasting Hello packets and exchanging information; step 2, constructing a hole evaluation index based on node movement trend prediction, namely predicting whether a neighboring node is likely to escape from the node communication radius by establishing a safety area division and an escape area division in the node communication range, and quantitatively evaluating the communication performance of the neighboring node from three dimensions of a safety area score, an escape area score and a forwarding performance score based on the neighbor list information obtained in the step 1; Step 3, calculating a cavity index based on an entropy weight MARCOS algorithm, namely dynamically fusing three indexes of a safety zone score, an escape zone score and a forwarding performance score by introducing a multi-attribute decision method, and calculating comprehensive forwarding priority; step 4, a routing decision and secondary forwarding waiting mechanism is that when a node forwards a data packet, a candidate node list ordered according to a multi-attribute d