CN112702710A - Opportunistic routing optimization method based on link correlation in low duty ratio network - Google Patents

Opportunistic routing optimization method based on link correlation in low duty ratio network Download PDF

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CN112702710A
CN112702710A CN202011526524.6A CN202011526524A CN112702710A CN 112702710 A CN112702710 A CN 112702710A CN 202011526524 A CN202011526524 A CN 202011526524A CN 112702710 A CN112702710 A CN 112702710A
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申兴发
刘立立
倪振贤
李树丰
赵庆彪
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Hangzhou Dianzi University
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    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04W—WIRELESS COMMUNICATION NETWORKS
    • H04W40/00—Communication routing or communication path finding
    • H04W40/02—Communication route or path selection, e.g. power-based or shortest path routing
    • H04W40/12—Communication route or path selection, e.g. power-based or shortest path routing based on transmission quality or channel quality
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04W—WIRELESS COMMUNICATION NETWORKS
    • H04W4/00—Services specially adapted for wireless communication networks; Facilities therefor
    • H04W4/30—Services specially adapted for particular environments, situations or purposes
    • H04W4/38—Services specially adapted for particular environments, situations or purposes for collecting sensor information
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04W—WIRELESS COMMUNICATION NETWORKS
    • H04W40/00—Communication routing or communication path finding
    • H04W40/02—Communication route or path selection, e.g. power-based or shortest path routing
    • H04W40/12—Communication route or path selection, e.g. power-based or shortest path routing based on transmission quality or channel quality
    • H04W40/125—Communication route or path selection, e.g. power-based or shortest path routing based on transmission quality or channel quality using a measured number of retransmissions as a link metric
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04W—WIRELESS COMMUNICATION NETWORKS
    • H04W40/00—Communication routing or communication path finding
    • H04W40/24—Connectivity information management, e.g. connectivity discovery or connectivity update
    • H04W40/246—Connectivity information discovery
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04W—WIRELESS COMMUNICATION NETWORKS
    • H04W84/00—Network topologies
    • H04W84/18—Self-organising networks, e.g. ad-hoc networks or sensor networks

Abstract

The invention discloses an opportunistic routing optimization method based on link correlation in a low duty ratio network. The invention comprises the following steps: step 1, sensor nodes in a network send data detection packets to each other; step 2, collecting link quality of neighbor sensor nodes in the current network; step 3, calculating link correlation through a receiving bitmap of the data detection packet; calculating expected transmission times ETX by combining the link quality and the link correlation; step 4, making grouping decision based on the minimum ETX; and 5, rescheduling the work scheduling plan of the node. The invention only needs the information of the neighbor sensor node, which brings the minimum communication overhead, and the algorithm closes the gap between the limited energy of the node and the service life requirement of the application program. The invention has the advantages of low time complexity and good effect, is easy to be deployed in the nodes, and can optimize the data transmission condition of the nodes in the wireless network most truly.

Description

Opportunistic routing optimization method based on link correlation in low duty ratio network
Technical Field
The invention belongs to the field of wireless sensor network protocols, and particularly relates to a novel intra-group synchronous and extra-group asynchronous low-duty-ratio packet scheduling algorithm.
Background
Wireless sensor networks have gradually penetrated into the daily lives of people, changing the life style of people, including smart homes, infrastructure protection, environmental monitoring, military fields, and the like. The low duty ratio mechanism is used as an effective method for reducing energy consumption of the wireless sensor network and prolonging the service cycle, allows the node to wake up periodically, and avoids energy consumed when the node is in a waiting state and is in idle listening. The low duty cycle technique can greatly prolong the service life of the network. The discovery and research of link correlation can greatly improve the transmission efficiency of the opportunistic routing protocol by improving the receiving diversity of the data packets in the candidate forwarding set, and reduce a large amount of redundant transmission from a source node to a target node due to retransmission, thereby reducing time delay caused by network data transmission, improving the network throughput rate and the like.
The traditional routing algorithm is inherently simple in logic and easy to implement, but does not consider the influence of instability, time-varying characteristics and broadcasting characteristics of a wireless channel in a sensor network on the performance of a protocol. The time-varying nature of the wireless link can cause the link quality to change over time, and therefore the path selected in advance is not necessarily the best case, potentially leading to transmission redundancy and increased transmission times. The broadcast nature of the channel makes it possible for a packet sent by a transmitting node to be received by multiple forwarding nodes, and opportunistic routing takes advantage of this to reduce the number of hops on the transmission path. In various applications, opportunistic routing plays an increasingly important role, and most existing solutions of opportunistic routing protocols still only focus on the situation that nodes are all awake, which can cause serious reduction of network efficiency if the solutions are directly applied to low-duty-cycle wireless networks.
Meanwhile, the existing research on opportunistic routing in a low-duty ratio wireless network ignores the influence of receiving diversity among duty ratio scheduling centralized repeaters, so that the advantage of the opportunistic routing cannot be fully utilized. At the same time, these studies assume explicitly or implicitly that the radio links are independent of each other. But studies have clearly shown that wireless links are not independent and that packet transmission from a sender to multiple receivers is correlated in short time intervals, mainly caused by cross-network interference and associated shadowing. The lack of link correlation consideration overestimates the performance efficiency of opportunistic routing in low duty cycle wireless networks, and therefore new solutions are necessary to solve the problem.
Disclosure of Invention
The invention mainly aims to provide a link correlation-based optimization method of an opportunistic routing protocol in a low-duty-cycle network, aiming at the problem that the performance efficiency of opportunistic routing in the low-duty-cycle wireless network is unreal due to the lack of link correlation consideration.
The opportunistic routing optimization algorithm designed by the invention comprises the following steps:
step 1, sending data detection packets to sensor nodes in network
The sensor node periodically sends 10 data detection packets to all the neighbor sensor nodes, and each data detection packet must have a unique work order D so as to identify whether the data detection packet is lost or not. The receiving state information of the data detection packet is represented by a binary sequence receiving bitmap, wherein '1' represents that the detection data packet is successfully received, and '0' represents that the detection data packet is lost and is not received by the neighbor sensor node. For example, [10101] indicates that the data probe packets with ID 1, 3, and 5 were successfully received, and the data probe packets with ID 2 and 4 were lost.
Step 2, collecting link quality Q of neighbor sensor nodes in the current networkn；
Calculating link quality Q using the received bitmap of the data probe packet of step 1nThe number of "1" in the received bitmap is divided by the length L of the received bitmap, i.e.:
Figure BDA0002850982390000021
wherein Q isnThe link quality of the nth neighbor sensor node and the sensor node of the sender is represented, L represents the length of the receiving bitmap, and B (j) represents the value of the jth data packet in the data receiving bitmap.
Step 3, calculating the link correlation pr；
Calculating link correlation p using a received bitmap of step 1 data probe packetsrExpressing the correlation by adopting conditional probability, and connecting the sensor node fiTo sensor node fnThe correlation is calculated by dividing the number of identical "1" in the received bitmap received from the transmitting sensor node by the length L of the received bitmap, i.e.:
Figure BDA0002850982390000031
wherein p isr(f1...fn) Indicating the link correlation between n links, n indicating the number of neighbor sensor nodes, L indicating the length of the received bitmap,
Figure BDA0002850982390000032
representing a node fiFor the value of the jth data packet in the data bitmap, if the data packet is successfully received
Figure BDA0002850982390000033
Otherwise
Figure BDA0002850982390000034
Step 4, making grouping decision based on minimum ETX
After the information collection of the link quality and the link correlation is completed, each sending sensor node divides all the neighbor sensor nodes into a plurality of groups, specifically as follows:
step 4-1: determining initialization parameters N, K, r
Wherein N represents the number of neighbor sensor nodes, K represents the number of candidate forwarding sets, and r represents the threshold value of the successful data receiving rate DSAR in the candidate forwarding sets. Dividing N neighbor sensor nodes into K groups, wherein K is determined randomly, the number of nodes in each candidate forwarding set is determined by the successful data receiving rate DSAR, and the following steps:
Figure BDA0002850982390000035
setting a threshold r, setting the value of the threshold to be generally 0.8, and actually, it is not significant that the DSAR of each group exceeds 0.8, because the retransmission events can only be reduced but cannot be avoided. When the successful data receiving rate of a certain group reaches the threshold value, the group does not need to add new nodes.
Step 4-2: initial node partitioning within a candidate forwarding set
Firstly, sequencing all neighbor sensor nodes according to link quality, if the number N of the neighbor sensor nodes is more than or equal to K, selecting the first K nodes as initial nodes of K groups, and using the rest (N-K) nodes as candidate forwarding nodes; if the number of the nodes is N < K, the nodes are directly divided into N groups.
Step 4-3: calculating expected transmission times ETX based on the link quality and the link correlation obtained in the step 2 and the step 3, namely:
Figure BDA0002850982390000041
wherein, ETXsRepresenting the expected number of transmissions of the candidate forwarding set S, and m representing the number of nodes in the candidate forwarding set S.
Step 4-4: grouping decisions based on minimum ETX values
In order to fully exert the diversity of receiving the data packets in the candidate forwarding sets, the nodes related to the positive link should be prevented from being divided into the same candidate forwarding set as far as possible. The node with better link quality performance can be known by the calculation formula of the link correlation, and the probability that the nodes have positive correlation with each other is higher. Therefore, when the number of nodes is more than or equal to K, K nodes with the best link quality are selected from N candidate nodes in order according to link quality as initial nodes of K candidate forwarding sets, and the remaining (N-K) nodes determine into which set they are specifically divided according to ETX results calculated from the candidate forwarding sets, specifically as follows:
and calculating the ETX value calculated by each node in the rest (N-K) nodes and K candidate forwarding sets, and adding the node into the corresponding candidate forwarding set with the minimum ETX value after comparing the K ETX values of the node.
Step 5, rescheduling the work scheduling plan of the node
And rescheduling the working plan of the node according to the grouping result so as to meet the application of the opportunistic routing protocol in the low-duty-cycle wireless sensor network environment. The specific scheduling scheme adopts a synchronous awakening mechanism for nodes in the same candidate forwarding set, and adopts an asynchronous awakening mechanism among a plurality of candidate forwarding sets. The method not only can enable the nodes with low correlation to wake up at the same time to undertake the forwarding task of the data packet, but also can reduce the idle monitoring time of the nodes to the maximum extent.
Compared with the prior art, the invention has the following beneficial effects:
the invention provides an optimization method of an opportunistic routing protocol in a low duty ratio network based on link correlation, the algorithm only needs information of neighbor sensor nodes, which brings minimum communication overhead, and the algorithm closes the difference between limited energy of the nodes and the service life requirement of an application program. To our knowledge, we are the first to study the impact of link correlation on opportunistic routing in low duty cycle wireless networks. We also compared the performance and results of the proposed grouped greedy algorithm with the full permutation algorithm, with the best being not achieved, but the inventive algorithm is substantially close to the best, as shown in fig. 7. The result shows that the algorithm is low in time complexity and good in effect, is easy to deploy in the nodes, and can optimize the data transmission condition of the nodes in the wireless network most truly.
Drawings
FIG. 1 is a flow chart of the present invention;
FIG. 2 is a diagram of a simulated network topology of the present invention;
FIG. 3 is an exemplary diagram of a link packet of the present invention;
fig. 4 is a schematic diagram of successful node B grouping into groups 3;
FIG. 5 is a schematic diagram of link packet completion;
FIG. 6 is a diagram of different candidate forwarding sets asynchronously scheduled and synchronously scheduled within a group;
FIG. 7 is a graph comparing the grouping efficiency of the experimental algorithm;
Detailed Description
The invention is further illustrated by the following examples.
As shown in FIG. 1, the implementation steps of the present invention are as follows:
step 1, sending data detection packets to sensor nodes in network
Simulation experiment codes are written in an OMNET + + simulation program, so that sensor nodes in a network send 10 detection packets to each other, and the link quality and the link correlation of the nodes in the network are collected and counted, as shown in FIG. 2.
Step 2, collecting link quality of neighbor sensor nodes in the current network
The link quality is calculated using the reception bitmap of the step 1 data probe packet.
Step 3, calculating link correlation through a receiving bitmap of the data detection packet; calculating expected transmission times ETX by combining the link quality and the link correlation;
step 4, making grouping decision based on minimum ETX
The grouping process is repeated continuously in the transmission path from the starting node to the target node. The situation of the neighbor sensor node of a certain node is shown in fig. 3, where S is the source node, and the rest are the neighbor sensor nodes. The binary bit diagram at the upper right corner represents the reception condition of 10 detection packets in step 1, and the data on the connection line between S and other nodes represents the link quality of the link. The detailed procedure of grouping is illustrated accordingly.
Step 4-1: determining initialization parameters N, K, r
The initial conditions K-3, K-6, r-0.8 were determined.
Step 4-2: initial node partitioning within a candidate forwarding set
And (4) sequencing the neighbor sensor nodes according to the link quality, and taking the nodes A, C and E ranked in the first three as initial nodes of 3 candidate forwarding sets respectively.
Step 4-3: calculating expected transmission times ETX based on the link quality and the link correlation obtained in the step 2 and the step 3
And according to the sequence of the link quality, the ETXs of the node B in the 3 candidate forwarding sets are calculated and compared. Wherein p isr(AB) represents the link correlation of two links of the link S- > A and the link S- > B, and is obtained by the formula
Figure BDA0002850982390000061
Figure BDA0002850982390000062
For candidate forwarding sets { A, B } according to a calculation formula
Figure BDA0002850982390000063
Then
Figure BDA0002850982390000064
Figure BDA0002850982390000065
DSARgroup10.7. Similarly, ETX for the candidate forwarding set { C, B }group2＝1.429，DSARgroup20.7; ETX for candidate forwarding set { E, B }group3＝1.111，DSARgroup3＝0.9。
Step 4-4: grouping decisions based on minimum ETX values
Grouping based on minimum ETX, node B is added to group3 as shown in fig. 4. Meanwhile, when the successful data receiving rate DSAR of the group3 reaches the threshold r, the nodes are not added into the group3 any more unless all groups DSAR reach the threshold and the nodes are not grouped, and at this time, the nodes are grouped again based on ETX.
Steps 4-3 and 4-4 are repeated, node D is added to group1 and node F is added to group2, as shown in fig. 5.
Step 5, rescheduling the work scheduling plan of the node
The re-allocation scheduling scheme, in which the nodes in the same group use synchronous scheduling, and the nodes in different groups use asynchronous scheduling, illustrates the detailed scheduling process according to the example of step 2.
The group1 scheduling scheme is '010', and only works synchronously in the 2 nd time slice; group2 scheduling scheme "001", which works synchronously only in the 3 rd time slice; the group3 scheduling scheme "100" works synchronously only in slice 1 and asynchronously between different groups, as shown in FIG. 6.
And finally, continuously transmitting data by the sensor nodes, and finishing the program when the target node receives the data packet to finish the transmission.
The experimental results are as follows: we evaluated the performance of the algorithm through extensive simulation and a physical wireless test platform consisting of real TelosB nodes. The evaluation result shows that under the condition that the end-to-end time delay is slightly increased, the transmission efficiency and the energy consumption of the opportunistic routing under the low-duty-ratio wireless network are both obviously improved.

Claims (6)

1. The opportunistic routing optimization method based on the link correlation in the low duty ratio network is characterized by comprising the following steps of:
step 1, sensor nodes in a network send data detection packets to each other;
step 2, collecting link quality of neighbor sensor nodes in the current network;
step 3, calculating link correlation through a receiving bitmap of the data detection packet; calculating expected transmission times ETX by combining the link quality and the link correlation;
step 4, making grouping decision based on the minimum ETX;
and 5, rescheduling the work scheduling plan of the node.
2. The opportunistic routing optimization method based on link correlation in the low duty cycle network according to claim 1, characterized in that step 1 is implemented as follows:
the sensor node periodically sends 10 data detection packets to all neighbor sensor nodes, and each data detection packet must have a unique work order D so as to identify whether the data detection packet is lost; the receiving state information of the data detection packet is represented by a binary sequence receiving bitmap, wherein '1' represents that the detection data packet is successfully received, and '0' represents that the detection data packet is lost and is not received by the neighbor sensor node.
3. The opportunistic routing optimization method based on link correlation in the low duty cycle network according to claim 2, characterized in that step 2 is implemented as follows:
calculating link quality Q using the received bitmap of the data probe packet of step 1nThe number of "1" in the received bitmap is divided by the length L of the received bitmap, i.e.:
Figure FDA0002850982380000011
wherein Q isnThe link quality of the nth neighbor sensor node and the sensor node of the sender is represented, L represents the length of the receiving bitmap, and B (j) represents the value of the jth data packet in the data receiving bitmap.
4. The opportunistic routing optimization method based on link correlation in the low duty cycle network according to claim 3, wherein the step 3 is implemented as follows:
calculating link correlation p using a received bitmap of step 1 data probe packetsrExpressing the correlation by adopting conditional probability, and connecting the sensor node fiTo sensor node fnThe correlation is calculated by dividing the number of identical "1" in the received bitmap received from the transmitting sensor node by the length L of the received bitmap, i.e.:
Figure FDA0002850982380000021
wherein p isr(f1...fn) Indicating the link correlation between n links, n indicating the number of neighbor sensor nodes, L indicating the length of the received bitmap,
Figure FDA0002850982380000022
representing a node fiFor the value of the jth data packet in the data bitmap, if the data packet is successfully received
Figure FDA0002850982380000023
Otherwise
Figure FDA0002850982380000024
5. The opportunistic routing optimization method based on link correlation in the low duty cycle network according to claim 4, wherein the step 4 is implemented as follows:
after the information collection of the link quality and the link correlation is completed, each sending sensor node divides all the neighbor sensor nodes into a plurality of groups, specifically as follows:
step 4-1: determining initialization parameters N, K, r
N represents the number of neighbor sensor nodes, K represents the number of candidate forwarding sets, and r represents a threshold value of a data successful receiving rate DSAR in the candidate forwarding sets; dividing N neighbor sensor nodes into K groups, wherein K is determined randomly, the number of nodes in each candidate forwarding set is determined by the successful data receiving rate DSAR, and the following steps:
Figure FDA0002850982380000025
setting a threshold r, wherein the value of the threshold is 0.8, and when the successful data receiving rate of a certain group reaches the threshold, indicating that the group does not need to be added with new nodes;
step 4-2: initial node partitioning within a candidate forwarding set
Firstly, sequencing all neighbor sensor nodes according to link quality, if the number N of the neighbor sensor nodes is more than or equal to K, selecting the first K nodes as initial nodes of K groups, and using the rest (N-K) nodes as candidate forwarding nodes; if the number N of the nodes is less than K, directly dividing the nodes into N groups;
step 4-3: calculating expected transmission times ETX based on the link quality and the link correlation obtained in the step 2 and the step 3, namely:
Figure FDA0002850982380000031
wherein, ETXsRepresenting the expected transmission times of the candidate forwarding set S, and m representing the number of nodes in the candidate forwarding set S;
step 4-4: grouping decisions based on minimum ETX values
In order to fully exert the diversity of receiving data packets in the candidate forwarding sets, nodes related to the positive link are prevented from being divided into the same candidate forwarding set as far as possible; the node with better link quality performance can be known by a calculation formula of the link correlation, and the probability of positive correlation among the nodes is higher; therefore, when the number of nodes is more than or equal to K, K nodes with the best link quality are selected from N candidate nodes in order according to link quality as initial nodes of K candidate forwarding sets, and the remaining (N-K) nodes determine into which set they are specifically divided according to ETX results calculated from the candidate forwarding sets, specifically as follows:
and calculating the ETX value calculated by each node in the rest (N-K) nodes and K candidate forwarding sets, and adding the node into the corresponding candidate forwarding set with the minimum ETX value after comparing the K ETX values of the node.
6. The opportunistic routing optimization method based on link correlation in the low duty cycle network according to claim 5, wherein the step 5 is implemented as follows:
rescheduling the working plan of the node according to the grouping result so as to meet the application of the opportunistic routing protocol in the low duty ratio wireless sensor network environment; the specific scheduling scheme is that a synchronous awakening mechanism is adopted for nodes in the same candidate forwarding set, and an asynchronous awakening mechanism is adopted among a plurality of candidate forwarding sets; the method not only can enable the nodes with low correlation to wake up at the same time to undertake the forwarding task of the data packet, but also can reduce the idle monitoring time of the nodes to the maximum extent.
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Application publication date: 20210423