CN111479304B - Wireless sensor network routing system and method - Google Patents
Wireless sensor network routing system and method Download PDFInfo
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Abstract
The invention relates to a wireless sensor network routing system and a method, wherein the method comprises the following steps: establishing an adjacency graph of each forwarding node; extracting a forwarding set having the largest expected packet progress EPA from the adjacency graph and excluding all hidden nodes therein; selecting an optimal forwarding set, and taking candidate nodes with the maximum probability density-improved PAD as forwarding nodes in the optimal forwarding set; adjusting the number of forwarding nodes in the optimal forwarding set, randomly selecting one node from candidate nodes with higher probability density-increasing PAD values, and removing other nodes which are not connected with the selected node from a candidate node list; checking the number of different members of the forwarding set to achieve the maximum possible value of EEPA for expected energy and packet progress; and forwarding the data packet.
Description
Technical Field
The invention belongs to the field of wireless sensor networks, and particularly relates to a wireless sensor network routing system and method applicable to underwater.
Background
The wireless sensor network technology is becoming mature day by day, for example, the water resource can be monitored through the wireless sensor network, the data collected by arranging the wireless sensor network on the water surface is single, and the evaluation of the water resource not only needs basic data such as water quality and water level, but also needs to monitor underwater ecology such as underwater topography, temperature of different depths, aquatic life and the like, so that the Underwater Wireless Sensor Network (UWSN) becomes the best monitoring means.
The underwater wireless sensor network directly arranges the acquisition nodes in an underwater environment, cannot transmit electromagnetic waves underwater, needs a special underwater sound transmission device, and is also influenced by many factors such as waves, vortexes, noises, various aquatic organisms and rocks in the data transmission process, so that the realization of effective data transmission is a technical problem.
Disclosure of Invention
The invention aims to provide a wireless sensor network routing method which can be applied underwater and can realize underwater acoustic modulation and demodulation with the communication distance reaching tens of meters.
The routing method of the wireless sensor network provided by the invention comprises the following steps: establishing an adjacency graph of each forwarding node; extracting a forwarding set having the largest expected packet progress EPA from the adjacency graph and excluding all hidden nodes therein; selecting an optimal forwarding set, and taking candidate nodes with the maximum probability density-improved PAD as forwarding nodes in the optimal forwarding set; adjusting the number of forwarding nodes in the optimal forwarding set, randomly selecting one node from candidate nodes with higher probability density-increasing PAD values, and removing other nodes which are not connected with the selected node from a candidate node list; checking the number of different members of the forwarding set to achieve the maximum possible value of EEPA for expected energy and packet progress; and forwarding the data packet.
In the above method, the expected packet progress EPA is:
where Φ is a subset of nodes created by the forwarding node that does not contain hidden nodes, pikIs the probability of transmission, Pi0＝0，
βikThe factor for normalization is based on the sensor node RiAnd each candidate node mkThe relative depth difference between them.
In the above method, the probability increasing density PAD is:
PADG(C)(nu)＝Piu×βiu×degG(C)(nu)
in the formula, nuIs a candidate node containing a hidden node, C is a sensor node RiAvailable candidate node L (R)i) G (C) a generalized subgraph of candidate nodes, degG(C)(nu) Is nuDegree of C with respect to G (C), PiuAnd betaiuAre respectively a node RiAnd nuPacket delivery probability and packet progression in between.
In the above method, the number of forwarding nodes in the optimal forwarding set is adjusted by the following steps:
randomly selecting a node from the list RCL of the restriction candidate nodes and adding the node into the group graph;
all nodes adjacent to the newly selected node are kept in the candidate node list, and other nodes are removed from the candidate node list;
after each node is selected and the candidate node list is modified, the PAD values of all the remaining candidate nodes are recalculated;
the above process is repeated until there is no node in the candidate node list.
In the above method, the expected energy and packet progression EEPA is:
where μ and ρ are defined as weight coefficients for EPA and energy, respectively, EPA (F, j) and E (F, j) being expected packet progress and energy consumption of the forwarding set, respectivelymaxMaximum value of EPA, EmaxFor maximum energy consumption, F represents the sensor node RiJ-1, 2, r, where r-F, r represents the number of nodes in F.
The invention also provides a wireless sensor network routing system, comprising: an adjacency graph establishing module, configured to establish an adjacency graph for each forwarding node; a forwarding set determining module, configured to extract a forwarding set with the largest expected packet progress EPA from the adjacency graph, and exclude all hidden nodes therein; the optimal forwarding set selection module is used for taking the candidate node with the maximum probability density-improved PAD as the forwarding node in the optimal forwarding set; a forwarding node number adjusting module, configured to adjust the number of forwarding nodes in the optimal forwarding set, randomly select a node from candidate nodes with a higher probability increase density PAD value, and remove other nodes not connected to the selected node from a candidate node list; the energy efficiency and routing efficiency balancing module is used for checking different member numbers of the forwarding set so as to realize the maximum possible value of EEPA (energy efficiency and routing efficiency) for expecting energy and data packet progress; and the data packet forwarding module is used for forwarding the data packet.
In the above system, the expected packet progress EPA is:
where Φ is a subset of nodes created by the forwarding node that does not contain hidden nodes, pikIs the probability of transmission, Pi0＝0，
βikThe factor for normalization is based on the sensor node RiAnd each candidate node mkThe relative depth difference between them.
In the above system, the probability increasing density PAD is:
PADG(C)(nu)＝Piu×βiu×degG(C)(nu)
in the formula, nuIs a candidate node containing a hidden node, C is a sensor node RiAvailable candidate node L (R)i) G (C) a generalized subgraph of candidate nodes, degG(C)(nu) Is nuDegree of C with respect to G (C), PiuAnd betaiuAre respectively a node RiAnd nuPacket delivery probability and packet progression in between.
In the above system, the forwarding node number adjusting module adjusts the number of forwarding nodes in the optimal forwarding set by the following steps:
randomly selecting a node from the list RCL of the restriction candidate nodes and adding the node into the group graph;
all nodes adjacent to the newly selected node are kept in the candidate node list, and other nodes are removed from the candidate node list;
after each node is selected and the candidate node list is modified, the PAD values of all the remaining candidate nodes are recalculated;
the above process is repeated until there is no node in the candidate node list.
In the above system, the expected energy and packet development EEPA is:
where μ and ρ are defined as weight coefficients for EPA and energy, respectively, EPA (F, j) and E (F, j) being expected packet progress and energy consumption of the forwarding set, respectivelymaxMaximum value of EPA, EmaxFor maximum energy consumption, F represents the sensor node RiJ-1, 2, r, where r-F, r represents the number of nodes in F.
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The present invention will be described in further detail with reference to the accompanying drawings and specific embodiments.
Fig. 1 shows a system configuration diagram of a hydroacoustic modem.
Fig. 2 shows a wireless sensor network routing flow diagram.
Detailed Description
Fig. 1 shows a system structure of an underwater acoustic modem, which comprises an underwater transducer, an analog transceiver and a digital hardware platform.
The underwater transducer comprises a listening device and a transmitter, and is used for sending and receiving accurate modulation signals at high frequency and high symbol rate, and simulating a transceiver to filter and amplify the signals; the digital hardware platform assumes the processing and control functions of the modem.
The underwater transducer includes a listening device and a transmitter. The listening device may be C304XR, developed by Cetacean, and the transmitter may be formed of two layers of PVDF 110 μm thick, each layer being a 2cm diameter piston structure. The output signal of the listening device is converted by the filter, amplifier and signal waveform processor in the analog transceiver. A current-voltage converter is arranged at the front end of the amplifier, and an output voltage with a peak value of 3V can be obtained. The analog transceiver includes a power amplification module for amplifying the modulated signal before the signal is sent to the ultrasonic transducer. The digital hardware platform can adopt an FPGA Spartan3 chip to bear the processing and control functions of the modem. An analog-to-digital converter (ADC) (e.g., AD9244) and an analog-to-digital converter (DAC) (e.g., DAC904) are provided between the analog transceiver and the digital hardware platform.
In this embodiment, a Direct Digital Synthesizer (DDS) may be used to generate a 1MHz sine carrier, and a small signal sent from the RS232 controls a sine wave generator of the FPGA.
The routing method of the wireless sensor network comprises the following steps:
step 1, constructing an underwater sound propagation model
1-1, the path loss or attenuation model is:
A(d,f)＝A0dkα(f)d
wherein d is the crossing distance, f is the signal frequency, A0Denotes a normalized constant, k is a geometric diffusion factor, which is generally set to 1.5, and the absorption coefficient α (f) is defined by Thorp's equation.
1-2, according to the attenuation model, obtaining a signal-to-noise ratio model:
in the formula, pr (f) and pn (f) respectively represent the transmission power of the forwarding node with the frequency f and the underwater environment noise.
1-3, the model of the environmental noise in the underwater environment is:
PN(f)＝PNt(f)+PNs(f)+PNw(f)+PNth(f)
in the formula, PNt(f) Is turbulent flow, PNs(f) For shipping, PNw(f) Is a wave, PNth(f) Is thermal energy.
Step 2, forming an adjacency graph and selecting an optimal forwarding set, wherein the step is realized by the following scheme:
2-1, each forwarding node builds its adjacency graph with the information provided by the beacons, extracts from the adjacency graph a forwarding set with the largest expected packet progress (EPA), and estimates the progress of each packet relayed by the forwarding node. Suppose a sensor node RiTo send a data packet, L (R), to Sink Si)＝{n1,n2,...,ncDenotes RiThe available candidate nodes (neighbor nodes with lower hop count values) are sorted in increments according to depth value.
Let c ═ L (R)i) L represents L (R)i) The number of candidate nodes in (1). Node RiThe packet delivery probability of its neighboring nodes is known. For example, if RiReceives a signal from nk1. ltoreq. k. ltoreq.c, RiPair-wise distance (R) may be calculated based on the received signal strength or the usage arrival time of the beaconi,nk). Φ is a node subset created by the forwarding node that does not contain hidden nodes, { m ═ m1,m2,...,ml}，1≤l≤c，mkAs candidate nodes not containing hidden nodes, c is the number of candidate nodes, the subset being based on formula
In (b) gives beta (interval [0,1]]Normalized to α), where α represents the depth difference between the depth of the sender and the depth of the receiver: and (4) descending the sequence. The EPA of the subset Φ created by the forwarding node is computed as:
in the formula, pikIs the probability of transmission, Pi0＝0，
βikThe factor for normalization is based on the node RiAnd each candidate node mkThe relative depth difference between them. One forwarding set with the largest EPA value is extracted from the adjacency graph, excluding all hidden nodes therein.
2-2, selecting the optimal forwarding set
If a candidate node is able to maximize the probability increase density PAD value, it means that the node is in an ideal location for packet delivery and packet progression, and has high connectivity to the remaining other candidate nodes. Candidate node n comprising hidden nodeuThe calculation method of the probability increasing density PAD comprises the following steps:
PADG(C)(nu)＝Piu×βiu×degG(C)(nu)
wherein, L (R) is providedi)＝{n1,n2,...,ncDenotes RiC ═ L (R) of the available candidate nodes (neighbor nodes with low hop count values), c ═ L (R)i) L represents L (R)i) C is L (R)i) G (C) is the generalized subgraph. At each step of the build phase, a node is randomly selected from the candidate nodes having the higher PAD value, and the other nodes not connected to the selected node are removed from the list of candidate nodes. Thus, at each step, a clique graph is obtained. If deg.fG(C)(nu) Is nuDegree of C with respect to G (C), PiuAnd betaiuAre respectively a node RiAnd nuPacket delivery probability and packet progression in between.
Step 3, adjusting the number of the forwarding nodes in the optimal forwarding set
Step 3-1 randomly selects one node from the candidate nodes having the higher probability of increasing the density PAD value, and removes other nodes from the candidate node list that are not connected to the selected node.
And C is a candidate node set. At the beginning, L (R)i) All nodes inAll are considered as candidate nodes, i.e. C ═ L (R)i). In addition, there is a list RCL of constrained candidate nodes, i.e. all candidate nodes with higher PAD values in the subgraph g (c) including the generalised candidate nodes. Candidate node nuC is considered to have a higher PAD value if PAD is relative to G (C)G(C)(nu) At least satisfies deltamin+λ(δmax+δmin) The method comprises the following steps:
δmin＝min{PADG(C)(nu)|nu∈C}
in the formula, λ is a real parameter in the interval [0,1 ]. Among the candidate nodes in the RCL, one node is randomly selected and added to the clique graph. All nodes adjacent to the newly selected node will remain in the candidate node list from which other nodes will be removed. After each node is selected and the candidate node list is modified, the PAD values of all the remaining candidate nodes are recalculated as new. This process continues until there are no nodes in the candidate list.
Step 3-2 introduces a new metric, expected energy and packet progress (EEPA), to balance energy efficiency and routing efficiency. Let EPA (F, j) and E (F, j) be the expected packet progress and energy consumption of the forwarding set, respectively, to obtain the maximum EPA valuemaxAnd maximum value of energy consumption EmaxAll nodes, i.e. EPA (F, R) and E (F, R), may be involved in the forwarding set, where R ═ F |, where F denotes RiR denotes the number of nodes in F, EEPA may be defined as:
in the formula, μ and ρ are defined as weight coefficients of EPA and energy, respectively. μ and ρ may be defined according to the desired standard and density of the network. The number of different members of the forwarding set is checked, and EEPA may be checked for j 1, 2.
And 4, calculating the holding time of each candidate node before forwarding the data packet.
Let F represent RiIncluding all nodes used in opportunistic data forwarding. Let r ═ F | denote the number of nodes in F. The forwarding node decides which candidate nodes should join packet forwarding. The header of the packet contains F (R)i) All member IDs of (1). The receiving node should be in the forwarding set of the sender to accept the data packet; otherwise, the receiving node will discard the packet.
After the forwarding candidate node receives the data packet, a forwarding timer is set. With the retransmission procedure, if a node receives a duplicate packet, it will set a new retention timer for that packet again.
Before forwarding the candidate node, the forwarding timer value of the node with the highest priority is the smallest, if the data packet is relayed by the node, other candidate nodes with lower priorities should discard the data packet after hearing the transmission of the data packet.
If all higher priority nodes in the forwarding set fail to receive or relay packets, the lower priority candidate node may become a forwarding node.
A wireless sensor network routing system, comprising: an adjacency graph establishing module, configured to establish an adjacency graph for each forwarding node; a forwarding set determining module, configured to extract a forwarding set with the largest expected packet progress EPA from the adjacency graph, and exclude all hidden nodes therein; the optimal forwarding set selection module is used for taking the candidate node with the maximum probability density-improved PAD as the forwarding node in the optimal forwarding set; a forwarding node number adjusting module, configured to adjust the number of forwarding nodes in the optimal forwarding set, randomly select a node from candidate nodes with a higher probability increase density PAD value, and remove other nodes not connected to the selected node from a candidate node list; the energy efficiency and routing efficiency balancing module is used for checking different member numbers of the forwarding set so as to realize the maximum possible value of EEPA (energy efficiency and routing efficiency) for expecting energy and data packet progress; and the data packet forwarding module is used for forwarding the data packet.
The calculation method of the expected packet progress EPA, the probability increase density PAD, the expected energy and packet progress EEPA, and the number adjustment method of forwarding nodes in the optimal forwarding set and packet forwarding refer to the above steps 2 to 4.
A modem comprising a processor and a memory, the processor for executing the following program modules stored in the memory:
an adjacency graph establishing module, configured to establish an adjacency graph for each forwarding node; a forwarding set determining module, configured to extract a forwarding set with the largest expected packet progress EPA from the adjacency graph, and exclude all hidden nodes therein; the optimal forwarding set selection module is used for taking the candidate node with the maximum probability density-improved PAD as the forwarding node in the optimal forwarding set; a forwarding node number adjusting module, configured to adjust the number of forwarding nodes in the optimal forwarding set, randomly select a node from candidate nodes with a higher probability increase density PAD value, and remove other nodes not connected to the selected node from a candidate node list; the energy efficiency and routing efficiency balancing module is used for checking different member numbers of the forwarding set so as to realize the maximum possible value of EEPA (energy efficiency and routing efficiency) for expecting energy and data packet progress; and the data packet forwarding module is used for forwarding the data packet.
The calculation method of the expected packet progress EPA, the probability increase density PAD, the expected energy and packet progress EEPA, and the number adjustment method of forwarding nodes in the optimal forwarding set and packet forwarding refer to the above steps 2 to 4.
Claims (4)
1. A wireless sensor network routing method is characterized by comprising the following steps:
establishing an adjacency graph of each forwarding node;
extracting a forwarding set having a maximum expected packet progress EPA from the adjacency graph and excluding all hidden nodes therein, the expected packet progress EPA being:
where Φ is a subset of nodes created by the forwarding node that does not contain hidden nodes, pikIs the probability of transmission, Pi0＝0，
βikThe factor for normalization is based on the sensor node RiAnd each candidate node mkThe relative depth difference therebetween;
selecting an optimal forwarding set, and taking a candidate node with the maximum probability density-improved PAD as a forwarding node in the optimal forwarding set, wherein the probability density-improved PAD is as follows:
PADG(C)(nu)＝Piu×βiu×degG(C)(nu)
in the formula, nuIs a candidate node containing a hidden node, C is a sensor node RiAvailable candidate node L (R)i) G (C) a generalized subgraph of candidate nodes, degG(C)(nu) Is nuDegree of C with respect to G (C), PiuAnd betaiuAre respectively a node RiAnd nuPacket delivery probability and packet progression between;
adjusting the number of forwarding nodes in the optimal forwarding set, randomly selecting one node from candidate nodes with higher probability density-increasing PAD values, and removing other nodes which are not connected with the selected node from a candidate node list;
checking the number of different members of the forwarding set to achieve the maximum possible value of expected energy and packet progress EEPA:
where μ and ρ are defined as weight coefficients for EPA and energy, respectively, EPA (F, j) and E (F, j) being expected packet progress and energy consumption of the forwarding set, respectivelymaxMaximum value of EPA, EmaxFor maximum energy consumption, F represents the sensor node RiJ 1,2, r, where r | F | and r denotes the number of nodes in F;
and forwarding the data packet.
2. The method of claim 1, wherein the number of forwarding nodes in the optimal forwarding set is adjusted by:
randomly selecting a node from the list RCL of the restriction candidate nodes and adding the node into the group graph;
all nodes adjacent to the newly selected node are kept in the candidate node list, and other nodes are removed from the candidate node list;
after each node is selected and the candidate node list is modified, the PAD values of all the remaining candidate nodes are recalculated;
the above process is repeated until there is no node in the candidate node list.
3. A wireless sensor network routing system, comprising:
an adjacency graph establishing module, configured to establish an adjacency graph for each forwarding node;
a forwarding set determining module, configured to extract a forwarding set with a largest expected packet progress EPA from the adjacency graph, and exclude all hidden nodes therein, where the expected packet progress EPA is:
where Φ is a subset of nodes created by the forwarding node that does not contain hidden nodes, pikIs the probability of transmission, Pi0＝0，
βikThe factor for normalization is based on the sensor node RiAnd each candidate node mkThe relative depth difference therebetween;
an optimal forwarding set selection module, configured to use a candidate node with a maximum probability density-increasing PAD as a forwarding node in an optimal forwarding set, where the probability density-increasing PAD is:
PADG(C)(nu)＝Piu×βiu×degG(C)(nu)
in the formula, nuIs a candidate node containing a hidden node, C is a sensor node RiAvailable candidate node L (R)i) G (C) a generalized subgraph of candidate nodes, degG(C)(nu) Is nuDegree of C with respect to G (C), PiuAnd betaiuAre respectively a node RiAnd nuPacket delivery probability and packet progression between;
a forwarding node number adjusting module, configured to adjust the number of forwarding nodes in the optimal forwarding set, randomly select a node from candidate nodes with a higher probability increase density PAD value, and remove other nodes not connected to the selected node from a candidate node list;
an energy efficiency and routing efficiency balancing module, which checks the number of different members of the forwarding set to achieve the maximum possible value of the expected energy and packet progress EEPA, where the expected energy and packet progress EEPA is:
where μ and ρ are defined as weight coefficients of EPA and energy, EPA (F, j) ande (F, j) expected packet progress and energy consumption, EPA, respectively, for the Forwarding setmaxMaximum value of EPA, EmaxFor maximum energy consumption, F represents the sensor node RiJ 1,2, r, where r | F | and r denotes the number of nodes in F;
and the data packet forwarding module is used for forwarding the data packet.
4. The system of claim 3, wherein the forwarding node number adjustment module adjusts the number of forwarding nodes in the optimal forwarding set by:
randomly selecting a node from the list RCL of the restriction candidate nodes and adding the node into the group graph;
all nodes adjacent to the newly selected node are kept in the candidate node list, and other nodes are removed from the candidate node list;
after each node is selected and the candidate node list is modified, the PAD values of all the remaining candidate nodes are recalculated;
the above process is repeated until there is no node in the candidate node list.
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