CN103747498A - Direction angle-based wireless sensor network routing void optimization method - Google Patents
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Abstract
The invention puts forward a direction angle-based wireless sensor network routing void optimization method which belongs to the technical field of wireless sensor networks (WSNs). The method judges a routing void node by using the distance between any two nodes which is less than a communication radius R; with the void node as a center, a direction angle-based directional neighboring node set of the void node is constructed; the next-hop cost function of the neighboring nodes is calculated; according to the next-hop cost function, the priority levels of next-hop nodes of the routing void are divided; by adopting random choice, a node is chosen from the high-priority node set to serve as the next hop of the void node; finally, the paths near the void are reduced and optimized, the number of the nodes on the paths is reduced, and thereby the direction angle-based wireless sensor network routing void optimization method is fulfilled. The direction angle-based wireless sensor network routing void optimization method not only can handle the problem of void routing, but also meets the QoS (Quality of Service) requirement of WSNs; the direction angle-based wireless sensor network routing void optimization method is simple and feasible and has a remarkable effect in solving the problem of voids.
Description
Technical field
The present invention relates to a kind of radio sensing network route cavity optimization method based on orientation angle, belong to wireless sensor network (WSNs) technical field.
Background technology
The calculating of wireless sensor network (WSNs) node, storage, communication capacity is limited, traditional fixed network and the Routing Protocol of mobile ad-hoc network all can not be effectively applied to WSNs, the Routing Protocol of research WSNs is significant, Routing Protocol can be divided into plurality of classes by different sorting techniques, geographic routing is wherein used widely, in geographic routing, node is known the positional information of oneself by GPS or location algorithm, when data need to forward, node is according to the partial network information of its grasp, the greedy pass-through mode of service range, chosen position approaches the neighbor node of destination node more as down hop forward node, along shorter path transmission data.Due to the greedy pass-through mode forwarding data of its service range, inevitably there will be the problem of greedy retransmission failure, the node of retransmission failure becomes empty node, the definition of route cavity node: when setting up path to destination node service range greedy algorithm, the neighbor node that node meeting chosen position approaches destination node is more as down hop forward node, but when there is not the nearer node of distance objective node in neighbor node, this node is empty node.Therefore the settlement mechanism of empty problem indicates the validity of Routing Protocol.
Route cavity treatment mechanism is vital for geographic routing agreement efficiently, during the empty treatment mechanism of design route, should accomplish as far as possible that processing empty sensor node should lack as much as possible, self just can complete best empty node empty processing; The extra energy expense that route cavity treatment mechanism is brought should be lacked as much as possible, improves capacity usage ratio; Utilize a small amount of partial network information to complete empty processing, the extensibility of Routing Protocol is not exerted an influence; Approach as much as possible shortest path.
Summary of the invention
For the route cavity problem of WSNs, the object of the present invention is to provide a kind of radio sensing network route cavity optimization method based on orientation angle.
Technical scheme of the present invention is,
A radio sensing network route cavity optimization method based on orientation angle, the method step is:
Step 1: judge route cavity node;
First calculate every two internodal distances, conventionally utilize communication radius to determine the neighbor node of each node, two internodal distances are less than the i.e. neighbor node each other of certain numerical value, and each node has the neighbor node set of self; Calculate the distance of each nodal distance destination node, destination node is generally known, set up in the process of path, if while there is not the nearer node of compared with this node distance objective node while choosing next-hop node in neighbor node, this node is empty node;
Step 2: build the set of direction neighbor node centered by empty node;
Centered by empty node, with positive and negative 120 degree of empty node and destination node line, rebuild the direction neighbor node set { Node of empty node
i, in set, element number is n, the node of the n in set as after the alternative node of calculation cost function; When the angle of neighbor node and empty node line, empty node and destination node line is less than 120 while spending, in step 1, according to the neighbor node of the determined empty node of communication radius R, belong to direction neighbor node set { Node
i; That is,
When
time, N
i+1∈ { Node
i;
Wherein, N
ifor empty node, N
i+1for the determined empty node N of communication radius R in step 1
ineighbor node,
for the angle of neighbor node and empty node line, empty node and destination node line;
Step 3: the down hop cost function of calculated direction neighbor node;
Each node calculation cost function in pair set, described cost function is:
Wherein, L (N
i, D) and represent empty nodal distance destination node distance, L (N
i+1, D) and expression set { Node
iin node to the distance of destination node, the value of cost function is always greater than 1.To the C calculating
iascending sequence, builds set { C
i, calculate { C
imedian:
C
mid＝mid{C
i}，
By C
midas the standard of follow-up judgement priority level;
Step 4: divide route cavity next-hop node priority level according to down hop cost function;
The C calculating according to previous step
middivide empty node direction neighbor node preferentially choose grade, priority level is divided to 2 grades, if the C of node
ivalue is less than C
mid, node belongs to high priority { level
i=1}; Otherwise node belongs to low priority { level
i=0};
Step 5: determine next-hop node from the random selection of priority node set;
According to priority level { level
ichoose at random the next-hop node of empty node, the priority node set { level establishing from step 4
iin=1}, choose at random the next-hop node of empty node;
Step 6: path is simplified to optimize and reduced node number on path;
In the process of setting up path, all nodes on path are carried out to the numbering by 1 beginning, source node be numbered 1, the next-hop node of source node is numbered 2, back to back next-hop node is numbered 3, by that analogy, the node serial number on path is not 0, simplify optimization setting up after path success, optimization principles is to start to select to number maximum node directly as next-hop node neighbor node from source node, from next-hop node, according to same principle, simplify backward optimization afterwards, until destination node, establish final path, the node of being simplified is not due to on final path, numbering sets to 0 again,
Like this, obtain the radio sensing network route cavity optimization method based on orientation angle, the method has solved empty problem and has met the path of wireless sensor network QoS demand.
The invention has the beneficial effects as follows: simple possible of the present invention, can effectively solve empty routing issue, also met the QoS demand of WSNs.
Accompanying drawing explanation
Fig. 1 is flow chart of the present invention.
Fig. 2 is the principle schematic that the present invention introduces cost function while selecting empty node down hop.
Fig. 3 is the principle schematic that optimization is simplified in path.
Fig. 4 is the present invention selected path topology figure while running into empty node.
Fig. 5 simplifies to optimize the final topological diagram of rear path.
Fig. 6 is that the present invention and TPGF method are processed the node number contrast schematic diagram after empty problem.
Fig. 7 is that the present invention and TPGF method are processed the capacity usage ratio contrast schematic diagram after empty problem.
Embodiment
Below in conjunction with drawings and Examples, the present invention is elaborated.
Fig. 1 is flow chart of the present invention.As shown in Figure 1, a kind of radio sensing network route cavity optimization method based on orientation angle, the method step is, comprises the following steps:
Step 1: differentiate route cavity node, first utilize communication radius to determine the neighbor node of each node.We get communication radius R=60, unit: rice (m), any two internodal distances are less than the i.e. neighbor node each other of 60m, calculate again the distance of each nodal distance destination node, destination node is generally known, set up in the process of path, if while there is not the nearer node of compared with this node distance objective node while choosing next-hop node in neighbor node, this node is empty node;
Step 2: centered by empty node, with positive and negative 120 degree of empty node and destination node line, rebuild the direction neighbor node set of empty node, when
time, N
i+1∈ { Node
i, wherein, N
ifor empty node, N
i+1for the determined empty node N of communication radius R in step 1
ineighbor node,
for the angle of neighbor node and empty node line, empty node and destination node line; Element number n in this set is less than or equal to the neighbor node number of the empty node calculating by communication radius in step 1.In these nodes, choose the next-hop node of empty node.
Step 3: introduce cost function
fig. 2 is the principle schematic that the present invention introduces cost function while selecting empty node down hop, and as shown in Figure 2, in figure, Ni is empty node, must, in positive and negative 120 degree of angle, select down hop, calculates N
i+1a, N
i+1b, N
i+1c and N
i+1the cost function value of d, by set of computations { Node
icost function after, then obtain median C
mid, as the threshold value of subsequent divided priority.
Step 4: with C
midfor threshold value is by { Node
iin the priority of node be divided into 2 grades, { level
i=1} and { level
i=0}, as calculated N in rear Fig. 2
i+1a, N
i+1b belongs to high priority { level
i=1}, and N
i+1c and N
i+1d belongs to low priority { level
i=0}.
Step 5: choose at random { Node
iin a certain node as the down hop of empty node.At priority node N
i+1a, N
i+1between b, choose at random.
Step 6: simplify path node number, path optimizing;
As shown in Figure 3, Fig. 3 is the principle schematic that optimization is simplified in path, by source node S, to destination node D, sets up path, and path is S → a → b → c, and 1, a that is numbered of S is that 2, b is that 3, c is 4.A, b, c is the neighbor node of S, therefore directly chooses the down hop of the maximum c of numbering as S, starts to simplify and optimize until destination node according to identity principle afterwards from c.
[embodiment]
Adopt MATLAB as emulation tool, simulation parameter is set as follows:
Topology scope is 600 × 400, and destination node is located at (0,0) and locates, and source node is located at distance objective node farthest, and the primary power of node is all made as erg-ten, and node does not have mobility.
As shown in Figure 4, Fig. 4 is the present invention selected path topology figure while running into empty node (for setting up the topological diagram in path in the node number situation that is n=150).Afterwards according to the present invention, a kind of radio sensing network route cavity optimization method based on orientation angle, the method step is:
1) judge empty node, with greedy algorithm select next-hop node set up path, until node N
i; Node N
iapart from destination node, be 316.51m, be all less than node N
ineighbor node A, B, C, D, E is apart from the distance of destination node, its value is respectively 346.25m, 370.8m, 370.59m, 347.92m, 381.98, node N
ibecome route cavity node;
2) build the set of direction neighbor node, according to empty node N
ibe less than 120 degree with the angle of destination node line, the empty node N calculating
ithe set of direction neighbor node comprise node A, B, C, D;
3) the cost function set of calculated direction neighbor node, and sequence from small to large.A, B, C, the cost function value C that D calculates
ibe respectively 1.09,1.17,1.172,1.1, the set { C of structure
ibe:
{ 1.06,1.1,1.17,1.172}; Calculate median C
midbe 1.123;
4) according to the threshold value C calculating
mid, by A, B, C, D is divided into two priority, due to A, the C of D
ivalue is less than C
mid, therefore A, D ∈ { level=1}; B, C ∈ { level=0}.
5), at A, in the middle of two points of D, the random next-hop node of selecting empty node, has selected the next-hop node of D point as empty node.
6) the final path of determining according to path optimization's principle of parsimony afterwards as shown in Figure 5.(Fig. 5 simplifies to optimize the final topological diagram of rear path).From Fig. 5, can obviously find out according to the path the inventive method calculating and walk around empty node N
i.
Path had both solved empty problem, had met the QoS demand of wireless sensor network simultaneously.
Fig. 6 is that the present invention and TPGF method are processed the node number contrast schematic diagram after empty problem.In Fig. 6, showed the curve chart that the final path node of the present invention and TPGF calculating path node change along with node number, concrete data are as shown in table 1:
Table 1
| |
150 | 160 | 170 | 180 | 190 | 200 |
| TPGF | 21 | 19 | 21 | 20 | 21 | 20 |
| The inventive method | 19 | 18 | 19 | 19 | 20 | 19 |
On path node number and the path delay of time proportional, Statistical Principles is shown below:
D
end-to-end=D
transmission delay+ D
other factors,
Wherein, D
transmission delaybetween main dactylus point, send the time delay of data, and D
other factorsmain expression MAC layer time delay and other time delay, unification is added up by 20ms, and the inventive method has reduced respectively 9.5%, 5.3%, 4.5%, 5%, 4.8%, 5% compared with TPGF time delay.
Fig. 7 is that the present invention and TPGF method are processed the capacity usage ratio contrast schematic diagram after empty problem.The method of statistics energy has a lot, during now with first node death, stops, and uses dump energy divided by gross energy, i.e. capacity usage ratio.Energy model adopts and transmits and receives the energy that machine processing of circuit 1 Bit data consumes is 50J
-9, free space model transmits and receives dynamo-electric road direction unit are, and to launch the energy that 1 Bit data consumes be 100J
-12, data packet length 1600 bits.Final energy utilance is as shown in table 2:
Table 2
| |
150 | 160 | 170 | 180 | 190 | 200 |
| TPGF | 0.2832 | 0.25 | 0.2414 | 0.2364 | 0.2387 | 0.2723 |
| The inventive method | 0.3069 | 0.2725 | 0.2488 | 0.262 | 0.2492 | 0.2893 |
In sum, the present invention had both met that empty processing rear path node number is few, and energy expense is few, the requirement that utilance is high, and simple.
The present invention can process empty routing issue, has also met the QoS demand of WSNs; Simple possible, in the empty problem of solution, effect is remarkable.
The above; only for preferably embodiment of the present invention, but protection scope of the present invention is not limited to this, is anyly familiar with in technical scope that those skilled in the art disclose in the present invention; the variation that can expect easily or replacement, within all should being encompassed in protection scope of the present invention.Therefore, protection scope of the present invention should be as the criterion with the protection range of claim.
Claims (2)
1. the cavity of the radio sensing network route based on an orientation angle optimization method, is characterized in that, the method comprises the following steps:
Step 1: service range greedy algorithm is set up the path that arrives destination node, judges route cavity node;
Set communication radius R, any two internodal distances are less than communication radius R, two nodes neighbor node each other, and each node has the neighbor node set of self; Calculate again the distance of all nodal distance destination node D; Set up in the process of path, if while there is not the nearer node of compared with this node distance objective node D while choosing next-hop node in neighbor node, this node is empty node;
Step 2: build the set of direction neighbor node centered by empty node;
Centered by empty node, with positive and negative 120 degree of empty node and destination node line, rebuild the direction neighbor node set { Node of empty node
i, wherein, when the angle of neighbor node and empty node line, empty node and destination node line is less than 120 while spending, in step 1, according to the neighbor node of the determined empty node of communication radius R, belong to direction neighbor node set { Node
i, that is,
When
time, N
i+1∈ { Node
i,
Wherein, N
i+1for the determined empty node N of communication radius R in step 1
ineighbor node,
for the angle of neighbor node and empty node line, empty node and destination node line;
Set { Node
iin element number n be less than or equal to the neighbor node number of the empty node calculating by communication radius R in step 1;
Step 3: the down hop cost function C of calculated direction neighbor node
i;
Described cost function
l (N
i, D) and represent that empty node arrives the distance of destination node, L (N
i+1, D) and represent the set { Node that again establishes in step 2
iin direction neighbor node to the distance of destination node;
By set of computations { Node
icost function C
i, and to C
iafter ascending sequence, build set { C
i, then calculate median C
mid, as the threshold value of subsequent divided priority;
Step 4: according to down hop cost function C
idivide route next jump node priority level;
With C
midfor threshold value is by { Node
iin the priority of node be divided into 2 ranks: { level
i=1} and { level
i=0}, if cost function value C
ibe less than median C
mid, node belongs to high priority { level so
i=1}; Otherwise node belongs to low priority { level
i=0};
Step 5: adopt random selection mode from priority node set { level
iin=1}, determine next-hop node;
According to priority level { level
ichoose at random the next-hop node of empty node, the priority node set { level establishing from step 4
iin=1}, choose at random the next-hop node of empty node;
Step 6: optimization is simplified in path, reduces node number on path;
In the process of setting up path, all nodes on path are carried out to the numbering by 1 beginning, source node be numbered 1, the next-hop node of source node is numbered 2, back to back next-hop node is numbered 3, by that analogy, the node serial number on path is not 0, simplify optimization setting up after path success, optimization principles is to start to select to number maximum node directly as next-hop node neighbor node from source node, from next-hop node, according to same principle, simplify backward optimization afterwards, until destination node, establish final path, the node of being simplified is not due to on final path, numbering sets to 0 again,
Like this, obtain a path that has solved empty problem and met wireless sensor network QoS demand, obtained the radio sensing network route cavity optimization method based on orientation angle.
2. a kind of radio sensing network route cavity optimization method based on orientation angle according to claim 1, is characterized in that described communication radius R=60, unit: rice.
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| CN108650680A (en) * | 2018-03-07 | 2018-10-12 | 东南大学 | A kind of wireless sensor network cavity restorative procedure based on direction of arrival |
| CN113469813A (en) * | 2021-07-20 | 2021-10-01 | 华北电力大学 | Regional carbon quota transaction system and method for power enterprise based on block chain |
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