CN102300282B - Wireless sensor, actuator network and shortest time delay routing method of actuator network - Google Patents
Wireless sensor, actuator network and shortest time delay routing method of actuator network Download PDFInfo
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- CN102300282B CN102300282B CN201110294885.7A CN201110294885A CN102300282B CN 102300282 B CN102300282 B CN 102300282B CN 201110294885 A CN201110294885 A CN 201110294885A CN 102300282 B CN102300282 B CN 102300282B
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Abstract
The invention discloses a wireless sensor, an actuator network and a shortest time delay routing method of the actuator network. The network comprises a plurality of sensing nodes, a plurality of converging nodes and a plurality of actuating nodes dispersedly deployed in a target area, wherein all converging nodes move in the entire network; the moving path Tj of every converging node is independent; routing of each moving path Tj is designed with a frog leaping algorithm; when a converging node approaches a certain sensing node, the sensing node uploads data in a buffer area per se to the converging node and an actuating node makes a corresponding reaction according to the data received by the converging node; different weights Wi are preset for each sensing node; the magnitude of each weight is decided by the event occurrence frequency of an area where the sensing node is positioned and the importance of a detection event type; and the greater the weight is, the more the moving paths Tj pass through the sensing node. The invention has the advantages of small number of redundant sensing nodes, high communication flexibility and high instantaneity.
Description
Technical field
The present invention relates to wireless senser and actor network (WSAN) field, be specifically related to the short time delay method for routing of a kind of wireless senser and actor network and this network.
Background technology
Wireless senser and actor network (WSAN) are derivative by wireless sensor network (WSN).In wireless senser and actor network, target area has been disposed a large amount of micro sensing nodes (Sensor) except disperseing, and also disperses disposed the XM (actuator) of some and collected node (Sink).The information of sensing node monitoring, perception and collection monitoring target, and information is sent to and collects node.Collect node and make a policy to select which XM to carry out relevant operation by according to the monitoring information of collecting, thereby realize dynamic mutual in real time.
The main target that wireless senser and actor network are pursued improves real-time communication exactly, require XM to make a response fast to sense events, for example, when fire occurs, if XM cannot be made a response fast to sense events, fire probably can spread, finally cause some catastrophic consequences, serious threat is to national wealth and life security.Therefore in wireless senser and actor network, real-time communication is particularly crucial, and in order to improve real-time communication, with regard to inevitable requirement data, the delay in transmitting procedure reaches minimum as far as possible.
Yet in current wireless senser and actor network, sensing node is all to adopt by the equipment of battery powered low cost, low power consumption conventionally, such equipment had both needed it to carry out battery altering continually as sensing node, had limited again its induction range and communication distance.Therefore, real-time in order to ensure wireless senser and actor network, in the target area of current wireless senser and actor network conventionally random placement hundreds of redundancy sensing node, extend network lifecycle, yet the deployment density of this sensing node is unwanted for the node that collects with higher transmission energy with the XM with higher execution scope.
Summary of the invention
Technical problem to be solved by this invention is to provide the short time delay method for routing of a kind of wireless senser and actor network and this network, and it has the advantages that redundancy sensing node quantity is few and real-time communication is strong.
For addressing the above problem, the present invention is achieved by the following technical solutions:
Short time delay method for routing for wireless senser and actor network, this wireless senser and actor network comprise that through part is deployed in a plurality of sensing nodes in target area, a plurality of node and a plurality of XM collected; All nodes that collect move in whole network, and each collects the mobile route T of node
j(j=1,2 ..., M) be all separate closed-loop path, and every mobile route T
jin each sensing node all only through once; When collecting node and approach certain sensing node, this sensing node is given the data upload in self buffer area to collect node, and XM is made a response according to collecting the data that node receives; Every mobile route T
jby following steps, determined:
(1) calculate through i sensing node S
ithe number k of mobile route,
k＝W
i×M
In formula, i=1,2 ..., N; N is the number of sensing node; M is the number of collecting node; W
ifor sensing node S
icorresponding weight, and 0 < W
i≤ 1;
(2) be every mobile route T
jdistribute sensing node, the sensing node that is about to have identical k value is classified as one group of set, is designated as S set
k, S herein
ksubscript k represent the corresponding k value of sensing node in this set; According to the size order of k value, carry out successively following steps simultaneously:
(2.1) when k=M, by S set
kmiddle S
idistribute to all mobile route T
j;
(2.2) when k=M-1, by S set
kin S
idistribute to M-1 bar mobile route T arbitrarily
j;
(2.3) when k=M-2, by S set
kin S
idistribute to M-2 bar mobile route T arbitrarily
j;
(2.4) by that analogy, until k=1, now by S set
kin S
idistribute to a mobile route T
j;
(3) to every mobile route T
jall adopt the Algorithm for Solving shortest path solution that leapfrogs, that is:
(3.1) initialization, sets every mobile route T
jquantity m and the feasible solution number n in each feasible solution set, every mobile route T of feasible solution subclass
jall feasible solutions sum F=m * n;
(3.2) generate at random every mobile route T
jthe initial population that forms of F feasible solution, and establish each mobile route feasible solution U=(U
1, U
2..., U
n), U wherein
1, U
2..., U
nrepresent respectively this mobile route feasible solution the numbering of the sensing node of process successively;
(3.3) calculate the fitness of above-mentioned each mobile route feasible solution, the fitness of this mobile route feasible solution equals the inverse of this mobile route length;
(3.4) above-mentioned mobile route feasible solution is carried out to descending by adaptive value size, and the mobile route feasible solution of fitness maximum is recorded as to the initial overall situation preferably separates P
x; Meanwhile, by following allocation rule, above-mentioned each mobile route feasible solution is assigned to m subclass Y
kin, each subclass Y
kin comprise n mobile route feasible solution;
Allocation rule: Y
k=X (p), and f (p) | X (p)=X[q+m * (p-1)], f (p)=f[q+m * (p-1)]
In formula, p=1,2 ..., n; Q=1,2 ..., m; X (p) represents p mobile route feasible solution in subclass, and f (p) represents the fitness of p mobile route feasible solution;
(3.5) carry out Local Search, the initial overall situation is preferably separated to P
xupgrade, detailed process is as follows:
(3.5.1) at each subclass Y
kthe mobile route feasible solution that inside finds fitness maximum is locally optimal solution P
b, and the mobile route feasible solution of fitness minimum is part the poorest solution P
w;
(3.5.2) as follows to each subclass Y
kin part the poorest solution P
wupgrade,
P
q＝P
w+S' ①
S'＝min{int[rand(P
B-P
W)],s
max},P
B-P
W≥0 ②
S'＝max{int[rand(P
B-P
W)],-s
max},P
B-P
W<0 ③
In formula, P
qrepresent the poorest solution after upgrading; S ' represents the adjustment vector of mobile route feasible solution; S
maxrepresent that mobile route feasible solution allows the maximum step-length changing, it is worth by system intialization; Rand represents random quantity, and its value is generated by computer random or has system intialization, span (0,1] between;
(3.6) at each subclass Y
kall carried out one take turns renewal after, by each subclass Y
kmix, and the mobile route feasible solution after upgrading is carried out to descending by adaptive value size, and the overall situation that the mobile route feasible solution of fitness maximum is recorded as after renewal is preferably separated P
x;
(3.7) judge whether to meet algorithmic statement condition, if meet, the overall situation after output is upgraded is preferably separated P
xas optimal path sequence; Otherwise, turn back to step (3.4) and again upgrade the overall situation and preferably separate P
x.
The described algorithmic statement condition of above-mentioned steps (3.7) is: 1., after K time nearest overall thoughts communication process, the overall situation preferably solution is not significantly improved; Or 2. the predefined function evaluation of algorithm number of times reaches.
In such scheme, the number N of described sensing node is greater than the number M that collects node.
In such scheme, the span of the number N of described sensing node is 1<N<10000; The span of collecting the number M of node is 1<M<1000.
Can realize a kind of wireless senser and the actor network of above-mentioned short time delay method for routing, comprise that through part is deployed in a plurality of sensing nodes in target area, collects node and XM.All nodes that collect are all mobile; These collect node and move in whole network, and each collects the mobile route T of node
jall separate; When collecting node and approach certain sensing node, this sensing node is given the data upload in self buffer area to collect node, and XM is made corresponding reaction according to collecting the data that node receives; Each sensing node has all been preset different weights W
i, 0 < W wherein
i≤ 1, the frequency that the size of this weight is occurred by this sensing node region event and the importance that detects event type determines, weight is larger, through the mobile route T of this sensing node
jmore.
In such scheme, the number N of described sensing node is greater than the number M that collects node.
In such scheme, the span of the number N of described sensing node is 1<N<10000; The span of collecting the number M of node is 1<M<1000.
Compared with prior art, the present invention has following features:
1, adopt one group of node that collects moving to be responsible for information gathering, sensing node on-fixed collect node communication with certain, thereby have strengthened flexibility and the real-time of network;
The importance of the size of the frequency 2, occurring according to the region event of sense node and detection event type determines the number in the path of process, having shortened sensing node detects after event to being uploaded to the time interval of collecting node, thereby effectively reduced communication delay, improved real-time;
3, adopt the new more ripe algorithm that leapfrogs at present to collect to every the preferably solution that node-routing path Tj asks shortest path, again effectively reduced communication delay, improved real-time.
Accompanying drawing explanation
Fig. 1 is a kind of wireless senser of the present invention and actor network schematic diagram.
Fig. 2 is the short time delay method for routing flow chart of a kind of wireless senser of the present invention and actor network.
Embodiment
Referring to Fig. 1, a kind of wireless senser of the present invention and actor network, comprise that through part is deployed in a plurality of sensing nodes in target area, collects node and XM, is characterized in that: all nodes that collect are all mobile; These collect node and move in whole network, and each collects the mobile route T of node
jall separate; When collecting node and approach certain sensing node, this sensing node is given the data upload in self buffer area to collect node, and XM is made corresponding reaction according to collecting the data that node receives; Each sensing node has all been preset different weights W
i, 0 < W wherein
i≤ 1, the frequency that the size of this weight is occurred by this sensing node region event and the importance that detects event type determines, weight is larger, through the mobile route T of this sensing node
jmore.Consider that in wireless sensor and actor network, a large amount of sensing nodes and a plurality of actuator node and the mobile node that collects have been disposed in dispersion.Collect node and XM and all possessed high transmittability and transmission range, and can direct communication.Therefore in the present invention, the number N of described sensing node is greater than the number M that collects node.The number N of sensing node and the number M that collects node determine according to concrete applicable cases, network coverage area is larger, the value of M and N also can be larger, in the preferred embodiment of the present invention, the span of the number N of described sensing node is 1<N<10000; The span of collecting the number M of node is 1<M<1000.
Referring to Fig. 2, the short time delay method for routing of above-mentioned wireless senser and actor network, this wireless senser and actor network comprise that through part is deployed in a plurality of sensing nodes in target area, a plurality of node and a plurality of XM collected; It is characterized in that: all nodes that collect move in whole network, and each collects the mobile route T of node
j(j=1,2 ..., M) be all separate closed-loop path, and every mobile route T
jin each sensing node all only through once; When collecting node and approach certain sensing node, this sensing node is given the data upload in self buffer area to collect node, and XM is made a response according to collecting the data that node receives; Every mobile route T
jby following steps, determined:
(1) calculate through i sensing node S
ithe number k of mobile route,
k＝W
i×M
In formula, i=1,2 ..., N; N is the number of sensing node; M is the number of collecting node; The number N of sensing node and the number M that collects node determine according to concrete applicable cases, network coverage area is larger, the value of M and N also can be larger, in the preferred embodiment of the present invention, the span of the number N of described sensing node is 1<N<10000; The span of collecting the number M of node is 1<M<1000; W
ifor sensing node S
icorresponding weight, and 0 < W
i≤ 1;
For example: sense node S
icorresponding weighted value W
i=0.75, collect node number M=4, k=3, this just illustrates that 4 are collected in node and have 3 mobile routes that collect node can pass through sense node S
i.
(2) be every mobile route T
jdistribute sensing node, the sensing node that is about to have identical k value is classified as one group of set, is designated as S set
k(S herein
ksubscript k represent the corresponding k value of sensing node in this set, as S
3the k value that represents the sense node of this set all equals 3, in this set arbitrarily induction joint all have 3 collect node motion path through); According to the size order of k value, carry out successively following steps simultaneously:
(2.1) when k=M, (represent the sense node weighted value W in this set
i=1, each collects the mobile route T of node
jall to pass through these nodes), by S set
kmiddle S
idistribute to all mobile route T
j; For
there is s
i∈ T
j,, j=1 ... M;
(2.2) when k=M-1, by S set
kin S
i distribute to M-1 bar mobile route T arbitrarily
j;
(2.3) when k=M-2, by S set
kin S
idistribute to M-2 bar mobile route T arbitrarily
j;
(2.4) when k=M-3, by S set
kin S
idistribute to M-3 bar mobile route T arbitrarily
j;
(2.5) by that analogy, until k=1 (for any one sense node in network, has a T at least
jmeeting is through it), now by S set
kin S
idistribute to a mobile route T
j;
For
have
make s
i∈ T
j(S is the set of all sensing nodes in network)
(3) due to T
jseparate, so every T
jall can find out independently TSP problem, to every mobile route T
jthe employing Algorithm for Solving shortest path solution that leapfrogs, for example, according to the known road of previous step mobile route T
1the sense node of passing through, solves the mobile route T that collects node 1
1; Carry out following steps:
(3.1) initialization, sets every mobile route T
jquantity m and the feasible solution number n in each feasible solution set, every mobile route T of feasible solution subclass
jall feasible solutions sum F=m * n;
In general the careless value of m and n, algorithm starts front preset as the case may be in advance, can be several also can up to a hundred or thousands of, m and n value are larger, the result finally obtaining will be better, but general value more intensive is just larger.
(3.2) generate at random every mobile route T
jthe initial population that forms of F feasible solution, and establish each mobile route feasible solution U=(U
1, U
2..., U
n), U wherein
1, U
2..., U
nrepresent respectively this mobile route feasible solution the numbering of the sensing node of process successively;
For example: suppose the known mobile route T that collects node 1
1these five sensing nodes are numbered respectively to 1-5 through 5 sensing nodes, frog U=(3,4,1,5,2) represents that collecting node 1 mobile route is: 3-4-1-5-2-3 is T
1a mobile route feasible solution.
(3.3) calculate the fitness of above-mentioned each mobile route feasible solution, the fitness of this mobile route feasible solution equals the inverse of this mobile route length;
(3.4) above-mentioned mobile route feasible solution is carried out to descending (if encounter the individuality that adaptive value is identical, sequence in no particular order) by adaptive value size, and the mobile route feasible solution of fitness maximum is recorded as to the initial overall situation preferably separates P
x; Meanwhile, by following allocation rule, above-mentioned each mobile route feasible solution is assigned to m subclass Y
kin, each subclass Y
kin comprise n mobile route feasible solution;
Allocation rule: Y
k=X (p), and f (p) | X (p)=X[q+m * (p-1)], f (p)=f[q+m * (p-1)]
In formula, p=1,2 ..., n; Q=1,2 ..., m; X (p) represents p mobile route feasible solution in subclass, and f (p) represents the fitness of p mobile route feasible solution;
If set m=3, F mobile route feasible solution arranged from high to low by fitness, and position is positioned at first mobile route feasible solution and is divided into the first subclass Y
1, second mobile route feasible solution is divided into the second subclass Y
2, the 3rd mobile route feasible solution is divided into three subsetss and closes Y
3, the 4th mobile route feasible solution is divided into the first subclass Y
1, the like, all mobile route feasible solutions are divided in 3 subclass.
(3.5) carry out Local Search, the initial overall situation is preferably separated to P
xupgrade, detailed process is as follows:
(3.5.1) at each subclass Y
kthe mobile route feasible solution that inside finds fitness maximum is locally optimal solution P
b, and the mobile route feasible solution of fitness minimum is part the poorest solution P
w;
(3.5.2) as follows to each subclass Y
kin part the poorest solution P
wupgrade,
P
q＝P
w+S' ①
S'＝min{int[rand(P
B-P
W)],s
max},P
B-P
W≥0 ②
S'＝max{int[rand(P
B-P
W)],-s
max},P
B-P
W<0 ③
In formula, P
qrepresent the poorest solution after upgrading; S ' represents the adjustment vector of mobile route feasible solution; S
maxrepresent that mobile route feasible solution allows the maximum step-length changing, it is worth by system intialization; Rand represents random quantity, and it is generated by computer random or has system intialization, and its span is between 0～1;
If P
w=(13542), P
b=(21534), allow the maximum step-length S changing
max=3, if rand=0.5, P
q(1)=1+min{int[0.5 * (2-1)], 3}=1; P
q(2)=3+max{int[0.5 * (1-3)] ,-3}=2; Identical operation completes the solution P that can obtain a renewal after update strategy according to this
q=(12543) replace original P
w=(13542).
(3.6) at each subclass Y
kall carried out one take turns renewal after, by each subclass Y
kmix, and the mobile route feasible solution after upgrading is carried out to descending by adaptive value size, and the overall situation that the mobile route feasible solution of fitness maximum is recorded as after renewal is preferably separated P
x;
(3.7) judge whether to meet algorithmic statement condition, if meet, the overall situation after output is upgraded is preferably separated P
xas optimal path sequence; Otherwise, turn back to step (3.4) and again upgrade the overall situation and preferably separate P
x.
In the present invention, described algorithmic statement condition is: 1., after K time nearest overall thoughts communication process, the overall situation preferably solution is not significantly improved; Or 2. the predefined function evaluation of algorithm number of times reaches.The span of the above-mentioned number of times K that carries out overall thoughts communication (1,10000] between.
Claims (7)
1. short time delay method for routing for wireless senser and actor network, this wireless senser and actor network comprise that through part is deployed in a plurality of sensing nodes in target area, a plurality of node and a plurality of XM collected; It is characterized in that: all nodes that collect move in whole network, and each collects the mobile route T of node
j(j=1,2 ..., M) be all separate closed-loop path, and every mobile route T
jin each sensing node all only through once; When collecting node and approach certain sensing node, this sensing node is given the data upload in self buffer area to collect node, and XM is made a response according to collecting the data that node receives; Every mobile route T
jby following steps, determined:
(1) calculate through i sensing node S
ithe number k of mobile route,
k＝W
i×M
In formula, i=1,2 ..., N; N is the number of sensing node; M is the number of collecting node; W
ifor sensing node S
icorresponding weight, and 0 < W
i≤ 1;
(2) be every mobile route T
jdistribute sensing node, the sensing node that is about to have identical k value is classified as one group of set, is designated as S set
k, S herein
ksubscript k represent the corresponding k value of sensing node in this set; According to the size order of k value, carry out successively following steps simultaneously:
(2.1) when k=M, by S set
kmiddle S
idistribute to all mobile route T
j;
(2.2) when k=M-1, by S set
kin S
idistribute to M-1 bar mobile route T arbitrarily
j;
(2.3) when k=M-2, by S set
kin S
idistribute to M-2 bar mobile route T arbitrarily
j;
(2.4) by that analogy, until k=1, now by S set
kin S
idistribute to a mobile route T
j;
(3) to every mobile route T
jall adopt the Algorithm for Solving shortest path solution that leapfrogs, that is:
(3.1) initialization, sets every mobile route T
jquantity m and the feasible solution number n in each feasible solution set, every mobile route T of feasible solution subclass
jall feasible solutions sum F=m * n;
(3.2) generate at random every mobile route T
jthe initial population that forms of F feasible solution, and establish each mobile route feasible solution U=(U
1, U
2..., U
n), U wherein
1, U
2..., U
nrepresent respectively this mobile route feasible solution the numbering of the sensing node of process successively;
(3.3) calculate the fitness of above-mentioned each mobile route feasible solution, the fitness of this mobile route feasible solution equals the inverse of this mobile route length;
(3.4) above-mentioned mobile route feasible solution is carried out to descending by adaptive value size, and the mobile route feasible solution of fitness maximum is recorded as to the initial overall situation preferably separates P
x; Meanwhile, by following allocation rule, above-mentioned each mobile route feasible solution is assigned to m subclass Y
kin, each subclass Y
kin comprise n mobile route feasible solution;
Allocation rule: Y
k=X (p), and f (p) | X (p)=X[q+m * (p-1)], f (p)=f[q+m * (p-1)]
In formula, p=1,2 ..., n; Q=1,2 ..., m; X (p) represents p mobile route feasible solution in subclass, and f (p) represents the fitness of p mobile route feasible solution;
(3.5) carry out Local Search, the initial overall situation is preferably separated to P
xupgrade, detailed process is as follows:
(3.5.1) at each subclass Y
kthe mobile route feasible solution that inside finds fitness maximum is locally optimal solution P
b, and the mobile route feasible solution of fitness minimum is part the poorest solution P
w;
(3.5.2) as follows to each subclass Y
kin part the poorest solution P
wupgrade,
P
q＝P
w+S' ①
S'＝min{int[rand(P
B-P
W)],s
max},P
B-P
W≥0 ②
S'＝max{int[rand(P
B-P
W)],-s
max},P
B-P
W<0 ③
In formula, P
qrepresent the poorest solution after upgrading; S ' represents the adjustment vector of mobile route feasible solution; S
maxrepresent that mobile route feasible solution allows the maximum step-length changing, it is worth by system intialization; Rand represents random quantity, and its value is generated by computer random or has system intialization, span (0,1] between;
(3.6) at each subclass Y
kall carried out one take turns renewal after, by each subclass Y
kmix, and the mobile route feasible solution after upgrading is carried out to descending by adaptive value size, and the overall situation that the mobile route feasible solution of fitness maximum is recorded as after renewal is preferably separated P
x;
(3.7) judge whether to meet algorithmic statement condition, if meet, the overall situation after output is upgraded is preferably separated P
xas optimal path sequence; Otherwise, turn back to step (3.4) and again upgrade the overall situation and preferably separate P
x.
2. the short time delay method for routing of a kind of wireless senser according to claim 1 and actor network, it is characterized in that: the described algorithmic statement condition of step (3.7) is: 1., after K time nearest overall thoughts communication process, the overall situation preferably solution is not significantly improved; Or 2. the predefined function evaluation of algorithm number of times reaches.
3. the short time delay method for routing of a kind of wireless senser according to claim 1 and 2 and actor network, is characterized in that: the number N of described sensing node is greater than the number M that collects node.
4. the short time delay method for routing of a kind of wireless senser according to claim 1 and actor network, is characterized in that: the span of the number N of described sensing node is 1<N<10000; The span of collecting the number M of node is 1<M<1000.
5. wireless senser and an actor network, comprise that through part is deployed in a plurality of sensing nodes in target area, collects node and XM, is characterized in that: all nodes that collect are all mobile; These collect node and move in whole network, and each collects the mobile route T of node
jall separate; When collecting node and approach certain sensing node, this sensing node is given the data upload in self buffer area to collect node, and XM is made corresponding reaction according to collecting the data that node receives; Each sensing node has all been preset different weights W
i, 0 < W wherein
i≤ 1, the frequency that the size of this weight is occurred by this sensing node region event and the importance that detects event type determines, weight is larger, through the mobile route T of this sensing node
jmore.
6. a kind of wireless senser according to claim 5 and actor network, is characterized in that: the number N of described sensing node is greater than the number M that collects node.
7. a kind of wireless senser according to claim 6 and actor network, is characterized in that: the span of the number N of described sensing node is 1<N<10000; The span of collecting the number M of node is 1<M<1000.
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| CN102427593A (en) * | 2012-01-11 | 2012-04-25 | 桂林电子科技大学 | Data transmission adjustment method in wireless sensor and actor networks (WSANs) |
| CN102984713B (en) * | 2012-11-29 | 2015-07-15 | 武汉大学 | Wireless sensing and execution network covering method based on mobile node |
| CN107872807B (en) | 2016-09-26 | 2021-07-09 | 富士通株式会社 | Routing node position determination method and device and terminal equipment |
| CN107484220B (en) * | 2017-08-28 | 2021-03-19 | 西安电子科技大学 | Reliable and efficient routing method for wireless sensor and actuator network |
| CN108495249B (en) * | 2018-02-05 | 2019-12-03 | 西安电子科技大学 | Ad hoc network method for routing based on location information low-power consumption |
| CN109474904B (en) * | 2018-11-23 | 2021-06-25 | 淮阴工学院 | Wireless sensor network compressed data collection method considering energy consumption and coverage |
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2011
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