CN102300282A - 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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- CN102300282A CN102300282A CN2011102948857A CN201110294885A CN102300282A CN 102300282 A CN102300282 A CN 102300282A CN 2011102948857 A CN2011102948857 A CN 2011102948857A CN 201110294885 A CN201110294885 A CN 201110294885A CN 102300282 A CN102300282 A CN 102300282A
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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 to be derived by wireless sensor network (WSN).In wireless senser and actor network, the target area has been disposed a large amount of micro sensing nodes (Sensor) except disperseing, and also disperses to have disposed the XM (actuator) of some and compiled node (Sink).The information of sensing node monitoring, perception and collection monitoring target, and information is sent to compiles node.Compile node and make a policy selection by the relevant operation of which XM execution, thereby realize that real-time and dynamic is mutual according to the monitoring information of collecting.
The main target that wireless senser and actor network are pursued improves real-time communication exactly, require XM that sense events is made a response fast, when for example fire takes place, if XM can't be made a response fast to sense events, fire probably can spread, cause some catastrophic consequences at last, serious threat is to national wealth and life security.Therefore real-time communication is particularly crucial in wireless senser and the actor network, and the delay in transmission course reaches minimum as far as possible with regard to the inevitable requirement data in order to improve real-time communication.
Yet in present wireless senser and actor network, sensing node all is the equipment that adopts by battery powered low cost, low power consumption usually, such equipment had both needed it is carried out battery altering continually as sensing node, had limited its induction range and communication distance again.Therefore, real-time in order to ensure wireless senser and actor network, in the target area of present wireless senser and actor network, disposed hundreds of redundant sensing node usually at random, prolong network lifecycle, yet the deployment density of this sensing node is unwanted for the node that compiles with higher transmission energy with the XM with higher execution scope.
Summary of the invention
Technical problem to be solved by this invention provides 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 redundant 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:
The short time delay method for routing of a kind of wireless senser and actor network, this wireless senser and actor network comprise that through part is deployed in a plurality of sensing nodes in the target area, a plurality of node and a plurality of XM compiled; All nodes that compile move in whole network, and each compiles the mobile route T of node
j(j=1,2 ..., M) all be separate closed-loop path, and every mobile route T
jIn each sensing node all only through once; When compiling node near certain sensing node, this sensing node is given the data upload in self buffer area and is compiled node, and XM is made a response according to compiling the data that node receives; Every mobile route T
jDetermine by following steps:
(1) calculates through i sensing node S
iThe bar of mobile route count k, promptly
k＝W
i×M
In the formula, i=1,2 ..., N; N is the number of sensing node; M is a number of compiling node; W
iBe 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 pairing k value of sensing node in this set; Simultaneously carry out following steps successively according to the size order of k value:
(2.1) when k=M, with S set
kMiddle S
iDistribute to all mobile route T
j
(2.2) when k=M-1, with S set
kIn Si distribute to M-1 bar mobile route T arbitrarily
j
(2.3) repeating step (2.2) is up to k=1, and this moment is with S set
kIn Si distribute to a mobile route T
j
(3) to every mobile route T
jAll adopt the algorithm that leapfrogs to find the solution shortest path and separate, that is:
(3.1) every mobile route T is set in initialization
jThe quantity m of feasible solution subclass and the feasible solution number n in the set of each feasible solution, then every mobile route T
jAll feasible solutions sum F=m * n;
(3.2) generate every mobile route T at random
jThe initial population formed 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) fitness of above-mentioned each mobile route feasible solution of calculating, 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 descending by the adaptive value size, and the mobile route feasible solution of fitness maximum is recorded as the initial overall situation preferably separates P
XSimultaneously, 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 the formula, p=1,2 ..., n; Q=1,2 ..., m; P mobile route feasible solution in X (p) the expression subclass, the fitness of p mobile route feasible solution of f (p) expression;
(3.5) carry out Local Search, the initial overall situation is preferably separated P
XUpgrade, detailed process is as follows:
(3.5.1) at each subclass Y
kIn to find the mobile route feasible solution of fitness maximum be locally optimal solution P
b, and the mobile route feasible solution of fitness minimum is the poorest P of separating in part
w
(3.5.2) as follows to each subclass Y
kIn the poorest P that separates in part
wUpgrade,
P
q＝P
w+S’ ①
S '=min{int[rand (P
B-P
W)], s
Max, P
B-P
W0 2.
S’＝max{int[rand(P
B-P
W)]，-s
max}，P
B-P
W＜0 ③
In the formula, P
qThe poorest separating after expression is upgraded; The adjustment vector of S ' expression mobile route feasible solution; S
MaxExpression mobile route feasible solution allows the maximum step-length of change, and it is worth by system intialization; Rand represents random quantity, and its value is generated by computer random or system intialization arranged, span (0,1] between;
(3.6) at each subclass Y
kAll carried out one and took turns after the renewal, with each subclass Y
kMix, and the mobile route feasible solution after will upgrading carries out descending by the adaptive value size, and the overall situation that the mobile route feasible solution of fitness maximum is recorded as after the renewal is preferably separated P
X
(3.7) judge whether to satisfy the algorithmic statement condition, if satisfy, the overall situation after output is upgraded is preferably separated P
XAs the optimal path sequence; Otherwise, turn back to step (3.4) and upgrade the overall situation once more 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 is not preferably separated and is significantly improved; Or 2. the predefined function evaluation of algorithm number of times reaches.
In the such scheme, the number N of described sensing node is greater than the number M of compiling node.
In the such scheme, the span of the number N of described sensing node is 1＜N＜10000; The span of compiling 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 the target area, compiles node and XM.All nodes that compile all move; It is mobile in whole network that these compile node, and each compiles the mobile route T of node
jAll be separate; When compiling node near certain sensing node, this sensing node is given the data upload in self buffer area and is compiled node, and XM is made corresponding reaction according to compiling the data that node receives; Each sensing node has all been preset different weights W
i, 0＜W wherein
i＜1, the size of this weight is by the frequency of this sensing node region incident generation and the importance decision that detects event type, and weight is big more, through the mobile route T of this sensing node
jMany more.
In the such scheme, the number N of described sensing node is greater than the number M of compiling node.
In the such scheme, the span of the number N of described sensing node is 1＜N＜10000; The span of compiling the number M of node is 1＜M＜1000.
Compared with prior art, the present invention has following characteristics:
1, adopt one group of node that compiles that moves to be responsible for information gathering, sensing node and on-fixed and certain are compiled the node communication, thereby have strengthened network more flexible and real-time;
2, the size of the frequency that takes place according to the region incident of sense node and the bar number in path that detects the importance decision process of event type, having shortened sensing node detects after the incident to being uploaded to the time interval of compiling node, thereby effectively reduced communication delay, improved real-time;
3, adopt the new at present ripe algorithm that leapfrogs to compile node routed path Tj and ask preferably separating of shortest path, effectively reduced communication delay once more, improved real-time every.
Description of drawings
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 the target area, compiles node and XM, and it is characterized in that: all nodes that compile all move; It is mobile in whole network that these compile node, and each compiles the mobile route T of node
jAll be separate; When compiling node near certain sensing node, this sensing node is given the data upload in self buffer area and is compiled node, and XM is made corresponding reaction according to compiling the data that node receives; Each sensing node has all been preset different weights W i, 0＜Wi＜1 wherein, the size of this weight is by the frequency of this sensing node region incident generation and the importance decision that detects event type, and weight is big more, and is many more through the mobile route Tj of this sensing node.Consider to disperse in the wireless sensor and actor network to have disposed a large amount of sensing nodes and a plurality of actuator node and the node that compiles that moves.Compile 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 of compiling node.The number N of sensing node decides according to concrete applicable cases with the number M of compiling node, and network coverage area is big more, and the value of M and N also can be big more, and 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 compiling 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 the target area, a plurality of node and a plurality of XM compiled; It is characterized in that: all nodes that compile move in whole network, and each compiles the mobile route T of node
j(j=1,2 ..., M) all be separate closed-loop path, and every mobile route T
jIn each sensing node all only through once; When compiling node near certain sensing node, this sensing node is given the data upload in self buffer area and is compiled node, and XM is made a response according to compiling the data that node receives; Every mobile route T
jDetermine by following steps:
(1) calculates through i sensing node S
iThe bar of mobile route count k, promptly
k＝W
i×M
In the formula, i=1,2 ..., N; N is the number of sensing node; M is a number of compiling node; The number N of sensing node decides according to concrete applicable cases with the number M of compiling node, and network coverage area is big more, and the value of M and N also can be big more, and 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 compiling the number M of node is 1＜M＜1000; W
iBe sensing node S
iCorresponding weight, and 0＜W
i＜1;
For example: sense node S
iCorresponding weighted value W
i=0.75, compile node number M=4, k=3 then, this just illustrates that 4 are compiled and have 3 mobile routes that compile node can pass through sense node S in the node
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 pairing k value of sensing node in this set, as S
3The k value of representing the sense node of this set all equals 3, promptly in this set arbitrarily the induction joint all have 3 compile the node motion path through); Simultaneously carry out following steps successively according to the size order of k value:
(2.1) when k=M, (represent the sense node weighted value W in this set
i=1, promptly each compiles the mobile route T of node
jAll to pass through these nodes), with S set
kMiddle S
iDistribute to all mobile route T
jPromptly for
S is arranged
i∈ T
j,, j=1 ... M;
(2.2) when k=M-1, with S set
kIn S
iPromptly
Distribute to M-1 bar mobile route T arbitrarily
j
(2.3) (any one sense node in promptly for network has a T at least to repeating step (2.2) up to k=1
jMeeting is through it), this moment is with S set
kIn S
iDistribute to a mobile route T
jPromptly for
Have
Make s
I ∈T
j(S is the set of all sensing nodes in the network)
(3) because T
jSeparate, so every T
jEqual TSP problems independently as can be seen is then to every mobile route T
jThe employing algorithm that leapfrogs is found the solution shortest path and is separated, for example according to the known road of previous step mobile route T
1The sense node of passing through is found the solution the mobile route T that compiles node 1
1Carry out following steps:
(3.1) every mobile route T is set in initialization
jThe quantity m of feasible solution subclass and the feasible solution number n in the set of each feasible solution, then every mobile route T
jAll feasible solutions sum F=m * n;
In general the careless value of m and n presets before algorithm begins in advance as the case may be, can be several also can up to a hundred or thousands of, m and n value are big more, the result who obtains at last will be better, but general value intensive is just big more more.
(3.2) generate every mobile route T at random
jThe initial population formed 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 compiles node 1
1These five sensing nodes are numbered 1-5 respectively through 5 sensing nodes, then frog U=(3,4,1,5,2) represents that compiling node 1 mobile route is: 3-4-1-5-2-3 is T
1A mobile route feasible solution.
(3.3) fitness of above-mentioned each mobile route feasible solution of calculating, 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 descending (if run into the adaptive value individuals with same, ordering in no particular order) by the adaptive value size, and the mobile route feasible solution of fitness maximum is recorded as the initial overall situation preferably separates P
XSimultaneously, 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 the formula, p=1,2 ..., n; Q=1,2 ..., m; P mobile route feasible solution in X (p) the expression subclass, the fitness of p mobile route feasible solution of f (p) expression;
If set m=3, F mobile route feasible solution arranged from high to low by fitness, and the position is positioned at first mobile route feasible solution branch and goes into the first subclass Y
1, second mobile route feasible solution branch is gone into the second subclass Y
2, the 3rd mobile route feasible solution branch is gone into three subsetss and is closed Y
3, the 4th mobile route feasible solution branch is gone into the first subclass Y
1, and 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 P
XUpgrade, detailed process is as follows:
(3.5.1) at each subclass Y
kIn to find the mobile route feasible solution of fitness maximum be locally optimal solution P
b, and the mobile route feasible solution of fitness minimum is the poorest P of separating in part
w
(3.5.2) as follows to each subclass Y
kIn the poorest P that separates in part
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 the formula, P
qThe poorest separating after expression is upgraded; The adjustment vector of S ' expression mobile route feasible solution; S
MaxExpression mobile route feasible solution allows the maximum step-length of change, and it is worth by system intialization; Rand represents random quantity, and it is generated by computer random or system intialization is arranged, and its span is between 0～1;
If P
w=(13542), P
b=(21534) allow the maximum step-length S that changes
Max=3, if rand=0.5, then 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 operations is finished the P that separates that can obtain a renewal behind the update strategy according to this
q=(12543) replace original P
w=(13542).
(3.6) at each subclass Y
kAll carried out one and took turns after the renewal, with each subclass Y
kMix, and the mobile route feasible solution after will upgrading carries out descending by the adaptive value size, and the overall situation that the mobile route feasible solution of fitness maximum is recorded as after the renewal is preferably separated P
X
(3.7) judge whether to satisfy the algorithmic statement condition, if satisfy, the overall situation after output is upgraded is preferably separated P
XAs the optimal path sequence; Otherwise, turn back to step (3.4) and upgrade the overall situation once more 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 is not preferably separated and is 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. the short time delay method for routing of wireless senser and actor network, this wireless senser and actor network comprise that through part is deployed in a plurality of sensing nodes in the target area, a plurality of node and a plurality of XM compiled; It is characterized in that: all nodes that compile move in whole network, and each compiles the mobile route T of node
j(j=1,2 ..., M) all be separate closed-loop path, and every mobile route T
jIn each sensing node all only through once; When compiling node near certain sensing node, this sensing node is given the data upload in self buffer area and is compiled node, and XM is made a response according to compiling the data that node receives; Every mobile route T
jDetermine by following steps:
(1) calculates through i sensing node S
iThe bar of mobile route count k, promptly
k＝W
i×M
In the formula, i=1,2 ..., N; N is the number of sensing node; M is a number of compiling node; W
iBe 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 pairing k value of sensing node in this set; Simultaneously carry out following steps successively according to the size order of k value:
(2.1) when k=M, with S set
kMiddle S
iDistribute to all mobile route T
j
(2.2) when k=M-1, with S set
kIn Si distribute to M-1 bar mobile route T arbitrarily
j
(2.3) repeating step (2.2) is up to k=1, and this moment is with S set
kIn Si distribute to a mobile route T
j
(3) to every mobile route T
jAll adopt the algorithm that leapfrogs to find the solution shortest path and separate, that is:
(3.1) every mobile route T is set in initialization
jThe quantity m of feasible solution subclass and the feasible solution number n in the set of each feasible solution, then every mobile route T
jAll feasible solutions sum F=m * n;
(3.2) generate every mobile route T at random
jThe initial population formed 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) fitness of above-mentioned each mobile route feasible solution of calculating, 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 descending by the adaptive value size, and the mobile route feasible solution of fitness maximum is recorded as the initial overall situation preferably separates P
XSimultaneously, 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 the formula, p=1,2 ..., n; Q=1,2 ..., m; P mobile route feasible solution in X (p) the expression subclass, the fitness of p mobile route feasible solution of f (p) expression;
(3.5) carry out Local Search, the initial overall situation is preferably separated P
XUpgrade, detailed process is as follows:
(3.5.1) at each subclass Y
kIn to find the mobile route feasible solution of fitness maximum be locally optimal solution P
b, and the mobile route feasible solution of fitness minimum is the poorest P of separating in part
w
(3.5.2) as follows to each subclass Y
kIn the poorest P that separates in part
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 the formula, P
qThe poorest separating after expression is upgraded; The adjustment vector of S ' expression mobile route feasible solution; S
MaxExpression mobile route feasible solution allows the maximum step-length of change, and it is worth by system intialization; Rand represents random quantity, and its value is generated by computer random or system intialization arranged, span (0,1] between;
(3.6) at each subclass Y
kAll carried out one and took turns after the renewal, with each subclass Y
kMix, and the mobile route feasible solution after will upgrading carries out descending by the adaptive value size, and the overall situation that the mobile route feasible solution of fitness maximum is recorded as after the renewal is preferably separated P
X
(3.7) judge whether to satisfy the algorithmic statement condition, if satisfy, the overall situation after output is upgraded is preferably separated P
XAs the optimal path sequence; Otherwise, turn back to step (3.4) and upgrade the overall situation once more 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 is not preferably separated and is 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, it is characterized in that: the number N of described sensing node is greater than the number M of compiling node.
4. 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 span of the number N of described sensing node is 1＜N＜10000; The span of compiling the number M of node is 1＜M＜1000.
5. wireless senser and actor network comprise that through part is deployed in a plurality of sensing nodes in the target area, compiles node and XM, and it is characterized in that: all nodes that compile all move; It is mobile in whole network that these compile node, and each compiles the mobile route T of node
jAll be separate; When compiling node near certain sensing node, this sensing node is given the data upload in self buffer area and is compiled node, and XM is made corresponding reaction according to compiling the data that node receives; Each sensing node has all been preset different weights W
i, 0＜W wherein
i＜1, the size of this weight is by the frequency of this sensing node region incident generation and the importance decision that detects event type, and weight is big more, through the mobile route T of this sensing node
jMany more.
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 of compiling 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 compiling the number M of node is 1＜M＜1000.
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Cited By (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| 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) |
| CN102984713A (en) * | 2012-11-29 | 2013-03-20 | 武汉大学 | Wireless sensing and execution network covering method based on mobile node |
| CN107484220A (en) * | 2017-08-28 | 2017-12-15 | 西安电子科技大学 | A kind of reliable high usage router method of wireless senser and actor network |
| CN108495249A (en) * | 2018-02-05 | 2018-09-04 | 西安电子科技大学 | Ad hoc network method for routing based on location information low-power consumption |
| CN109474904A (en) * | 2018-11-23 | 2019-03-15 | 淮阴工学院 | A kind of wireless sensor network compressed data collection method considering energy consumption and covering |
| US10433233B2 (en) | 2016-09-26 | 2019-10-01 | Fujitsu Limited | Method and apparatus for determining position of routing node and terminal equipment |
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2011
- 2011-09-27 CN CN201110294885.7A patent/CN102300282B/en not_active Expired - Fee Related
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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) |
| CN102984713A (en) * | 2012-11-29 | 2013-03-20 | 武汉大学 | Wireless sensing and execution network covering method based on mobile node |
| CN102984713B (en) * | 2012-11-29 | 2015-07-15 | 武汉大学 | Wireless sensing and execution network covering method based on mobile node |
| US10433233B2 (en) | 2016-09-26 | 2019-10-01 | Fujitsu Limited | Method and apparatus for determining position of routing node and terminal equipment |
| CN107484220A (en) * | 2017-08-28 | 2017-12-15 | 西安电子科技大学 | A kind of reliable high usage router method of wireless senser and actor network |
| 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 |
| CN108495249A (en) * | 2018-02-05 | 2018-09-04 | 西安电子科技大学 | Ad hoc network method for routing based on location information low-power consumption |
| 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 |
| CN109474904A (en) * | 2018-11-23 | 2019-03-15 | 淮阴工学院 | A kind of wireless sensor network compressed data collection method considering energy consumption and covering |
| 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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