CN103501523A - Method for reducing power consumption of wireless sensor network based on greedy deletion - Google Patents
Method for reducing power consumption of wireless sensor network based on greedy deletion Download PDFInfo
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- CN103501523A CN103501523A CN201310476936.7A CN201310476936A CN103501523A CN 103501523 A CN103501523 A CN 103501523A CN 201310476936 A CN201310476936 A CN 201310476936A CN 103501523 A CN103501523 A CN 103501523A
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Abstract
The invention provides a method for reducing power consumption of a wireless sensor network based on greedy deletion, which is used for solving the problem of the power consumption of the wireless sensor network composed of sensor nodes, the electric energy carried by the sensor nodes is limited, and the method belongs to the technical field of control of the wireless sensor network. A topological structure of the wireless sensor network is controlled, so that the whole wireless sensor network is connected within the specified time, and simultaneously, the sensor nodes in an active status are minimized, so that the overall power consumption of the network is minimum within the time range. The method is especially suitable for the large-scale and self-organizing wireless sensor network with random deployment and complex environment, the network connection status of the wireless sensor network can be predicted, or network connections of the wireless sensor network are periodically changed.
Description
Technical field
The invention belongs to wireless sensor network control technology field, be specifically related to wireless sensor network topology control method, for reducing the power consumption of whole wireless sensor network.
Background technology
At present, in wireless sensor network, generally use can not spontaneous electric power battery the signal transmission is provided and receives required energy for the network sensor node.For the wireless sensor network formed for the sensor node limited by carried charge, some sensor nodes on network backbone can be used up self electric quantity very soon, and then may from whole network, break away from away, cause may no longer connecting between each sensor node of whole network.In wireless sensor network, a large amount of electric quantity consumption of sensor node becomes the bottleneck problem that maintaining network connects.Therefore, how to control the topological structure of wireless sensor network, thereby reduce the electric quantity consumption of whole network, become the more popular research direction in this field.
Mainly rely on the wireless sensor network of the self-contained electric energy maintenance work of sensor node for this class, the technical staff can ignore the Topology Structure Design of network self usually, or applies at random some simple static topological methods.There is not yet a kind of method that effectively by dynamic control network topology structure, reduces whole network power consumption.
Summary of the invention
The objective of the invention is for solve by self the power consumption problem of the wireless sensor network that forms of the limited sensor node of the electric energy of taking, a kind of method that reduces the wireless sensor network power consumption is proposed.By the topological structure to wireless sensor network, controlled, when making whole wireless sensor network keep connected state at the appointed time, sensor node in active state is minimized, make network whole power consumption minimum in this time range.This method is particularly useful on a large scale, self-organizing, random placement, circumstance complication and network connection state is predictable or network connects and to be periodically variable wireless sensor network.
The inventive method comprises the following steps:
Beneficial effect
The present invention, by proposing the network topology structure control method based on space-time diagram, advances control to the limited wireless sensor network of self institute's electric weight of taking.By dynamic topology design method, space-time diagram is controlled, according to the topological structure obtained, determined the at the appointed time open and-shut mode of section of sensor node.On the basis of network connectivty, close as far as possible the sensor node of greater number in satisfied scope at the appointed time, thus the optimized network topological structure, and the life span that extends network, significantly reduce the network power expense.
The accompanying drawing explanation
Fig. 1 is wireless sensor network at the communications status of section sometime.
Fig. 2 is that wireless sensor network changes at the communications status of four different time sections.
Fig. 3 is for being divided into 4 continuous time periods at whole time range T() in, a packet is from node v
1be sent to node v
5the directed walk (black thick line mean) of process.
Fig. 4 is to the handling process schematic diagram of space-time diagram ζ in the specific embodiment of the invention.
Fig. 5 is GrdDN, and the performance of GrdDN ' on the network node selection rate embodies.
Fig. 6 is GrdDN, and the performance of GrdDN ' on network power efficiency embodies.
Embodiment
The embodiment right below in conjunction with drawings and Examples is described in further details.
A kind of method of the reduction wireless sensor network power consumption of deleting based on greed, can guarantee that whole wireless sensor network keeps connected state at the appointed time, and at this moment in scope, sensor node in active state is minimum, makes network whole power consumption minimum in this time range.
For achieving the above object, the specific implementation process of the inventive method comprises the following steps:
Concrete, described stipulated time scope T is divided into to section set continuous time, T={1 ..., t}, wherein t is integer, represents the time period; V={v
1..., v
nmeaning the wireless sensor node set, n is integer.Fig. 1 has showed at time period 1(t=1) time concrete wireless sensor network in the correspondence of each sensor node.Fig. 2 has showed the different communication state of certain wireless sensor network within continuous four time periods ( time period 1,2,3,4).
Simultaneously, for any one sensor node in wireless sensor network in section t sometime
(i is integer, 1≤i≤n),
mean that this node sends the electric weight of the required consumption of packet within this time period;
mean that this node receives the electric weight of the required consumption of packet within this time period;
mean wireless sensor node v
ipower consumption in the t time period is weights.
In addition, can also use about node degree in space-time diagram ζ
node is set
weights
meaned node
average power consumption at t each degree of time period is weights.
At first, make G
t=(V
t, E
t) mean the correspondence figure of wireless sensor network in certain time period t.Wherein, limit
be illustrated in time period t sensor node v
ito sensor node v
jtransmit packet, i, j are integer, represent the numbering of wireless sensor node, 1≤i≤n, 1≤j≤n.In this way, finally obtain in stipulated time scope T network communication of wireless sensor graph of a relation set { G
t| t=1 ... T}.
Then, will gather { G
t| t=1 ... T} is converted to space-time diagram ζ.ζ=(υ, ε) means a space-time diagram, the temporal information that has comprised node and communicate status information.For decision node
whether need in certain time period t, open or close, suppose and have node in network in time period t
with
order
simultaneously, add two dummy nodes
with
wherein, use
mean v
iat the state zero hour of whole time range T, use
mean v
iat the state finish time of whole time range T.
At the appointed time in scope T, any a pair of node pair in space-time diagram ζ
at least there is a directed walk.Fig. 3 has meaned to be divided into 4 continuous time periods at whole time range T() in, the correspondence between each transducer, thick lines wherein represent that certain packet is from node v
1be sent to node v
5the directed walk of process.
In space-time diagram ζ, always have 2 (T+1) row node, wherein a time period is shown in every two lists; Each shows n node, adds up to the individual node of 2n (T+1).In space-time diagram ζ, there are three kinds of limits: time limit, limit, space, virtual limit.Wherein, time limit
the dactylus point
on the limit of time period t, be illustrated in this node in t time period and carry packet but do not send; The limit, space
finger is v in time period t
ito node v
jlimit, be illustrated in time period t interior nodes v
ito node v
jsend packet; Virtual limit
refer to node
from time period t to the formed limit of time period t+1.Example as shown in Figure 4.
At the appointed time in scope T, any a pair of node pair in space-time diagram H
, at least there is a directed walk in (1≤i, j≤n); Simultaneously, compare space-time diagram ζ and reduce total electric weight expense.
In space-time diagram ζ, each sensor node needs to consume the normal operation that electric energy maintains whole wireless network, and total electric weight expense of all nodes of space-time diagram ζ is c (ζ)=Σ
v ∈ ζc (v).
Processing procedure to space-time diagram ζ is as follows:
1), make period of the day from 11 p.m. to 1 a.m empty graph H equal space-time diagram ζ;
The order of 2), all nodes in period of the day from 11 p.m. to 1 a.m empty graph H being successively decreased by weights is put into Priority Queues Q;
3), judge whether Q is empty, if Q is empty, goes to step 5, if Q is not empty, goes to step 4);
4), take out the node of weights maximum in current queue from Q, after judgement is deleted this node from period of the day from 11 p.m. to 1 a.m empty graph H, whether H is communicated with, and deletes this node if H is communicated with and delete all limits that are connected with this node from H, otherwise H retains this node, goes to step 3);
5), return to period of the day from 11 p.m. to 1 a.m empty graph H.
Detailed process as shown in Figure 4.
Concrete setting up procedure is: the sensor node in the real network that in period of the day from 11 p.m. to 1 a.m empty graph H, each node is corresponding is opened.For example, the node in period of the day from 11 p.m. to 1 a.m empty graph H
expression is set as i sensor node to open t time period.
Embodiment
Impact energy of wireless sensor network consumed in order to test the present invention has been arranged 30 sensor nodes in the random network that utilizes classical stochastic model to generate, and test specification is divided into to 10 time periods.This random networks generation model with Probability p at two node v
i, v
jbetween add to connect, p can control the density of network, the p more density of macroreticular is larger, being illustrated in each time period network when p=1.0 is full the connection.According to the random network of continuous 10 time periods that generate, build space-time diagram ζ.Experiment has generated and has built 30 different space-time diagrams at random, moves the mean value that the experiment acquired results is the present invention's operation result on these 30 space-time diagrams on each space-time diagram.
It is input of the present invention that experiment arranges space-time diagram ζ, and space-time diagram H is output of the present invention, and n (H) means the number of node in space-time diagram H, and n (ζ) means the number of node in space-time diagram ζ, and c (H) means the total electric quantity consumption of space-time diagram H,
c (ζ) means the total electric quantity consumption of space-time diagram ζ,
The Performance Ratio of the present invention under two kinds of different node weighting schemes more as shown in Figure 5, Figure 6.In figure, GrdDN means to using the inventive method of c (v) mode as the node weights, and GrdDN ' means to using c'(v) mode is as the inventive method of node weights.
GrdDN shown in Fig. 5 and the GrdDN ' change curve under heterogeneous networks Connection Density p.The Connection Density p that in figure, abscissa is network, p respectively from 0.2 to 1.0, and ordinate is the node selection rate, node selection rate=n (H)/n (ζ).The node selection rate is lower, means that in network, the actual number of nodes used is fewer.As seen from the figure, GrdDN and GrdDN ' can both reduce the quantity of utilizing of node effectively, even when network density p is 0.2, the node selection rate of GrdDN and GrdDN ' is about 30%, still can save approximately 70% node.This experimental result shows, GrdDN and GrdDN ', under the prerequisite that meets the wireless network proper communication, can significantly reduce each time period and use the quantity of sensor node.
Shown in Fig. 6, the Connection Density that abscissa is sensor network, ordinate is network energy efficiency, energy efficiency=c (H)/c (ζ), ratio is less, saves energy more.As seen from the figure, continuous increase along with the network Connection Density, GrdDN and GrdDN ' are under the prerequisite that guarantees the wireless sensor network normal operation, can effectively save the energy of wireless sensor network, when the network Connection Density is 0.2, the energy efficiency of GrdDN and GrdDN ' is about 38%, has saved approximately 62% electric weight, and, along with the increase of network density, the continuous reduction of energy efficiency is saved the ratio of electric weight also in continuous increase simultaneously.
In sum, what the present invention proposed deletes the Topology control scheme of thought based on greed, be applicable to network simultaneously and connect sparse and network and connect wireless sensor network closely, can effectively reduce the electric quantity consumption of whole network under the prerequisite that guarantees the wireless sensor network normal operation.
Above-described instantiation is further to explain to of the present invention, and the protection range be not intended to limit the present invention is all within principle of the present invention and spirit, the change of doing and to be equal to replacement should be all within protection scope of the present invention.
Claims (2)
1. the method for a reduction wireless sensor network power consumption of deleting based on greed, is characterized in that, comprises the following steps:
Step 1, obtain wireless sensor network at the appointed time in scope continuous time section work state information; Described work state information comprises that sensor node receives the electric weight of the required consumption of packet, sends the electric weight of the required consumption of packet within each time period, and within each time period the correspondence between the different sensors node;
Concrete, described stipulated time scope T is divided into to section set continuous time, T={1 ..., t}, wherein t is integer, represents the time period; V={v
1..., v
nmeaning the wireless sensor node set, n is integer; Simultaneously, for any one sensor node in wireless sensor network in section t sometime
i is integer, 1≤i≤n,
mean that this node sends the electric weight of the required consumption of packet within this time period;
mean that this node receives the electric weight of the required consumption of packet within this time period;
mean wireless sensor node v
ipower consumption in the t time period is weights;
Step 2, the work state information obtained according to step 1, set up the space-time diagram of interior this network of scope T at the appointed time;
At first, make G
t=(V
t, E
t) mean the correspondence figure of wireless sensor network in certain time period t; Wherein, limit
be illustrated in time period t sensor node v
ito sensor node v
jtransmit packet, i, j are integer, represent the numbering of wireless sensor node, 1≤i≤n, 1≤j≤n; Finally obtain in stipulated time scope T network communication of wireless sensor graph of a relation set { G
t| t=1 ... T};
Then, will gather { G
t| t=1 ... T} is converted to space-time diagram ζ; ζ=(υ, ε) means a space-time diagram, the temporal information that has comprised node and communicate status information; For decision node
whether need in certain time period t, open or close, suppose and have node in network in time period t
with
order
simultaneously, add two dummy nodes
with
wherein, use
mean v
iat the state zero hour of whole time range T, use
mean v
iat the state finish time of whole time range T;
At the appointed time in scope T, any a pair of node pair in space-time diagram ζ
at least there is a directed walk;
In space-time diagram ζ, always have 2 (T+1) row node, wherein a time period is shown in every two lists; Each shows n node, adds up to the individual node of 2n (T+1); In space-time diagram ζ, there are three kinds of limits: time limit, limit, space, virtual limit; Wherein, time limit
the dactylus point
on the limit of time period t, be illustrated in this node in t time period and carry packet but do not send; The limit, space
finger is v in time period t
ito node v
jlimit, be illustrated in time period t interior nodes v
ito node v
jsend packet; Virtual limit
refer to node
from time period t to the formed limit of time period t+1;
Step 3, the space-time diagram ζ that step 2 is obtained are processed, and obtain the period of the day from 11 p.m. to 1 a.m empty graph H of space-time diagram ζ; Wherein, period of the day from 11 p.m. to 1 a.m empty graph H need to meet following requirement:
At the appointed time in scope T, any a pair of node pair in space-time diagram H
, at least there is a directed walk in (1≤i, j≤n); Simultaneously, compare space-time diagram ζ and reduce total electric weight expense;
In space-time diagram ζ, each sensor node needs to consume the normal operation that electric energy maintains whole wireless network, and total electric weight expense of all nodes of space-time diagram ζ is c (ζ)=Σ
v ∈ ζc (v);
Processing procedure to space-time diagram ζ is as follows:
1) make period of the day from 11 p.m. to 1 a.m empty graph H equal space-time diagram ζ;
The order of 2) all nodes in period of the day from 11 p.m. to 1 a.m empty graph H being successively decreased by weights is put into Priority Queues Q;
3) judge whether Q is empty, if Q is empty, goes to step 5, if Q is not empty, goes to step 4);
4) take out the node of weights maximum in current queue from Q, after judgement is deleted this node from period of the day from 11 p.m. to 1 a.m empty graph H, whether H is communicated with, and delete this node if H is communicated with and delete all limits that are connected with this node from H, otherwise H retains this node, goes to step 3);
5), return to period of the day from 11 p.m. to 1 a.m empty graph H;
Step 4, according to period of the day from 11 p.m. to 1 a.m empty graph H, the topological structure of wireless sensor network is arranged, thereby at utmost reduced whole network power consumption under the prerequisite that guarantees the network normal operation.
2. the method for a kind of reduction wireless sensor network power consumption of deleting based on greed as claimed in claim 1, is characterized in that, in described step 1, adopts node degree in space-time diagram ζ
node is set
weights
mean node
average power consumption at t each degree of time period is weights.
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CN101437305A (en) * | 2008-12-09 | 2009-05-20 | 重庆邮电大学 | Method for double communications and communication route optimization of wireless sensor network |
CN101437306A (en) * | 2008-12-08 | 2009-05-20 | 北京航空航天大学 | Method for implementing complete k communication of wireless sensing network based on part k communication |
CN102158938A (en) * | 2011-03-18 | 2011-08-17 | 武汉优赢科技有限公司 | Power-adjustable zonal sensor network topology control method |
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US20080253327A1 (en) * | 2004-12-22 | 2008-10-16 | Mikko Kohvakka | Energy Efficient Wireless Sensor Network, Node Devices for the Same and a Method for Arranging Communications in a Wireless Sensor Network |
CN101437306A (en) * | 2008-12-08 | 2009-05-20 | 北京航空航天大学 | Method for implementing complete k communication of wireless sensing network based on part k communication |
CN101437305A (en) * | 2008-12-09 | 2009-05-20 | 重庆邮电大学 | Method for double communications and communication route optimization of wireless sensor network |
CN102158938A (en) * | 2011-03-18 | 2011-08-17 | 武汉优赢科技有限公司 | Power-adjustable zonal sensor network topology control method |
Cited By (2)
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CN110620686A (en) * | 2019-09-05 | 2019-12-27 | 西安交通大学 | Routing node selection method based on complex communication network |
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