CN103024859A - Data collection method of minimum overhead in low duty-cycle wireless sensor network - Google Patents
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Abstract
The invention discloses a data collection method of a minimum overhead in a low duty-cycle wireless sensor network, which comprises the following steps of: A, depending on a physical topology G of an actual network and waking cycles phi of various nodes, converting a logic topology which dynamically changes into a virtual grid network; B, based on the virtual grid network, setting an initial virtual grid network extension time delta as a maximum value of the minimal time required by a data pocket generated by a node ni to reach a sink node; C, finding out a maximum flow which meets a conflict-free requirement between a super source node s to a super sink node d in the virtual grid network; and D, judging whether the maximum flow is greater than or identical to the number of the source nodes; and if not, continuing to extend the virtual grid network in time until the found maximum flow meeting the conflict-free requirement is identical to the number of the source nodes. According to the data collection method disclosed by the invention, the timeliness of the data collection is improved; and the data receiving can be implemented only when the node is under a waked state, so that the service life of the network is maximized.
Description
Technical field
The present invention relates to the wireless sensor network technology field, relate in particular to the method for data capture of minimal time delay in a kind of low duty ratio wireless sensor network.
Background technology
In recent years, the develop rapidly of the communication technology, embedded technology and sensor technology makes the large-scale application of wireless sensor network become possibility.Wireless sensor network can be expanded people's information obtaining ability, the information interchange that greatly is convenient for people to, therefore have very wide application prospect, can be applied to the numerous areas such as military and national defense, industrial or agricultural control, city management, biologic medical, environmental monitoring, rescue and relief work.Wireless sensor network is comprised of the microsensor node (abbreviation node) that is deployed in a large amount of finite energies in the monitored area, form the self-organizing network of a multi-hop by communication, its objective is the information of perceptive object in collaboratively perception, the acquisition and processing network's coverage area, and to send to processing center (sink node) be aggregation node.Because the sensor node energy content of battery of carrying is limited, add the node number many, distributed areas are wide, some in addition be deployed in the deathtrap, so sensor node to come makeup energy by the mode of changing battery be unpractical.It is the overriding challenge that wireless sensor network faces that procotol how to design efficient energy-saving is come the maximization network life-span.
Sleep awakening mechanism is a kind of effective ways that improve network life.Sensor node has the state of two kinds of low duty ratios usually: wake-up states and sleep state.Under wake-up states, sensor node can perception around physical world information, and sending and receiving relevant information, and under sleep state, sensor node will be closed all communications and sensing module, only open time clock feature.Low duty ratio sleep awakening mechanism mainly is to adopt the mode of periodically waking node up, to reduce unnecessary data retransmission and reception, allows the sensor node time as much as possible be in sleep state, and is unlikely to affect proper communication and the function of network.Owing to just can carry out proper communication when only having communicating pair all to be in wake-up states, in case there is a side to be in sleep state, then the opposing party need to wait by the time next cycle the other side wakes Shi Caineng up and carries out transfer of data, and this has just brought " sleep time delay ".In the low duty ratio network, when namely the ratio of the wakeup time of node and the length of one's sleep is very little, end-to-end data transmission time delay will extremely worsen, and cause that network data is ageing to be reduced greatly.In the wireless sensor network of accident monitoring, the requirement of real-time that data are collected is very high, in case sensor node monitors unusual situation, guarantee with the fastest speed information to be sent to processing center.Therefore method of data capture how to design the time delay optimum in the low duty ratio wireless sensor network that improves efficiency is a very good problem to study.
Because sensor node is by periodic wakeup, so the logical topology of network is in the dynamic change in time, and how a kind of method of data capture that can reach the time delay minimum of design has very large challenge in dynamic topology.The scholar of Princeton and University of Southern California has proposed a kind of method of data capture of time delay optimum jointly, and combine channel allocation and power control mechanism, the method has provided the link scheduling method of time delay minimum in single channel and two kinds of situations of multichannel, but the method is not considered sensor node " sleep time delay ", the hypothesis node is in wake-up states always in the employed network model, and can only could realize this time delay optimal scheduling method under tree topology.The scholar of Stanford University has proposed a kind of method of data capture based on balance energy consumption and time delay in the radio sensing network of time division multiple access access (Time Division Multiple Access, TDMA).The method is under the prerequisite of given slot length, can find a kind of link scheduling strategy of time delay minimum, but the method is not considered the periodic sleep mechanism of sensor node yet, does not namely consider the impact that " sleep time delay " brought data collection time delay yet.
Summary of the invention
For above-mentioned technical problem, the object of the present invention is to provide the method for data capture of minimal time delay in a kind of low duty ratio wireless sensor network, it has solved because " the sleep time delay " that sleep awakening mechanism is brought is long and the problem of the ageing decline of Data Collection, can be under the prerequisite that guarantees energy-efficiency, find a kind of route and link scheduling federation policies of Data Collection, and can effectively avoid because data collision retransmits the delay problem that brings.
For reaching this purpose, the present invention by the following technical solutions:
The method of data capture of minimal time delay comprises the steps: in a kind of low duty ratio wireless sensor network
A, according to the physical topology G of real network and the wake-up period π of each node, the logical topology of dynamic change is changed into virtual grid network static, in time continuation;
B, based on the virtual grid network, initial virtual grid network expansion time Δ is made as node n
iThe packet that produces arrives the required minimum time of sink node
In maximum
Wherein, n is the total nodes in the network;
C, in the virtual grid network, seek from super source node s to the max-flow that satisfies the super sink node d without conflicting request;
D, judge whether described max-flow equals the source node number; If the determination result is NO, then the virtual grid network is continued continuation in time, until equal the source node number in the satisfied max-flow without conflicting request of finding out.
Especially, described steps A also comprises:
Difference according to task that node is born, node is divided into three kinds: leaf node, intermediate node and sink node, wherein, described leaf node only sends packet as source node, described intermediate node both sent packet as source node, receive again and transmit the packet from neighbor node, described Sink node is only as destination node receive data bag.
Especially, described steps A specifically comprises:
A1, for each the node n among the physical topology G of real network
i, at any time t of T in the time, the virtual node N that wakes up of the node mapping that is in wake-up states in time continuation in the virtual grid network
I, t
A2, in the virtual grid network, increase a super source node s and super sink node d;
A3, in the physical topology G of real network node n
iLeaf node, and to node n
jWhen having directed edge, if node n
iT wakes node n constantly up for the first time
jP after time t wakes up constantly, then increases from N in the virtual grid network
I, tTo N
J, pDirected edge;
A4, in the physical topology G of real network node n
iIntermediate node, and to node n
jWhen having directed edge, if node n
iAnd n
jWakeup time be respectively t and p, and t and p be at T in the time, p t, then in the virtual grid network, increase from N
I, tTo N
J, pDirected edge;
A5, in the physical topology G of real network node n
iWhen being the sink node, then in the virtual grid network, set up all virtual nodes that wake up of its correspondence to the directed edge between the super sink node d;
A6, in the virtual grid network, set up first virtual directed edge of waking node corresponding from super source node s to institute's active node.
Especially, node n among the described step B
iThe packet that produces arrives the required minimum time of sink node
Obtain by dijkstra's algorithm.
Especially, described step C comprises: find the data packet transmission path that makes Data Collection time delay minimum by Ford-Fulkerson max-flow algorithm.
The present invention just logical topology of dynamic change changes into virtual grid network static, in time continuation, greatly reduce the complexity of data collection algorithm, and adopt uncompetitive TDMA media access mechanism, find the Data Collection path of time delay minimum, and guarantee data collision can not occur at data-gathering process.In the low duty ratio wireless sensor network, the present invention has improved the ageing of Data Collection, and has guaranteed the efficiency of whole network, and node only carries out data receiver at wake-up states, all enters At All Other Times sleep state, makes the network life maximization.
Description of drawings
The method of data capture flow chart of minimal time delay in the low duty ratio wireless sensor network that Fig. 1 provides for the embodiment of the invention;
Conflict free restrictive condition one schematic diagram of wireless sensor network that Fig. 2 a provides for the embodiment of the invention;
Conflict free restrictive condition two schematic diagrames of wireless sensor network that Fig. 2 b provides for the embodiment of the invention;
Physical topology G and the node wake-up period schematic diagram of the real network that Fig. 3 provides for the embodiment of the invention;
The virtual grid network diagram that Fig. 4 provides for the embodiment of the invention;
The max-flow schematic diagram of the virtual grid network that Fig. 5 provides for the embodiment of the invention;
The MDCD algorithm flow chart that Fig. 6 provides for the embodiment of the invention.
Embodiment
For making the purpose, technical solutions and advantages of the present invention clearer, the invention will be further described below in conjunction with drawings and Examples.
Please refer to shown in Figure 1, the method for data capture flow chart of minimal time delay in the low duty ratio wireless sensor network that Fig. 1 provides for the embodiment of the invention.
For the application characteristic of low duty ratio wireless sensor network, the present invention has set up following network model: in the low duty ratio wireless sensor network, node has two states: wake-up states and sleep state.Node can perception under wake-up states around physical world, and receive the packet of sending from neighbor node.For packet can be transmitted more rapidly, node can carry out the transmission of packet under any state, as long as next-hop node is in wake-up states.In each time slot, each node can only send a packet, and in the network except the sink node, other node all can produce a packet at initial time.The Data Collection time delay refers to that the packet that institute's active node produces all arrives the used time of sink node.
In the TDMA media access protocol, will be divided into a lot of identical time slots the time, if this time slot node is in wake-up states, then use " 1 " expression, if be in sleep state, then use " 0 " expression.The node wake-up period represents with π.If the working mechanism that node is given is " π=0100 ", show that in first job cycle π, node is waken up at second time slot, other time slot all is in sleep state.
In the present embodiment in the low duty ratio wireless sensor network method of data capture of minimal time delay comprise the steps:
Step S101, according to the physical topology G of real network and the wake-up period π of each node, the logical topology of dynamic change is changed into virtual grid network static, in time continuation.
Difference according to task that node is born, node is divided into three kinds: leaf node, intermediate node and sink node, wherein, described leaf node only sends packet as source node, described intermediate node both sent packet as source node, receive again and transmit the packet from neighbor node, described sink node is only as destination node receive data bag.
The detailed process that in the present embodiment the physical topology G of real network is mapped to virtual grid network (Virtual Grid Network, VGN) is as follows:
Step S1011, for each the node n among the physical topology G of real network
i, at any time t of T in the time, the virtual node N that wakes up of the node mapping that is in wake-up states in time continuation in the virtual grid network
I, t
Step S1012, in the virtual grid network, increase a super source node s and super sink node d.
Step S1013, in the physical topology G of real network node n
iLeaf node, and to node n
jWhen having directed edge, if node n
iT wakes node n constantly up for the first time
jP after time t wakes up constantly, then increases from N in the virtual grid network
I, tTo N
J, pDirected edge.
Because may when waking up for the first time, being carved with packets need and sending of leaf node, so do not need to consider when other wakes up limit to other node.
Step S1014, in the physical topology G of real network node n
iIntermediate node, and to node n
jWhen having directed edge, if node n
iAnd n
jWakeup time be respectively t and p, and t and p be at T in the time, p t, then in the virtual grid network, increase from N
I, tTo N
J, pDirected edge.
Step S1015, in the physical topology G of real network node n
iWhen being the sink node, then in the virtual grid network, set up all virtual nodes that wake up of its correspondence to the directed edge between the super sink node d.
Step S1016, in the virtual grid network, set up first virtual directed edge of waking node corresponding from super source node s to institute's active node.
Step S102, based on the virtual grid network, initial virtual grid network expansion time Δ is made as node n
iThe packet that produces arrives the required minimum time of sink node
In maximum
Wherein, n is the total nodes in the network.
Node n in the present embodiment
iThe packet that produces arrives the required minimum time of sink node
Obtain by dijkstra's algorithm.Dijkstra is a kind of known shortest path first at last, and it can in the hope of shortest path, no longer describe in detail at this according to the length of whole network topology and each link.
Step S103, in the virtual grid network, seek from super source node s to the max-flow that satisfies the super sink node d without conflicting request.
In the virtual grid network, seek from super source node s to the max-flow that satisfies the super sink node d without conflicting request by the Data Collection routing algorithm (Minimum Data Collection Delayalgorithm, MDCD) of minimal time delay.The MDCD algorithm finds the data packet transmission path that makes Data Collection time delay minimum by Ford-Fulkerson max-flow algorithm, and guarantees that the collection path of finding out by this algorithm in whole data-gathering process data collision can not occur.The Network Maximal-flow algorithm that a kind of ratio of Ford-Fulkerson max-flow algorithm is easier to realize is used comparatively extensively, no longer describes in detail at this.
The below describes for described data collision problem.In order to guarantee not clash in the data transmission procedure, need to consider the half-duplex characteristic of node, namely node can not receive and send packet simultaneously.Shown in Fig. 2 a and Fig. 2 b, both of these case does not allow to occur in the link scheduling process, in case occur data collision will occur.Shown in Fig. 2 a, node j is when the data that receiving node i sends, and node j can not send data to node m.Shown in Fig. 2 b, node 2 and node 3 send data can not for simultaneously node 1.Therefore when the max-flow of considering to seek in the virtual grid network, above two kinds of conflict situations should be foreclosed.
Step S104, judge whether described max-flow equals the source node number; If the determination result is NO, then the virtual grid network is continued continuation in time, until equal the source node number in the satisfied max-flow without conflicting request of finding out.
As shown in Figure 3, physical topology G and the node wake-up period schematic diagram of the real network that provides for the embodiment of the invention of Fig. 3.As an example of the physical topology G of real network shown in Figure 3 example implementation procedure of the present invention is carried out specific description.
To be mapped to the detailed process of virtual grid network as follows for the physical topology G of real network in the present embodiment:
1, as shown in Figure 3, the wake-up period of node 1 is " 1000 ", and the duration that tentation data is collected is 11 time slots, and node 1 can be waken up at the 1st, 5,9 three time slot so, so the virtual node that wakes up in the node 1 corresponding virtual grid network is N
1,1, N
1,5And N
1,9The virtual node that wakes up that node 2, node 3 and node 4 convert in the virtual grid network in like manner can get.
2, as shown in Figure 3, leaf node 1 can with Packet Generation to node 3, therefore can add directed edge: N in the virtual grid network when its neighbor node 3 wakes up
1,1→ N
3,2, N
1,1→ N
3,6And N
1,1→ N
3,10, as shown in Figure 4.Can for leaf node 2, equally also be when its neighbor node 3 is in wake-up states, can with Packet Generation to node 3, therefore can in the virtual grid network, add directed edge: N in like manner
2,4→ N
3,6And N
2,4→ N
3,10
3, as shown in Figure 3, intermediate node 3 is as source node, and it can send packet to node 4 when neighbor node 4 is in wake-up states, therefore can add directed edge: N in the virtual grid network
3,2→ N
4,3, N
3,2→ N
4,7And N
3,2→ N
4,11Node 3 is as via node, can be when it be in wake-up states the receive data bag, and be transmitted to neighbor node 4.Therefore can in the virtual grid network, add directed edge: N
3,6→ N
4,7, N
3,6→ N
4,11And N
3,10→ N
4,11
4, as shown in Figure 4, node 4 can add the virtual node that wakes up corresponding to super sink node d to the directed edge between the super sink node d as the sink node in the virtual grid network, therefore can add directed edge N
4,3→ d, N
4,7→ d and N
4,11→ d, as shown in Figure 3.
5, as shown in Figure 4, set up super source node s to the interior corresponding virtual directed edge that wakes node up of first wake-up period of each source node, therefore can in VGN, add directed edge: s → N
1,1, s → N
2,4And s → N
3,2
Executing above-mentioned steps 1 after 5, the physical topology G of real network as shown in Figure 3 and node wake-up period just convert static virtual grid network to, concrete condition, as shown in Figure 4.Find the minimal time delay Data Collection path that meets nothing conflict restriction in the wireless sensor network based on virtual grid network using MDCD algorithm.In virtual grid network as shown in Figure 4, seek the max-flow from super source node s to super sink node d, try to achieve the minimum time that in the virtual grid network, makes max-flow equal the source node number and expand.Resulting result as shown in Figure 5, when minimal time delay was expanded and to be 11 time slots, the max-flow from super source node s to super sink node d just equaled source node number 3.The flow direction of max-flow is the path of Data Collection: node 3 is issued node 4 at the 3rd time slot with the packet of self, node 2 is issued node 3 at the 6th time slot with the packet that self produces, the package forward that node 3 will be produced by node 2 at the 7th time slot is to node 4, node 1 is issued node 3 at the packet that the 10th time slot produces self, and the package forward that node 3 will be produced by node 1 at the 11st time slot is to node 4.
As shown in Figure 6, the MDCD algorithm flow chart that provides for the embodiment of the invention of Fig. 6.Detailed process is as follows:
Step S601, netinit.Netinit: each node is known the wake-up period π of oneself by the sink node by sending hello packet, initial virtual grid network expansion time Δ is made as node n
iThe packet that produces arrives the required minimum time of sink node
In maximum
Wherein, n is the total nodes in the network.Virtual grid network expansion time (VGN expands the time) Δ is the Data Collection duration.Initial max-flow f
mBe made as 0.Wherein,
Step S602, the VGN expansion time is updated to k π.
Step S603, judgement are in residual network G
fWhether exist super source node s to the augmenting path P of super sink node d in (Δ); If judged result is for being (Yes), execution in step S604 then, if judged result is for being (No), execution in step S608 then.
Step S604, increase flow valuve f ' at augmenting path P.
Step S605, judge whether flow valuve f ' satisfies the conflict free restrictive condition of data.The conflict free restrictive condition of data can be with reference to Fig. 2 a and Fig. 2 b.If judged result is yes, execution in step S607 then, if the determination result is NO, execution in step S608 then.
Step S607, stream is updated to f ', residual network is updated to G
f' (Δ) then continues execution in step S603.
Step S608, f
mBe updated to the max-flow of (G, s, d, c, Δ), optimum flow path is P.
Step S609, judgement f
mWhether less than n-1.If judged result is yes, execution in step S6010 then, if the determination result is NO, execution in step S6011 then.
Step S6010, k is carried out the k=k+1 computing.Then return execution in step S602.
Step S6011, in k node wake-up period, find the virtual node that wakes up of corresponding time t maximum.
Step S6012, acquisition minimum data are collected time delay T
MinEqual the t of described maximum.
Technical scheme of the present invention will change into owing to the dynamic logic topology that the node wake-up period causes static virtual grid network, and based on the conflict free Data Collection of virtual grid network searching minimal time delay path, it adopts uncompetitive TDMA media access mechanism, improved the ageing of Data Collection, and guaranteed the efficiency of whole network, make the network life maximization.
Above-mentioned only is preferred embodiment of the present invention and institute's application technology principle, anyly is familiar with those skilled in the art in the technical scope that the present invention discloses, and the variation that can expect easily or replacement all should be encompassed in protection scope of the present invention.
Claims (5)
1. the method for data capture of minimal time delay in the low duty ratio wireless sensor network is characterized in that, comprises the steps:
A, according to the physical topology G of real network and the wake-up period π of each node, the logical topology of dynamic change is changed into virtual grid network static, in time continuation;
B, based on the virtual grid network, initial virtual grid network expansion time Δ is made as node n
iThe packet that produces arrives the required minimum time of sink node
In maximum
Wherein, n is the total nodes in the network;
C, in the virtual grid network, seek from super source node s to the max-flow that satisfies the super sink node d without conflicting request;
D, judge whether described max-flow equals the source node number; If the determination result is NO, then the virtual grid network is continued continuation in time, until equal the source node number in the satisfied max-flow without conflicting request of finding out.
2. the method for data capture of minimal time delay in the low duty ratio wireless sensor network according to claim 1 is characterized in that, described steps A also comprises:
Difference according to task that node is born, node is divided into three kinds: leaf node, intermediate node and sink node, wherein, described leaf node only sends packet as source node, described intermediate node both sent packet as source node, receive again and transmit the packet from neighbor node, described Sink node is only as destination node receive data bag.
3. the method for data capture of minimal time delay in the low duty ratio wireless sensor network according to claim 2 is characterized in that, described steps A specifically comprises:
A1, for each the node n among the physical topology G of real network
i, at any time t of T in the time, the virtual node N that wakes up of the node mapping that is in wake-up states in time continuation in the virtual grid network
I, t
A2, in the virtual grid network, increase a super source node s and super sink node d;
A3, in the physical topology G of real network node n
iLeaf node, and to node n
jWhen having directed edge, if node n
iT wakes node n constantly up for the first time
jP after time t wakes up constantly, then increases from N in the virtual grid network
I, tTo N
J, pDirected edge;
A4, in the physical topology G of real network node n
iIntermediate node, and to node n
jWhen having directed edge, if node n
iAnd n
jWakeup time be respectively t and p, and t and p be at T in the time, p t, then in the virtual grid network, increase from N
I, tTo N
J, pDirected edge;
A5, in the physical topology G of real network node n
iWhen being the sink node, then in the virtual grid network, set up all virtual nodes that wake up of its correspondence to the directed edge between the super sink node d;
A6, in the virtual grid network, set up first virtual directed edge of waking node corresponding from super source node s to institute's active node.
4. the method for data capture of minimal time delay in the low duty ratio wireless sensor network according to claim 3 is characterized in that node n among the described step B
iThe packet that produces arrives the required minimum time of sink node
Obtain by dijkstra's algorithm.
5. the method for data capture of minimal time delay in the low duty ratio wireless sensor network according to claim 4, it is characterized in that, described step C comprises: find the data packet transmission path that makes Data Collection time delay minimum by Ford-Fulkerson max-flow algorithm.
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| CN101466161B (en) * | 2009-01-08 | 2010-08-25 | 西安电子科技大学 | Data collection method suitable for multi-hop wireless sensor network |
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| Publication number | Priority date | Publication date | Assignee | Title |
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| CN103327518A (en) * | 2013-06-24 | 2013-09-25 | 中国科学院信息工程研究所 | Node dormancy scheduling method based on link quality |
| CN103327518B (en) * | 2013-06-24 | 2017-01-11 | 中国科学院信息工程研究所 | Node dormancy scheduling method based on link quality |
| CN108770016A (en) * | 2018-06-04 | 2018-11-06 | 北京邮电大学 | 5G end to end network slice generation method based on template and device |
| CN109450809A (en) * | 2018-11-27 | 2019-03-08 | 华中科技大学 | A kind of data center scheduling system and method |
| CN109450809B (en) * | 2018-11-27 | 2021-10-15 | 华中科技大学 | Data center scheduling system and method |
| CN111698655A (en) * | 2020-05-08 | 2020-09-22 | 东南大学 | Non-interference pipelined data collection method based on duty ratio scheduling |
| CN112954636A (en) * | 2020-12-01 | 2021-06-11 | 东南大学 | Duty ratio scheduling-based linear sensor network multi-channel pipelined data collection method |
| CN114599077A (en) * | 2022-03-09 | 2022-06-07 | 中南大学 | Duty ratio self-adaptive adjusting scheme based on data stream prediction |
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