CN106954228A - A kind of lifetime based on dynamic data pattern optimizes the building method of tree - Google Patents
A kind of lifetime based on dynamic data pattern optimizes the building method of tree Download PDFInfo
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- CN106954228A CN106954228A CN201710196722.2A CN201710196722A CN106954228A CN 106954228 A CN106954228 A CN 106954228A CN 201710196722 A CN201710196722 A CN 201710196722A CN 106954228 A CN106954228 A CN 106954228A
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04W—WIRELESS COMMUNICATION NETWORKS
- H04W24/00—Supervisory, monitoring or testing arrangements
- H04W24/06—Testing, supervising or monitoring using simulated traffic
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04W—WIRELESS COMMUNICATION NETWORKS
- H04W40/00—Communication routing or communication path finding
- H04W40/02—Communication route or path selection, e.g. power-based or shortest path routing
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04W—WIRELESS COMMUNICATION NETWORKS
- H04W40/00—Communication routing or communication path finding
- H04W40/02—Communication route or path selection, e.g. power-based or shortest path routing
- H04W40/04—Communication route or path selection, e.g. power-based or shortest path routing based on wireless node resources
- H04W40/08—Communication route or path selection, e.g. power-based or shortest path routing based on wireless node resources based on transmission power
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04W—WIRELESS COMMUNICATION NETWORKS
- H04W40/00—Communication routing or communication path finding
- H04W40/02—Communication route or path selection, e.g. power-based or shortest path routing
- H04W40/04—Communication route or path selection, e.g. power-based or shortest path routing based on wireless node resources
- H04W40/10—Communication route or path selection, e.g. power-based or shortest path routing based on wireless node resources based on available power or energy
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04W—WIRELESS COMMUNICATION NETWORKS
- H04W52/00—Power management, e.g. TPC [Transmission Power Control], power saving or power classes
- H04W52/02—Power saving arrangements
- H04W52/0209—Power saving arrangements in terminal devices
- H04W52/0212—Power saving arrangements in terminal devices managed by the network, e.g. network or access point is master and terminal is slave
- H04W52/0216—Power saving arrangements in terminal devices managed by the network, e.g. network or access point is master and terminal is slave using a pre-established activity schedule, e.g. traffic indication frame
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04W—WIRELESS COMMUNICATION NETWORKS
- H04W84/00—Network topologies
- H04W84/18—Self-organising networks, e.g. ad-hoc networks or sensor networks
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- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
- Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
- Y02D—CLIMATE CHANGE MITIGATION TECHNOLOGIES IN INFORMATION AND COMMUNICATION TECHNOLOGIES [ICT], I.E. INFORMATION AND COMMUNICATION TECHNOLOGIES AIMING AT THE REDUCTION OF THEIR OWN ENERGY USE
- Y02D30/00—Reducing energy consumption in communication networks
- Y02D30/70—Reducing energy consumption in communication networks in wireless communication networks
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Abstract
The building method of tree, including following operating procedure are optimized the present invention relates to a kind of lifetime based on dynamic data pattern：Energy charge is quantified using TPO scheduling mechanisms；Calculate node v is used to receiving in a sampling period, the energy charge model of transmission and idle listening；Using the routing tree that the above-mentioned energy charge Construction of A Model lifetime is optimal.In above-mentioned technical proposal, a Mathematical Modeling is devised for tree structure, the energy charge for accurately describing sensor node, and the application of mathematical model designed is carried out into the lifetime of peak optimizating network in constructing efficient tree.
Description
Technical field
The present invention relates to wireless sensor network field, and in particular to a kind of lifetime based on dynamic data pattern is optimal
Change the building method of tree.
Background technology
Wireless sensor network is made up of the wireless sensor node of dense deployment.This network is commonly placed at nature
In region, by cooperating with each other between node, the change to physical quantity in target environment is monitored.This network generally by
One base station and numerous sensor nodes are constituted, as shown in Figure 1.Sensor node is battery powered, and base station is powered by power supply,
Sensor node and base station are by way of radio communication, and self-organizing is a network.
The Data Collection of sensor network is faced with the challenge of node energy pre-mature exhaustion.In all energy ezpenditures,
Proportion of the radio communication in occupation of maximum.For power saving, it should avoid excessive carry out data transmission.And which number is transmitted actually
According to, determined in itself by data, and only Monitoring Data by sensor node collect after can just be determined.So,
In each sampling period, the node of data is reported and submitted to change and unpredictable dynamic.Such as, within the neighbouring sample cycle,
The data that each sensor node is collected, the often more steady or only fluctuation in certain scope.In order to save electricity,
Only when the deviation between the data that new sample magnitude and last time report and submit it is big to a certain extent when, node just needs to send out to base station
Give this data collected.Before node is to Environment features, each sensor node can not calculate it in advance and report twice
The deviation for sending data is how many.And for example, in the Sensor monitoring application triggered by condition, such as in being monitored in volcano, only
When vibrations and acoustic signals produce mutation, just need to transmit data.But, before node sample to data, it does not know simultaneously
Whether following data in road oneself can meet the good condition of earlier set.The characteristics of two above application scenarios have identical：
In each sampling period, sensor node over time constantly dynamic change of the data to base station is reported and submitted, and this change has
Unpredictability.Distribution of the data to the sensor node of base station will be reported and submitted in network, data pattern is defined as.
In the case of data pattern dynamic change, the energy charge that reduction Data Collection is brought is most important.Wirelessly
Sensor node is generally by battery power, and the lifetime for farthest saving electricity to extend network, (first was saved in network
The time of the dry energy of point consumption) it is very important.And dynamic data pattern brings challenge to energy-conservation.
On the other hand, in data-gathering process, the energy ecology of node is influenceed by routing infrastructure again.Different roads
By structure, it will have influence on that each node is received and need the number of packet sent, so as to have influence on the energy of node
Utilize.Work in terms of all existing Routing Protocols, is handled both for complete data pattern.Complete datagram
Sample refers to：All nodes all produce a packet, go to be sent to aggregation node within each sampling period in network.For place
Reason is periodic, and with the Data Collection of dynamic data pattern, these Routing Protocols are poorly efficient.Because, in network not
Same data pattern, can cause each node in the reception of packet, send, and in terms of idle listening, spend different percentages
The energy of ratio.So, different data patterns needs to get up from the matching of different routing infrastructures, goes to extend the lifetime of network.
Such as, when the node that data are sent in network is more, receive and transmission packet generally disappears in the energy of sensor node
Sizable proportion is occupied in consumption.In this case, the data volume for balancing each node is extremely important.On the other hand, net is worked as
When the node of transmission data is fewer in network, the energy charge of sensor node is generally dominated by idle listening.Now, converge
Sensor node around node is no longer just the bottleneck of energy ezpenditure.Make each node spend in idle listening in terms of energy
It is few as far as possible, reform into terms of routing infrastructure is designed, a considerable Consideration.So, it is dynamic in order to tackle
State data pattern, is designed to balance the routing infrastructure that different node energies are spent, is very heavy to extend the lifetime of network
Want.
The content of the invention
The building method of tree is optimized it is an object of the invention to provide a kind of lifetime based on dynamic data pattern, its
It can be applied to construct efficient tree, the lifetime for peak optimizating network.
To achieve the above object, present invention employs following technical scheme：
A kind of lifetime based on dynamic data pattern optimizes the building method of tree, it is characterised in that：Including following behaviour
Make step：
S1：Energy charge is quantified using TPO scheduling mechanisms；
S2：Calculate node v is used to receiving in a sampling period, the energy charge model of transmission and idle listening；
S3：Using the routing tree that the above-mentioned energy charge Construction of A Model lifetime is optimal.
Specifically scheme is：
Step S2 includes following operation：
S11:The mathematic expectaion of packet is produced in mono- sampling period of calculate node v and packet institute energy consumption is sent
Take；
S12:All packets and node v produced in calculating using node v child nodes as the subtree of root are used to receive
The energy charge of these packets；
S13:Calculate in each sampling period, node v is expended with the gross energy on idle listening.
Using the routing tree that the tactful component lifetime of greed is optimal in step S3.
In above-mentioned technical proposal, a Mathematical Modeling is devised for tree structure, for accurately describing sensor node
Energy charge, and the application of mathematical model designed is carried out into the lifetime of peak optimizating network in constructing efficient tree.
Brief description of the drawings
Fig. 1 is typical wireless sensor network structure；
Fig. 2 a are the network topological diagrams of the tree constructed using the present invention；
Fig. 2 b are that the packet of the tree constructed using the present invention produces probability graph；
Fig. 2 c are the lifetime optimal trees of the tree constructed using the present invention；
Fig. 3 is the network topological diagram of normalized 100 nodes；
Fig. 4 a are the datagrams of 5000 temperature and solar radiation before certain sensor；
Fig. 4 b are the percentage for the sensor node for sending temperature data in each sampling period as different data are fuzzy
The variation diagram of threshold value
Fig. 4 c are the percentage for the sensor node for sending solar radiation data in each sampling period with different numbers
According to the variation diagram of Fuzzy Threshold.
Embodiment
In order that objects and advantages of the present invention are more clearly understood, the present invention is carried out specifically with reference to embodiments
It is bright.It should be appreciated that following word is only to describe one or more of specific embodiments of the invention, not to the present invention
The protection domain specifically asked carries out considered critical.
The technical scheme that the present invention takes, comprises the following steps：
S1：First, TPO scheduling mechanisms are introduced to quantify energy charge.TPO(Traffic Pattern Oblivious)
Dispatching algorithm be used to construct transmission schedule, and node is according to the collisionless transceiving data of this transmission schedule.TPO is a kind of
Time division multiple acess (TDMA) algorithm, it has been proved to be energy efficient.The introducing of TPO scheduling mechanisms so that quantify node
Energy charge be possibly realized.
In order to quantify energy expenses of each node v in TPO dispatch lists, it will be assumed that in each sampling period, node v
It is p that data, which produce probability,i(i sends the probability of data to base station).Nodes v send a packet used by energy be
et, it is e to intercept the energy used by a secondary channelr.The generation of packet meets independence on Different sampling period, different nodes
With distribution.
S2：Calculate node v is used to receiving in the one sampling period, the energy of transmission and idle listening.
S21：Calculate node v is in one sampling period (Tv) in produce packet mathematic expectaion and send packet
Energy charge；
S22：All packets produced in calculating using node v child nodes as the subtree of root, and node v are used to receive
The energy charge of these packets；
S23：In TPO scheduling methods, node v need not carry out idle listening, child nodes that and if only if to child nodes k
K sends data in each of which timeslice.Calculate in each sampling period, gross energies of the node v on idle listening.
The superposition of energy ezpenditure three parts more than total within a sampling period node v.
S3：As above the energy charge model designed is used to construct lifetime optimal routing tree.Using a kind of greed
Strategy, the node in network is added one by one in routing tree T to be constructed.During beginning, T only includes aggregation node s,
In the iteration of each step, construction set E, set E includes the node of all and tree T-phase neighbour (at least with a section in tree T
Point is neighbor node).During each iteration, the node in only set E is just considered to be added in current tree T.For each
Individual node v ∈ E, this method checks the neighbor node of all node v in current T, selects suitable neighbor node and node v to connect
Connect.If node v is connected with the neighbor node u in T, the only energy ezpenditure in the node from node u to aggregation node s on path
Speed can produce change.So, these nodes recalculate the rate of energy dissipation of oneself, and record most short on this path
Lifetime.For all node v ∈ E and possible node v father node u, this method is possible to cause current T lifetime
Maximized link (u, v) is added in T, until T covers nodes all in network, as shown in Fig. 2 a, 2b, 2c.
The present invention is specifically described below by way of a specific embodiment：
The first step, arranges network；
Reference picture 3, by 100 sensor nodes being placed in the square area of one at random, in order to allow whole network
Connection is kept, the transmission radius of each node is set to 0.25 in topological diagram.
Second step, chooses data sequence, sets threshold value；
Reference picture 4a, is increased income the temperature collected by LEM projects and the sensor of solar radiation using University of Washington
Data sequence is tested.Each data sequence is containing 3000000 sensing datas are had more than, wherein continuous two sensor numbers
According to sampling time interval 1 second.Exist in order to which base station to be adopted to the control of the deviation between the data being collected into, and real sensing data
Within e (can regard error range as), the data grid technology that each node is reported with the last time sets a threshold value [u-e, u+e].
In each sampling period, only when the data that each node is collected into, beyond the scope of the threshold value set by this node, node
Just need to transmit data to base station, and update the scope of threshold value.Otherwise, node need not report and submit any content.Reference picture 4b
With Fig. 4 c, when e value becomes big, threshold range becomes big accordingly, and the data volume that each node is reported is decreased.
3rd step, sets node energy；
The energy supply for setting base station is infinite, and the energy of sensor node is limited, and sensor sends one
Individual packet consumes the energy of 1 unit, and monitors the energy that a secondary channel will take for 0.75 unit.The primary power phase of node
Together, it is set to 50,000 energy unit.The lifetime of network be defined as since just into network first node energy
The time exhausted.
4th step, estimates that the data of each node report and submit probability；
Respectively to two kinds of data sequences of temperature and solar radiation, different e values are set, each section of observation within a period of time
The datagram of point is given a present condition, and reports and submits number of times that the period is normalized data, is reported and submitted as corresponding with error range e
Probability.
5th step, constructs lifetime optimal tree；
With the strategy of greed, by iteration, node is added one by one in routing tree T to be constructed.
The present invention fails equipment, mechanism, component and the operating method of detailed description, and those of ordinary skill in the art are optional
Used and implemented with the equipment with identical function, mechanism, component and operating method commonly used in the art.Or according to life
Identical equipment, mechanism, component and the operating method that general knowledge living is selected are used and implemented.
The above is only the preferred embodiment of the present invention, it is noted that for the ordinary skill people of the art
For member, after content described in the present invention is known, under the premise without departing from the principles of the invention, it can also be made some
Equal conversion and replacement, these, which convert and substituted on an equal basis, also should be regarded as belonging to protection scope of the present invention.
Claims (3)
1. a kind of lifetime based on dynamic data pattern optimizes the building method of tree, it is characterised in that：Including following operation
Step：
S1：Energy charge is quantified using TPO scheduling mechanisms；
S2：Calculate node v is used to receiving in a sampling period, the energy charge model of transmission and idle listening；
S3：Using the routing tree that the above-mentioned energy charge Construction of A Model lifetime is optimal.
2. the lifetime according to claim 1 based on dynamic data pattern optimizes the building method of tree, its feature exists
In step S2 includes following operation：
S11:The mathematic expectaion of packet is produced in mono- sampling period of calculate node v and packet institute energy charge is sent；
S12:All packets and node v produced in calculating using node v child nodes as the subtree of root are used to receive these
The energy charge of packet；
S13:Calculate in each sampling period, node v is expended with the gross energy on idle listening.
3. the lifetime according to claim 1 based on dynamic data pattern optimizes the building method of tree, its feature exists
In using the routing tree that the tactful component lifetime of greed is optimal in step S3.
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Cited By (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN108076499A (en) * | 2017-12-28 | 2018-05-25 | 西安电子科技大学 | A kind of Heuristic construction method of lifetime optimal routing |
| CN109982357A (en) * | 2019-04-09 | 2019-07-05 | 合肥工业大学 | A kind of sampling period optimization method based on multi-hop wireless sensor network |
| CN112333729A (en) * | 2020-10-12 | 2021-02-05 | 深圳市华奥通通信技术有限公司 | Communication power consumption calculation method, system, device and storage medium |
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