CN103327513B - Intelligent data acquisition method - Google Patents

Intelligent data acquisition method Download PDF

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CN103327513B
CN103327513B CN201310222664.8A CN201310222664A CN103327513B CN 103327513 B CN103327513 B CN 103327513B CN 201310222664 A CN201310222664 A CN 201310222664A CN 103327513 B CN103327513 B CN 103327513B
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bunch
data
leader cluster
agency
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CN103327513A (en
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蒋峥峥
高瞻
陆建新
陈继红
顾翔
严燕
王丹丹
石明波
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Huaibei Shengshi Haoming Technology Service Co ltd
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Nantong University
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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
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    • Y02D30/70—Reducing energy consumption in communication networks in wireless communication networks

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Abstract

The invention discloses a kind of intelligent data acquisition method, task be embedded in each mobile agent, send on wireless sensor network, afterwards, mobile agent independently creates its process, and asynchronous, autonomous completes born task; What mobile agent had not by the feature that data migration calculates by calculating migration data, decreases the flow of online initial data, reduces offered load, and can eliminate the hidden danger that network delay brings.

Description

Intelligent data acquisition method
The application is application number: 201110232806.X, the applying date: 2011.8.15, the divisional application of title " the wireless sensor network intelligent data acquisition method based on mobile agent ".
Technical field
The present invention relates to a kind of method of intelligent data acquisition in massive wireless sensor, mainly utilize distributed computing technology and artificial intelligence technology to solve the acquisition of mass data in wireless sensor network, transmission, search problem, belong to the cross-application field of distributed computing technology, artificial intelligence technology and wireless sensor network data integration technology.
Background technology
Wireless sensor network is by having perception, the network that process and the sensor node of wireless communication ability are formed by Ad hoc mode, it can make us extend to more wide interactive space, obtain dynamic state information around us, realize for the more accurate and deep understanding in the peripheral world and control, thus in military affairs, environment, healthy, family, traffic, manufacturing industry, business, facilities management, transport, safety, the fields such as space exploration and disaster rescue have broad application prospects, to the live and work mode of people, industry development and change produce revolutionary impact.
Wireless sensor network be a kind of wireless, can self-organizing, fault-tolerance is high, dynamic, application is relevant, data-centered novel information network, the information of monitored target in the perception that object is to cooperate, acquisition and processing network's coverage area.Sensor node normally random placement, in certain area, performs monitoring task or positions external object and follow the trail of.Therefore, the data collected by sensor node send the top priority that user is wireless sensor network quickly and accurately to.Good data management technique can improve the efficiency of sensor node collaborative sensing, collection, process, distributing data information, and then determines availability and the validity of wireless sensor network better.Different from traditional Ad-hoc network (Ad hoc network), the communication capacity of wireless sensor network is limited, dynamic strong, and node power finite energy, computing capability are limited, quantity has a very wide distribution greatly, perception data stream is unlimited in real time.Due to the large and random distribution of sensor node quantity, adjacent transducer is monitored obtained data to same event and is had similitude.The limited feature of the energy of wireless sensor network node, memory space and computing capability makes again being transmitted in of redundant data will consume too much energy to a certain extent, shortens the life span of whole network.Therefore, in order to better manage perception data, in the data transmission procedure of massive wireless sensor, need a kind of special collecting method of applicable massive wireless sensor.
Mobile proxy technology is a kind of network distributed computing technology, in distributed network environment, realize high efficiency between colony with loose, loosely-coupled, the moveable intelligent structure of a component in essence mutually to cooperate with combining and solve, solve the conflict under multiple cooperative strategy and scheme and contradiction.The parallel network that artificial neural network technology is made up of some simple processing units, be modern neuro biology and cognitive science to the neural simplification to people that human information treatment research performance basis proposes, abstract model, there is large-scale parallel simulation process, nonlinear mapping, adaptive learning, the effect of the network overall situation, the good feature such as fault-tolerance and robust calculating.Mobile agent has independence, initiative, reactivity, mobility, the characteristic such as social and intelligent, the collaborative and autonomous of system can be realized, can be applied in the data management of wireless sensor node very well, and solve more insoluble key issues in this field current.Especially, in wireless sensor network limited bandwidth, energy constraint, unstable dynamic wireless environments, mobile agent contributes to reducing data traffic and communication overhead, the amount of calculation of minimizing perception data and amount of redundancy, conserve energy, effectively extends network system life cycle; The adaptive learning training of artificial neural network technology contributes to improving the ageing of the transfer of data of key message when reducing message transmission rate, minimizing data traffic.
Summary of the invention
The object of the present invention is to provide a kind of data collection problems solving massive wireless sensor interior joint, thus the intelligent data acquisition method providing effectively and ensure reliably for the various application of wireless sensor network.
Technical solution of the present invention is:
Based on a wireless sensor network intelligent data acquisition method for mobile agent, it is characterized in that: comprise the following steps:
1) during initial condition, only there is sink node and ordinary node two category node in network, ordinary node utilizes to distribute to act on behalf of and the node serial number of oneself, position, timestamp information is sent to the node being positioned at its communication context around;
2) each ordinary node safeguards an anticipatory remark earth's surface, after receiving the information distributing and act on behalf of the neighbor node sent, above-mentioned information is stored in this earth's surface, store field in this earth's surface of node to have: node ID, position, dump energy E, state, bunch ID, bunch head number of times, timestamp, wherein mode field value has: common, bunch first two, during initial condition the mode field of all ordinary nodes all value be common; The initial value of field bunch ID and bunch head number of times is 0;
3) sink node distributes intelligent networking agency to all ordinary nodes in net, sub-clustering is carried out to nodes all in network, and filter out leader cluster node, other node broadcasts in network, revise the value of corresponding state, bunch ID and bunch head time field in this earth's surface simultaneously;
4) according to user's requirement, sink node by distribute agency task is distributed to each leader cluster node, then by leader cluster node successively to bunch in member node distribute; Distribute agency and will carry following information: task ID, type of detection, alarm conditions, alarm level, data sampling frequency, state, timestamp;
5), after ordinary node receives the task of distributing agency, perform data intelligent acquisition flow process, and under certain data sampling frequency, the data collected are passed to sink node;
6) in order to ensure leader cluster node unduly consumed energy, the method repeating step 3) after certain hour re-starts the election of bunch head.
In step 3), acted on behalf of the election carrying out bunch head by intelligent networking at each bunch of interior joint, concrete grammar is as follows:
(1) the intelligent networking agency that sink node distributes carries default parameter and in net, each node moves, and the parameter preset has: the initial value of the round r of election of cluster head, r is 1; Bunch head is by the number of times r elected num, r numinitial value be 0; Predetermined bunch head number accounts for the percentage P of all the sensors node total number; Intelligent networking agency scans the whole network node on network, and in statistics this earth's surface of sensor node, the value of field bunch head number of times is less than or equal to r numthe number of node, stored in the variable n of intelligent networking agency pin, the variable n that in statistics the whole network, effective node total number is acted on behalf of stored in intelligent networking tin;
(2) n is calculated t* the value of P, with n pcompare, if n p>n t* P, calculates value, stored in intelligent networking agency variable T sin;
(3) according to formula 1. computing node energy threshold E,
E = cycle × ( C degree × E DA + Σ i = 1 C degree k i × ( E elec + ϵ fs × d i 2 ) + Σ i = 1 C degree k i ' × E elec +
l × E elec + l × ϵ mp × d 2 4 + l ' × E elec ) ①
Formula 1. in, cycle represents the Data Collection number of times of often taking turns, C degreerepresent bunch in number of members, E dArepresent the energy that fused data consumes and the energy that data processing needs, E elecfor sensor node electron energy consumes, by the decision such as digital coding, modulation, filtering, spread spectrum of signal, ε fsand ε mpbe respectively wireless electrical signals in free space and multidiameter fading channel and amplify the energy consumed, Σ i = 1 C degree k i × ( E elec + ϵ fs × d i 2 ) + Σ i = 1 C degree k i ' × E elec Represent the transmission that node needs when bunch interior nodes that distance is d sends k bit information and received energy expense, l × E elec+ l × ε mp× d 2 4+ l ' × E elecrepresent that node is d to distance 2sink the node transmission that needs and received energy expense when sending l bit information.Preset by sink node, acted on behalf of by the intelligent networking distributed and carry calculating;
(4) intelligent networking agency obtains the value of field dump energy E in this earth's surface of node, stored in the variable E of intelligent networking agency nin,
(5) by variable E nvalue and step 33) in the energy threshold E that calculates compare, if E n>E, λ=1; If E n≤ E, λ=0; Compute cluster head valve value T n=λ * T s;
(6) node produces the number between 0 ~ 1 at random, by this number and step 35) in bunch head valve value T that calculates ncompare, if be less than T n, this ordinary node just becomes a leader cluster node, now, and leader cluster node amendment T nvalue be 0, revise state in this earth's surface, bunch ID, bunch head time field: change the value of mode field into a bunch head simultaneously, insert the value of bunch ID of generation, a bunch value for head number of times is added 1 automatically; Leader cluster node sends ADV broadcast packet to network simultaneously, declares it oneself is a bunch head;
(7) intelligent networking is acted on behalf of the result of carrying election of cluster head and is returned sink node, and round r value adds 1 automatically simultaneously;
(8) after ordinary node receives the next broadcast packet of bunch hair, this packet is added the receiving queue of oneself, then from oneself receiving queue, choose a nearest bunch head, add its bunch, revise the value of field bunch ID in this earth's surface, then empty receiving queue.And send packet to the leader cluster node of oneself lishu;
(9), after leader cluster node receives the datagram that ordinary node sends, the information of node is added in bunch members list of oneself.Leader cluster node, according to the number of member node in this bunch, produces a tdma slot table, specifies each member node can send the period of data, and to bunch in member send broadcast.
In step 5), use Intelligent Fusion agency and prompt alarm agency to carry out intelligent processing method to the data that node collects, concrete methods of realizing is as follows:
(1) leader cluster node by distribute agency to bunch in all nodes distribute task, the task definition distributed comprises data acquisition session, data alarm conditions, message transmission rate etc.; Leader cluster node distributes Intelligent Fusion agency to a bunch interior nodes simultaneously;
(2), after a bunch interior nodes collects data, the task according to distributing agency's transmission carries out com-parison and analysis, is saved in local data base simultaneously, acts on behalf of data the MRI data blending algorithm carried carry out data fusion calculating to the data collected by Intelligent Fusion;
(3) bunch interior nodes is when analyzing the data collected, if find that data reach alert if, then according to the alert levels that task is preset, send prompt alarm to be acted on behalf of immediately and carry the information transfers such as alarm content, Alert Level, timestamp to leader cluster node, collect warning message by leader cluster node and pass to sink node immediately; Then, prompt alarm agency moves back origin node by leader cluster node again;
(4) data analysis that the prompt alarm agency moving back origin node continues gathering compares, if find that alarm disappears, send prompt alarm to be acted on behalf of immediately and carry information transfer such as elimination alarm content, timestamp etc. to leader cluster node, elimination warning information is passed to sink node by leader cluster node; Then, prompt alarm agency moves back origin node by leader cluster node again;
Bunch (5) in, each node is in the data transfer period that Intelligent Fusion agency presets, and according to the specific tasks content of user, act on behalf of the BP neural network algorithm carried learn the data gathered, to train and non-linear judgement is predicted by Intelligent Fusion;
(6) Intelligent Fusion agency carries MRI algorithm, BP neural net intelligent algorithm program and related data, bunch in move between each node, in completing bunch, the data fusion of multiple node calculates and non-linear judgement is predicted;
(7) data of collection and Intelligent Fusion are acted on behalf of predicting the outcome of learning training and are compared by sensor node, if reach early-warning conditions, then acted on behalf of by prompt alarm and carry the information transfers such as early warning content, Alert Level, timestamp to leader cluster node, early warning information is passed to sink node by leader cluster node immediately, improves message transmission rate simultaneously; Then, prompt alarm agency moves back origin node by leader cluster node;
(8) data of collection and Intelligent Fusion are acted on behalf of predicting the outcome of learning training and are compared by sensor node, if the data gathered get back to normal range (NR), all clear, acted on behalf of by prompt alarm and carry the information transfers such as all clear content, timestamp to leader cluster node, early warning is removed information and is passed to sink node by leader cluster node, reduces message transmission rate simultaneously; Then, prompt alarm agency moves back origin node by leader cluster node;
(9) according to the message transmission rate of Intelligent Fusion proxy setup, sensor node is by the Data Migration after fusion to neighbor node, and the data fusion completing multiple node calculates and BP neural network learning training calculating; After in bunch, each node all moves, Intelligent Fusion agency carries the Data Migration after fusion to leader cluster node, by leader cluster node, data is passed to sink node, carries out further data processing by user; Then, the mission requirements that leader cluster node distributes according to sink node, again send Intelligent Fusion act on behalf of to bunch in each node, repeat the method for above-mentioned steps (1) ~ (8) and realize intelligent data acquisition.
The inventive method is based on the characteristic of mobile agent, in massive wireless sensor, propose a kind of new method of node intelligent data acquisition, be mainly used in the problem of the mass data collection transmission solving massive wireless sensor node, by this method, do not need to add extra hardware to sensor node, the communication consumption between sensor node can be reduced, reduce node calculate amount, improve the intelligent and ageing of sensor node data collection.We provide specific description below:
1. task is embedded in each mobile agent by this method, sends on wireless sensor network, and afterwards, mobile agent independently creates its process, and asynchronous, autonomous completes born task; What mobile agent had not by the feature that data migration calculates by calculating migration data, decreases the flow of online initial data, reduces offered load, and can eliminate the hidden danger that network delay brings.
2. by intelligent networking agency, a large-scale wireless sensor network is divided into multiple bunches, carry out the acquisition of information one by one and gather, make sensor node from short haul connection in original long haul communication becomes bunch, save the communication energy consumption of sensor node, improve operational efficiency; Consider that leader cluster node energy ezpenditure is large, finite energy, intelligent networking agency in conjunction with simple energy balane, by net interior nodes elected bunch head in turn, ensure that the equilibrium consumption of net interior nodes energy, extends the life cycle of network in cluster algorithm.
3. prompt alarm is acted on behalf of the abnormal information collected by sensor node and is passed to sink node immediately, improves the transmission rate of critical data, reduces the time delay of network.
4. by Intelligent Fusion agency, Intelligent Fusion is carried out, eliminate redundancy information and hash to the data gathered, only necessary information is passed to sink node; The characteristic of program and data is carried by mobile agent, originally the data fusion completed by leader cluster node or sink node is calculated, share in each bunch and ordinary node realizes calculate, decrease the expense of the data volume of leader cluster node and sink node, amount of calculation and communication energy, can to obtain in wireless sensor network coverage while Monitoring Data guarantee user, greatly reduce the volume of transmitted data in net, thus extend the life cycle of network.
5. Intelligent Fusion agency predicts the data gathered according to the BP neural network learning training algorithm carried, once send prompt alarm to act on behalf of after predicting abnormal conditions immediately send early warning information to sink node, dynamic adjusting data transmission rate simultaneously, thus the monitoring selectively strengthened abnormal area, improve the ageing and accuracy of wireless sensor network data monitoring.
Accompanying drawing explanation
Below in conjunction with drawings and Examples, the invention will be further described.
Fig. 1 is the structure chart of massive wireless sensor.Illustrate that wireless sensor network is carried out sub-clustering by intelligent networking agency by wireless sensor node.
Fig. 2 is the flow chart of the execution intelligent data acquisition of the Intelligent Fusion agency that leader cluster node distributes to bunch interior nodes.
Fig. 3 is Intelligent Fusion agency, prompt alarm agency bunch in the agency that to realize in the process of intelligent data acquisition send, perform, move schematic diagram.
In Fig. 1: 1, sink node, 2, leader cluster node, 3, communication link, 4, ordinary node, 5, bunch;
In Fig. 3: 6, leader cluster node, 7, bunch interior nodes, 8, migration path, 9, task is distributed, 10, prompt alarm agency, 11, information fusion, 12, carry the prompt alarm agency of important warning message, 13, carry eliminate warning information prompt alarm agency, 14, carry intelligent early-warning information prompt alarm agency.
Embodiment
First we provide the definition of several special movement agency:
Intelligent networking is acted on behalf of: utilize the mobility of mobile agent that whole wireless sensor network is divided into several bunches, so that node is when to sink node-node transmission data, reduces the jumping figure of information transmission thus the energy consumption of saving node.
Distribute agency: in wireless sensor network, node utilizes the mobility of mobile agent the mission bit stream of perception will send to neighbouring sensor node by inundation strategy, provides prerequisite for each node in network carries out perception data process.
Prompt alarm is acted on behalf of: the mobility utilizing mobile agent, is immediately passed to sink node by the information reaching early warning and alarm warning requirements in perception data process.
Intelligent Fusion is acted on behalf of: acting on behalf of according to distributing the perception task requirement that distributes, in conjunction with the BP neural network algorithm of artificial intelligence, utilizing mobile agent to carry the characteristic of data, merging perception data, early warning.
Architecture
Fig. 1 gives the wireless sensor network system assumption diagram that uses this collecting method.In wireless sensor network, sensor node is divided into some bunches.Be responsible for collecting by a leader cluster node data that all ordinary nodes in this bunch of region collect, and finally pass to sink node for each bunch.Ordinary node in each bunch just can arrive leader cluster node by single-hop or several jumping.As from the foregoing, the wireless sensor node in this architecture is mainly divided into following three classes:
Ordinary node: this category node is present in some bunch, be responsible for perception environmental data, and the data collected finally is sent to sink node by the collecting method adopting us to propose.These node energies are limited, and disposal ability is limited, have an opportunity dynamically to be selected to leader cluster node in turn.Ordinary node regularly and its neighbor node exchange message safeguard a neighbor table.
Leader cluster node: selected dynamically in turn by ordinary node.Basic thought be selection one bunch in the strong and sufficient node of energy of communication capacity.The neighbor table of all ordinary node lists and other leader cluster nodes in preserving in leader cluster node bunch.
Sink node: have very strong communication and disposal ability, for passing on user to the detection requirement of whole wireless sensor network, collects the information in whole wireless sensor network, and by satellite or wired mode, information can be passed to end user.
Particularity being devoted to for massive wireless sensor ensures that node collects the accuracy of information and ageing, take into account the network traffic data and data amount of calculation that reduce and produce in node data fusion calculation process, the present invention proposes the node intelligent data acquisition plan based on mobile agent in a kind of massive wireless sensor: a massive wireless sensor is divided into several bunches by the mobility that intelligent networking is acted on behalf of in massive wireless sensor and inundation strategy; Task of needing wireless sensor network to complete is sent by sink node and is distributed agency to each bunch by user; Node carries out information gathering according to the mission requirements distributing agency, such as, if find the emergency needing to report to the police, the Information abnormity of monitoring point, is then acted on behalf of by prompt alarm immediately and passes warning information back sink node; If the information of node monitors is normal, do not need to report to the police, then carry out data fusion according to the mission requirements distributed by Intelligent Fusion agency and operate and intelligent early-warning calculating, adjust data transmission frequencies simultaneously, at set intervals by merge after data back to sink node, transfer to user to process.
Wireless sensor network intelligent data acquisition method based on mobile agent of the present invention by intelligent networking agency, distribute agency, mutual cooperation that prompt alarm agency, Intelligent Fusion act on behalf of these mobile agents, complete the intelligent data acquisition of wireless sensor network node, the step that described method comprises is:
Step is 1.) initial condition time, only there is sink node and ordinary node two category node in network, ordinary node utilizes and distributes agency the node serial number of oneself, position, timestamp information are sent to the node being positioned at its communication context around;
Step is 2.) each ordinary node safeguards an anticipatory remark earth's surface, after receiving the information distributing and act on behalf of the neighbor node sent, above-mentioned information is stored in this earth's surface, store field in this earth's surface of node to have: node ID, position, dump energy E, state, bunch ID, bunch head number of times, timestamp, wherein mode field value has: common, bunch first two, during initial condition the mode field of all ordinary nodes all value be common; The initial value of field bunch ID and bunch head number of times is 0;
Step is 3.) sink node to net in all ordinary nodes distribute intelligent networking agency, sub-clustering is carried out to nodes all in network, and filter out leader cluster node, other node broadcasts in network, revise the value of corresponding state, bunch ID and bunch head time field in this earth's surface simultaneously;
Step is 4.) according to user's requirement, sink node by distribute agency task is distributed to each leader cluster node, then by leader cluster node successively to bunch in member node distribute; Distribute agency and will carry following information: task ID, type of detection, alarm conditions, alarm level, data sampling frequency, state, timestamp;
Step is 5.) after ordinary node receives the task of distributing agency, perform data intelligence collecting flowchart as shown in Figure 2, and under certain data sampling frequency, the data collected are passed to sink node.
Step is 6.) in order to ensure leader cluster node unduly consumed energy, the method repeating step 3) after certain hour re-starts the election of bunch head.
In step 3.), acted on behalf of the election carrying out bunch head by intelligent networking at each bunch of interior joint, concrete grammar is as follows:
31) the intelligent networking agency that .sink node distributes carries default parameter and in net, each node moves, and the parameter preset has: the initial value of the round r of election of cluster head, r is 1; Bunch head is by the number of times r elected num, r numinitial value be 0; Predetermined bunch head number accounts for the percentage P of all the sensors node total number; Intelligent networking agency scans the whole network node on network, and in statistics this earth's surface of sensor node, the value of field bunch head number of times is less than or equal to r numthe number of node, stored in the variable n of intelligent networking agency pin, the variable n that in statistics the whole network, effective node total number is acted on behalf of stored in intelligent networking tin;
32). calculate n t* the value of P, with n pcompare, if n p>n t* P, calculates value, stored in intelligent networking agency variable T sin;
33). according to formula 1. computing node energy threshold E,
E = cycle × ( C degree × E DA + Σ i = 1 C degree k i × ( E elec + ϵ fs × d i 2 ) + Σ i = 1 C degree k i ' × E elec +
l × E elec + l × ϵ mp × d 2 4 + l ' × E elec ) ①
Formula 1. in, cycle represents the Data Collection number of times of often taking turns, C degreerepresent bunch in number of members, E dArepresent the energy that fused data consumes and the energy that data processing needs, E elecfor sensor node electron energy consumes, by the decision such as digital coding, modulation, filtering, spread spectrum of signal, ε fsand ε mpbe respectively wireless electrical signals in free space and multidiameter fading channel and amplify the energy consumed, Σ i = 1 C degree k i × ( E elec + ϵ fs × d i 2 ) + Σ i = 1 C degree k i ' × E elec Represent the transmission that node needs when bunch interior nodes that distance is d sends k bit information and received energy expense, l × E elec+ l × ε mp× d 2 4+ l ' × E elecrepresent that node is d to distance 2sink the node transmission that needs and received energy expense when sending l bit information.Preset by sink node, acted on behalf of by the intelligent networking distributed and carry calculating;
34). intelligent networking agency obtains the value of field dump energy E in this earth's surface of node, stored in the variable E of intelligent networking agency nin,
35). by variable E nvalue and step 33) in the energy threshold E that calculates compare, if E n>E, λ=1; If E n≤ E, λ=0; Compute cluster head valve value T n=λ * T s;
36). node produces the number between 0 ~ 1 at random, by this number and step 35) in bunch head valve value T that calculates ncompare, if be less than T n, this ordinary node just becomes a leader cluster node, now, and leader cluster node amendment T nvalue be 0, revise state in this earth's surface, bunch ID, bunch head time field: change the value of mode field into a bunch head simultaneously, insert the value of bunch ID of generation, a bunch value for head number of times is added 1 automatically; Leader cluster node sends ADV broadcast packet to network simultaneously, declares it oneself is a bunch head;
37). the result that intelligent networking agency carries election of cluster head returns sink node, and round r value adds 1 automatically simultaneously;
38). after ordinary node receives the next broadcast packet of bunch hair, this packet is added the receiving queue of oneself, then from oneself receiving queue, choose a nearest bunch head, add its bunch, revise the value of field bunch ID in this earth's surface, then empty receiving queue.And send packet to the leader cluster node of oneself lishu;
39). the information of node adds in bunch members list of oneself after receiving the datagram that ordinary node sends by leader cluster node.Leader cluster node, according to the number of member node in this bunch, produces a tdma slot table, specifies each member node can send the period of data, and to bunch in member send broadcast;
Step is 5.) in, Intelligent Fusion agency and prompt alarm agency is used to carry out intelligent processing method to the data that node collects, handling process as shown in Figure 2, Intelligent Fusion agency, prompt alarm agency bunch in realize in the process of intelligent data acquisition that agency sends, performs, transition process as shown in Figure 3.Concrete methods of realizing is as follows:
51). leader cluster node by distribute agency to bunch in all nodes distribute task, the task definition distributed comprises data acquisition session, data alarm conditions, message transmission rate etc.; Leader cluster node distributes Intelligent Fusion agency to a bunch interior nodes simultaneously;
52). after a bunch interior nodes collects data, the task according to distributing agency's transmission carries out com-parison and analysis, is saved in local data base simultaneously, acts on behalf of data the MRI data blending algorithm carried carry out data fusion calculating to the data collected by Intelligent Fusion;
53). bunch interior nodes is when analyzing the data collected, if find that data reach alert if, then according to the alert levels that task is preset, send prompt alarm to be acted on behalf of immediately and carry the information transfers such as alarm content, Alert Level, timestamp to leader cluster node, collect warning message by leader cluster node and pass to sink node immediately; Then, prompt alarm agency moves back origin node by leader cluster node again;
54). the data analysis that the prompt alarm agency moving back origin node continues gathering compares, if find that alarm disappears, send prompt alarm to be acted on behalf of immediately and carry information transfer such as elimination alarm content, timestamp etc. to leader cluster node, elimination warning information is passed to sink node by leader cluster node; Then, prompt alarm agency moves back origin node by leader cluster node again;
55). in bunch, each node is in the data transfer period that Intelligent Fusion agency presets, and according to the specific tasks content of user, is acted on behalf of the BP neural network algorithm carried learn the data gathered, train and non-linear judgement prediction by Intelligent Fusion;
56). Intelligent Fusion agency carries MRI algorithm, BP neural net intelligent algorithm program and related data, bunch in move between each node, in completing bunch, the data fusion of multiple node calculates and non-linear judgement is predicted;
57). the data of collection and Intelligent Fusion are acted on behalf of predicting the outcome of learning training and are compared by sensor node, if reach early-warning conditions, then acted on behalf of by prompt alarm and carry the information transfers such as early warning content, Alert Level, timestamp to leader cluster node, early warning information is passed to sink node by leader cluster node immediately, improves message transmission rate simultaneously; Then, prompt alarm agency moves back origin node by leader cluster node;
58). the data of collection and Intelligent Fusion are acted on behalf of predicting the outcome of learning training and are compared by sensor node, if the data gathered get back to normal range (NR), all clear, acted on behalf of by prompt alarm and carry the information transfers such as all clear content, timestamp to leader cluster node, early warning is removed information and is passed to sink node by leader cluster node, reduces message transmission rate simultaneously; Then, prompt alarm agency moves back origin node by leader cluster node;
59). according to the message transmission rate of Intelligent Fusion proxy setup, sensor node is by the Data Migration after fusion to neighbor node, and the data fusion completing multiple node calculates and BP neural network learning training calculating; After in bunch, each node all moves, Intelligent Fusion agency carries the Data Migration after fusion to leader cluster node, by leader cluster node, data is passed to sink node, carries out further data processing by user; Then, the mission requirements that leader cluster node distributes according to sink node, again send Intelligent Fusion act on behalf of to bunch in each node, repeat step 51) ~ 58) method realize intelligent data acquisition.

Claims (1)

1. an intelligent data acquisition method, is characterized in that: comprise the following steps:
1) during initial condition, only there is sink node and ordinary node two category node in network, ordinary node utilizes to distribute to act on behalf of and the node serial number of oneself, position, timestamp information is sent to the node being positioned at its communication context around;
2) each ordinary node safeguards an anticipatory remark earth's surface, after receiving the information distributing and act on behalf of the neighbor node sent, above-mentioned information is stored in this earth's surface, store field in this earth's surface of node to have: node ID, position, dump energy E, state, bunch ID, bunch head number of times, timestamp, wherein mode field value has: common, bunch first two, during initial condition the mode field of all ordinary nodes all value be common; The initial value of field bunch ID and bunch head number of times is 0;
3) sink node distributes intelligent networking agency to all ordinary nodes in net, sub-clustering is carried out to nodes all in network, and filter out leader cluster node, other node broadcasts in network, revise the value of corresponding state, bunch ID and bunch head time field in this earth's surface simultaneously;
4) according to user's requirement, sink node by distribute agency task is distributed to each leader cluster node, then by leader cluster node successively to bunch in member node distribute; Distribute agency and will carry following information: task ID, type of detection, alarm conditions, alarm level, data sampling frequency, state, timestamp;
5), after ordinary node receives the task of distributing agency, perform data intelligent acquisition flow process, and under certain data sampling frequency, the data collected are passed to sink node;
6) in order to ensure leader cluster node unduly consumed energy, after certain hour, repeat step 3) method re-start the election of bunch head;
Step 5) in, described data intelligence collecting flowchart is as follows:
(1) leader cluster node by distribute agency to bunch in all nodes distribute task, the task definition distributed comprises data acquisition session, data alarm conditions, message transmission rate; Leader cluster node distributes Intelligent Fusion agency to a bunch interior nodes simultaneously;
(2) after a bunch interior nodes collects data, task according to distributing agency's transmission carries out com-parison and analysis, data are saved in local data base simultaneously, act on behalf of by Intelligent Fusion the MRI data blending algorithm carried and data fusion calculating is carried out to the data collected;
(3) bunch interior nodes is when analyzing the data collected, if find that data reach alert if, then according to the alert levels that task is preset, send prompt alarm to be acted on behalf of immediately and carry alarm content, Alert Level, timestamp information move to leader cluster node, collect warning message by leader cluster node and pass to sink node immediately; Then, prompt alarm agency moves back origin node by leader cluster node again;
(4) data analysis that the prompt alarm agency moving back origin node continues gathering compares, if find that alarm disappears, send prompt alarm to be acted on behalf of immediately to carry and eliminate alarm content, timestamp information and move to leader cluster node, elimination warning information is passed to sink node by leader cluster node; Then, prompt alarm agency moves back origin node by leader cluster node again;
Bunch (5) in, each node is in the data transfer period that Intelligent Fusion agency presets, and according to the specific tasks content of user, act on behalf of the BP neural network algorithm carried learn the data gathered, to train and non-linear judgement is predicted by Intelligent Fusion;
(6) Intelligent Fusion agency carries MRI algorithm, BP neural net intelligent algorithm program and related data, bunch in move between each node, in completing bunch, the data fusion of multiple node calculates and non-linear judgement is predicted;
(7) data of collection and Intelligent Fusion are acted on behalf of predicting the outcome of learning training and are compared by sensor node, if reach early-warning conditions, then acted on behalf of by prompt alarm and carry early warning content, Alert Level, timestamp information move to leader cluster node, early warning information is passed to sink node by leader cluster node immediately, improves message transmission rate simultaneously; Then, prompt alarm agency moves back origin node by leader cluster node;
(8) data of collection and Intelligent Fusion are acted on behalf of predicting the outcome of learning training and are compared by sensor node, if the data gathered get back to normal range (NR), all clear, acted on behalf of by prompt alarm and carry all clear content, timestamp information moves to leader cluster node, early warning is removed information and is passed to sink node by leader cluster node, reduces message transmission rate simultaneously; Then, prompt alarm agency moves back origin node by leader cluster node;
(9) according to the message transmission rate of Intelligent Fusion proxy setup, sensor node is by the Data Migration after fusion to neighbor node, and the data fusion completing multiple node calculates and BP neural network learning training calculating; After in bunch, each node all moves, Intelligent Fusion agency carries the Data Migration after fusion to leader cluster node, by leader cluster node, data is passed to sink node, carries out further data processing by user; Then, the mission requirements that leader cluster node distributes according to sink node, again send Intelligent Fusion act on behalf of to bunch in each node, repeat the method for above-mentioned steps (1) ~ (8) and realize intelligent data acquisition;
Step 3) in, acted on behalf of the election carrying out bunch head by intelligent networking at each bunch of interior joint, concrete grammar is as follows:
(1) the intelligent networking agency that sink node distributes carries default parameter and in net, each node moves, and the parameter preset has: the initial value of the round r of election of cluster head, r is 1; Bunch head is by the number of times r elected num, r numinitial value be 0; Predetermined bunch head number accounts for the percentage P of all the sensors node total number; Intelligent networking agency scans the whole network node on network, and in statistics this earth's surface of sensor node, the value of field bunch head number of times is less than or equal to r numthe number of node, stored in the variable n of intelligent networking agency pin, the variable n that in statistics the whole network, effective node total number is acted on behalf of stored in intelligent networking tin;
(2) n is calculated t* the value of P, with n pcompare, if n p>n t* P, calculates value, stored in intelligent networking agency variable T sin;
(3) according to formula 1. computing node energy threshold E,
Formula 1. in, cycle represents the Data Collection number of times of often taking turns, C degreerepresent bunch in number of members, E dArepresent the energy that fused data consumes and the energy that data processing needs, E elecfor sensor node electron energy consumes, determined by the digital coding of signal, modulation, filtering, spread spectrum, ε fsand ε mpbe respectively wireless electrical signals in free space and multidiameter fading channel and amplify the energy consumed, Σ i = 1 C degree k i × ( E elec + ϵ fs × d i 2 ) + Σ i = 1 C degree k i ′ × E elec Represent the transmission that node needs when bunch interior nodes that distance is d sends k bit information and received energy expense, l × E elec+ l × ε mp× d 2 4+ l ' × E elecrepresent that node is d to distance 2sink the node transmission that needs and received energy expense when sending l bit information; Preset by sink node, acted on behalf of by the intelligent networking distributed and carry calculating;
(4) intelligent networking agency obtains the value of field dump energy E in this earth's surface of node, stored in the variable E of intelligent networking agency nin,
(5) by variable E nvalue and step (3) in the energy threshold E that calculates compare, if E n>E, λ=1; If E n≤ E, λ=0; Compute cluster head valve value T n=λ * T s;
(6) node produces the number between 0 ~ 1 at random, by bunch head valve value T calculated in this number and step (5) ncompare, if be less than T n, this ordinary node just becomes a leader cluster node, now, and leader cluster node amendment T nvalue be 0, revise state in this earth's surface, bunch ID, bunch head time field: change the value of mode field into a bunch head simultaneously, insert the value of bunch ID of generation, a bunch value for head number of times is added 1 automatically; Leader cluster node sends ADV broadcast packet to network simultaneously, declares it oneself is a bunch head;
(7) intelligent networking is acted on behalf of the result of carrying election of cluster head and is returned sink node, and round r value adds 1 automatically simultaneously;
(8) after ordinary node receives the next broadcast packet of bunch hair, this packet is added the receiving queue of oneself, then from oneself receiving queue, choose a nearest bunch head, add its bunch, revise the value of field bunch ID in this earth's surface, then empty receiving queue; And send packet to the leader cluster node oneself be subordinate to;
(9), after leader cluster node receives the datagram that ordinary node sends, the information of node is added in bunch members list of oneself; Leader cluster node, according to the number of member node in this bunch, produces a tdma slot table, specifies each member node can send the period of data, and to bunch in member send broadcast.
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