CN1809012A - Wireless sensor network system and method supporting reconstruction of environment adaptive application - Google Patents
Wireless sensor network system and method supporting reconstruction of environment adaptive application Download PDFInfo
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Abstract
This invention relates to wireless sensor network system and its work method to support environment self-adapting, wherein, the system comprises four layers of racks to dynamically sense environment changes and recreate point application tasks multiple sensor points RN and multiple sensor points SN, data collection point and control point. The invention is characterized by the following: introducing self-adapting technique into sensor points with certain number fields to make the sensor point of simple rules to change with environment within certain range.
Description
Technical field
The present invention relates to a kind of support environment self adaptation and use the wireless sensor network system of reconstruct and the method that this system realizes application reconstruct, belong to wireless self-organization network systems technology field.
Background technology
Wireless sensor network is the wireless network that is made of in the wireless Ad Hoc mode a plurality of sensor nodes, be used for the information of the geographic area monitoring target of the perception collaboratively each other of each sensor node, collection and this network coverage of processing, and in time issue monitoring result to the user.
Wireless sensor network is mainly used in things in monitoring environment, the environment and the effect between the object.Because the environment of wireless sensor network work changes easily, and various variation can't predict in advance, and this just requires the application of sensor network to change flexibly along with the variation of environment with reconstruct to upgrade.
At present, the research about wireless sensor network application reconfiguration technique mainly contains the Mate of Berkeley and two kinds of application reconstruct at certain node failure that Hyun-Chong Kim proposes respectively.Wherein, Mate supports the programmable frame structure of sensor node, and this method has defined 24 elementary instructions that sensor node must be supported, all tasks that sensor network is carried out all are that the difference by these instructions disposes and realizes.When the task on the needs modification sensor node, be directly downloaded on the node just passable as long as will carry out the application scenarios of this task.But Mate is the application reconstruct that a kind of one-by-one mode from the PC to the sensor node is carried out, and needs manual the triggering to use reconstruct and specify the sensor node that needs reconstruct, does not consider the automatic reconfiguration problem that sensor network is used.Though Hyun-Chong Kim has proposed a kind of sensor network and used reconstructing method automatically, this method is only considered when scheduling of the application task during certain node failure and reconstruct problem in the network.Because sensor network is the network of a high redundancy, the fault of individual nodes is sustainable, the main starting point that sensor network is used reconstruct should be because the variation and the adjustment of the network application that environmental change causes, the sensor node that at this time needs reconstruct often is not certain node, but the problem of several even many nodes, and Hyun-Chong Kim method is mainly considered the situation of individual node failure, is not suitable for the application reconstruct problem of the sensor network that causes owing to reason that dynamic environment changes.Therefore, how to realize that the sensor network system of the adaptive application reconstruct of a kind of support environment and method of work thereof just become the focus that those skilled in the art pay close attention to.
Summary of the invention
In view of this, the purpose of this invention is to provide a kind of support environment self adaptation and use the wireless sensor network system and the method for work thereof of reconstruct, this wireless sensor network system can be supported the dynamic restructuring of sensing task, promptly reconfigure the monitoring task of network system, make sensor node carry out different application codes at different times, on the sensor node of resource-constrained, realize the reconstruct of sensing task, thereby need not to increase on the basis of too many investment cost, improving the function and the service efficiency of sensor network system greatly.
In order to achieve the above object, the invention provides a kind of support environment self adaptation and use the wireless sensor network system of reconstruct, include: a plurality of sensor nodes, convergence node and Control Node, wherein adopt wireless mode to communicate by letter between the sensor node and between sensor node and the convergence node, adopt Internet or other legacy networks to communicate by letter between convergence node and the Control Node; It is characterized in that: described sensor node has two kinds: script sensor node SN (Script Node) and reconstruct sensor node RN (Reconfiguration Node), both have dynamic perception environmental change and according to the function of application code on the environmental change self-adapting reconstruction node; And described system adopts following level framework:
Control Node is positioned at the superiors, this sensor network system is managed and controls by this node for user or administrative staff;
The convergence node, be positioned at the second layer, interface layer as legacy network and sensor network, promptly the new application scenarios code that the user disposes by Control Node is transferred to each sensor node, and the convergence of each sensor node perception, collection is transferred to Control Node by this node layer;
Script sensor node SN, be positioned at the 3rd layer, be used to deposit the needed application scenarios code of each RN node in self and the range of management thereof, be provided with the application scenarios code and carry out engine, variation that can its environment that is monitored of perception is also carried out new application scenarios code, communicate with the convergence node: application scenarios code of receive downloading and storage, and upload after the sensing data that the RN node sends converged fusion treatment; , communicate during reconstruction applications in environmental change: receive their application scenarios code request message, and pass the application corresponding scripted code down, perhaps directly application corresponding scripted code initiative part is deployed to the RN node with the RN node;
Reconstruct sensor node RN is positioned at the bottom, is provided with the application scenarios code and carries out engine, and variation that can its environment that is monitored of real-time perception is also carried out new application scenarios code; If RN node this locality does not need the application scenarios code carried out, with the application scenarios code that initiatively please look for novelty to its SN node of management.
Described SN is the high-performance sensors node, and its place that is provided with is an advance planning; The RN that quantity is maximum in system, density is maximum is the low performance sensor node, and its setting is at random, does not need advance planning; The Application in Sensing scripted code that described sensor node is carried out includes but not limited to the monitoring program of temperature, humidity, cigarette sense.
The Control Software of described SN node and RN node also has respectively the reconstructed module that is connected with data acquisition module with routing module except the routing module that comprises traditional sensors, data acquisition module, data processing/convergence module, I/O interface module; This reconstructed module is made up of reconstruct decision-making module, experience accumulation module, four submodules of knowledge base and experience storehouse, wherein:
Knowledge base is used to deposit with rule and represents and at the domain knowledge of netinit phase deployment to the node, according to the environmental data of the current collection of knowledge analysis wherein, obtains the contingent change information of environment for sensor node;
The experience storehouse is used for depositing the experience that this sensor node forms at running, i.e. the probability of happening of the rule of certain environmental data of representing with weights environmental change that may cause, and weights are high more, and the probability that respective change takes place is high more; The experience storehouse is empty during initialization, and along with the operation of sensor node, the experience storehouse constantly obtains and the preservation experience by the experience accumulation submodule: the confidence level weights that each is regular;
The experience accumulation submodule is responsible for the formation experience, after each sensor node is reconstructed decision-making, all will revise the confidence level weights of the experience in the experience storehouse with the decision-making judged result;
Experience in the knowledge and experience storehouse in the reconstruct decision-making submodule use knowledge base is carried out reasoning to the current environment status data, judges the variation that current environment takes place, and whether decision needs to trigger application reconstruct and which kind of application scenarios code of reconstruct.
In order to achieve the above object, the present invention also provides a kind of support environment self adaptation to use the method for work of the wireless sensor network system of reconstruct, it is characterized in that: comprise the steps:
(1) network and sensor node are carried out initialization operation;
(2) sensor node perception environmental change: the environmental data that the sensor node collection is monitored, and utilize the experience that accumulates in the predefined domain knowledge and experience storehouse in the knowledge base that environmental data is analyzed, judge whether environment changes;
(3) sensor node triggers and uses reconstruct: according to the variation of environment, sensor node judges whether to need to trigger application reconstruct, trigger if desired and use reconstruct, then obtain the type coding of reconstruction applications script and revise the experience storehouse, order is carried out subsequent operation then; Otherwise, return step (2);
(4) sensor node obtains the application scenarios code: judge the local application scenarios code that whether has had next operating state correspondence earlier, if having, and redirect execution in step (5); If there is no, judge again whether the dump energy of this node reaches the setting threshold value, if carry out the operation of obtaining required application scenarios code; Otherwise, directly return step (2);
(5) sensor node is carried out the application scenarios code: sensor node is carried out new application scenarios code, realized the reconfiguring of application task after, return step (2).
Described step (1) further comprises following content of operation:
(11) network topology structure initialization: during on-premise network, plan the SN node location earlier, at its periphery a plurality of RN nodes are set at random again, and make each node know the information of adjacent node around it by the inundation method, make the SN node jump as bunch head and one or the double bounce scope in the RN node constitute a reconstruct bunch, by the SN node administration and store self and the reconstruct administered bunch in the RN node application scenarios code that may need;
(12) sensor node knowledge base initialization: when disposing SN and RN node,, manually in advance the knowledge in related application field is arranged in the knowledge base of node according to the different demands in sensor application field;
(13) sensor node operating state initialization: according to the different types of data of sensor node sampling, sample frequency with to the different disposal method of sampled data, select the application corresponding scripted code, be in the application scenarios code of different operating state as sensor node; Simultaneously, adopt finite-state automata to represent the transforming relationship of each operating state of this node under the varying environment condition, and the initialization state that each sensor node is set.
Application knowledge in the described step (12) is that sensor network need monitor or the various environmental abnormality incidents of user's interest by enumerating, extract the environmental data condition that may cause taking place these anomalous events again, the corresponding relation of this environmental data condition and anomalous event is exactly a knowledge, and adopt rule format to represent it: P → Q, or IF P THEN Q; In the formula, prerequisite P is the environmental data condition, and conclusion Q is the environmental abnormality incident; If P sets up, Q as a result then takes place.
Described step (2) further comprises following content of operation:
(21) gather environmental data: sensor node is regularly gathered corresponding environmental data according to the present located operating state;
(22) whether testing environment changes: the knowledge that sensor node calls earlier in the knowledge base is carried out rules-based analysis to the current environment data, if can only obtain unique conclusion, promptly next operating state that changes over to according to finite-state automata is unique, and then directly execution in step (3) triggers the operation of using reconstruct; If conclusion is not unique, then utilize the experience in the experience storehouse, next operating state of selecting the most probable generation is as new operating state, simultaneously, judged result is stored in the node experience storehouse as experience, and recomputates each regular confidence level weights, execution in step (3) then.
Described step (3) further comprises following content of operation:
(31) reconstruct decision-making: sensor node compares its next operating state and current working state because of the environmental change initiation, judges whether to use reconstruct; If both are inequality, order is carried out subsequent operation; Otherwise, need not use reconstruct, return step (2);
(32) revise the experience storehouse: sensor node obtains corresponding relation between this environmental data and its next operating state according to the conclusion of environmental data and reconstruct decision-making, concerns confidence level weights regular in the modification experience storehouse according to this;
(33) type coding of acquisition reconstruction applications script: sensor node is according to the table of comparisons of node operating state in the internal memory and node application scenarios type of code, and judgement need be used the application scenarios type of code of reconstruct.
The computational methods of described each regular confidence level weights are: the rule of write down, add up the frequency of utilization of every rule in the current record at least respectively, using the access times of the rule of use and last time in the recent period continuously, with these results by after setting weights and handling, the increment that obtains is a weighted value, the current confidence level weights sum of this weighted value and every rule is exactly the new confidence level weights of each rule, is used for next analysis ratiocination.
Described step (4) further comprises following content of operation:
(41) preparatory function: judge the local application scenarios code that whether has had next operating state correspondence earlier, if having, redirect execution in step (5); If there is no, judge again whether the dump energy of this node reaches the setting threshold value, if order is carried out subsequent operation; Otherwise, directly return step (2);
(42) request down load application scripted code: the RN node sends request down load application script message to SN node and/or the SN node in its reconstruct bunch respectively to other SN node, comprises the type number of the application scenarios code of being asked in this message;
(43) application scenarios code response:
After the SN node is received the request Download Script message of the RN node that it is managed, inquire about its local application scenarios code library,, just this application scenarios code is sent to the RN node of request if the application scenarios code of RN node request is arranged; Otherwise, to this application scenarios code of the SN of other bunches node limited number of time ground inquiry, inquiry times depends on sensor network nodes quantity, reconstruct bunch size and residue energy of node, if obtain required scripted code, then this scripted code is sent to the RN node of request; Perhaps SN node analysis RN node upload data after, initiatively the application corresponding scripted code is downloaded to corresponding RN node; And/or
After other SN nodes are received the request Download Script message of this SN node, inquire about its local application scenarios code library,, just this application scenarios code is sent to the SN node of request if the application scenarios code of SN node request is arranged; Otherwise to this application scenarios code of the SN of other bunches node limited number of time ground inquiry, inquiry times depends on the size and the residue energy of node of network node quantity, reconstruct bunch, if obtain required scripted code, then this scripted code is sent to the RN node of request.
The application reconstructing method of prior art mainly considers to carry out the scheduling and the reconstruct of application task under the situation of some node failure, system and method for the present invention improves it and innovates.Because sensor network is the network of high redundancy, the fault of individual nodes is sustainable, the principal element that sensor network is used reconstruct should be because the adaptation and the adjustment of the caused network application of environmental change, the sensor node that at this time needs reconstruct often is not certain node, but many nodes, therefore characteristics of the present invention are that the application self-adapting technology is incorporated into sensor node: at the domain knowledge of sensor node deploy some (because the node storage capacity is limited), make sensor node have the reasoning intelligence of simple logic rule, can be along with the application of oneself be adjusted in the variation of environmental data adaptively in setting range, thus make sensor network adapt to the automatic operation under the long-time unattended environment and the needs of adjustment better.
Description of drawings
Fig. 1 is the wireless sensor network system structure composition schematic diagram that support environment self adaptation of the present invention is used reconstruct.
Fig. 2 is that the software module structure of SN node and RN node is formed schematic diagram.
Fig. 3 is that wireless sensor network system of the present invention carries out the operational flowchart that environment self-adaption is used the implementation method of reconstruct.
Fig. 4 is the schematic diagram of sensor node operating state automaton.
Fig. 5 is the corresponding relation figure of knowledge and operating state automaton.
Fig. 6 is the state transitions schematic diagram of the corresponding different Condition of Environment Changes of equivalent environment data.
Fig. 7 is the sequential chart that sensor node obtains interacting message in the process of scripted code.
Fig. 8 is the sensor node operating state transition diagram among the fire monitoring system embodiment.
Fig. 9 is the sensor node temperature anomaly state transitions schematic diagram among the fire monitoring system embodiment.
Embodiment
For making the purpose, technical solutions and advantages of the present invention clearer, the present invention is described in further detail below in conjunction with accompanying drawing.
Referring to Fig. 1, the present invention is the wireless sensor network system that a kind of support environment self adaptation is used reconstruct, form by a plurality of sensor nodes, convergence node and Control Node, wherein sensor node has two kinds: script sensor node SN and reconstruct sensor node RN, both have dynamic perception environmental change and according to the function of application scenarios code on the environmental change self-adapting reconstruction node; Adopt wireless mode to communicate by letter between the sensor node and between sensor node and the convergence node, adopt Internet or other legacy networks to communicate by letter between convergence node and the Control Node; This system adopts following level framework:
Control Node is positioned at the superiors, and user or administrative staff can manage and control this sensor network system by this node;
The convergence node, be positioned at the second layer, interface layer as legacy network and sensor network, promptly the new application scenarios code that the user disposes by Control Node is transferred to each sensor node, and the convergence of each sensor node perception, collection is transferred to Control Node by this node layer;
Script sensor node SN is positioned at the 3rd layer, belongs to high-performance sensors, and it is provided with the place is advance planning; Be used to deposit the needed application scenarios code of each RN node in self and the range of management thereof, itself be provided with the application scenarios code and carry out engine, variation that can its environment that is monitored of perception is also carried out new application scenarios code, communicate with the convergence node: application scenarios code of receive downloading and storage, and upload after the sensing data that the RN node sends converged fusion treatment; , communicate during reconstruction applications in environmental change: receive their application scenarios code request message, and pass the application corresponding scripted code down, perhaps directly application corresponding scripted code initiative part is deployed on the RN node to them with the RN node;
Reconstruct sensor node RN is positioned at the bottom, belongs to the low performance transducer, and quantity is maximum in system, density is maximum, and its setting is at random, does not need advance planning; Be provided with the application scenarios code and carry out engine, variation that can its environment that is monitored of real-time perception is also carried out new application scenarios code; If RN node this locality does not need the application scenarios code carried out, with the application scenarios code that initiatively please look for novelty to its SN node of management.
Referring to Fig. 2, introducing the Control Software structure of SN node and RN node among the present invention forms: except the routing module that comprises traditional sensors, data acquisition module, data processing/convergence module, I/O interface module, also have respectively the reconstructed module that is connected with data acquisition module with routing module; This reconstructed module is made up of reconstruct decision-making module, experience accumulation module, four submodules of knowledge base and experience storehouse, wherein:
Knowledge base is used to deposit with the form of logic rules and represents and at the domain knowledge of netinit phase deployment to the node, sensor node uses the environmental data of the current collection of these knowledge analysis, can obtain the contingent change information of environment;
The experience storehouse is used for depositing the experience that this sensor node forms at running, i.e. the probability of happening of the rule of certain environmental data of representing with weights environmental change that may cause, and weights are high more, and the probability that respective change takes place is high more; The experience storehouse is empty during initialization, and along with the operation of sensor node, the experience storehouse constantly obtains and the preservation experience by the experience accumulation submodule: the confidence level weights that each is regular;
The experience accumulation submodule is responsible for the formation experience, after each sensor node is reconstructed decision-making, all will revise experience (promptly revising the confidence level weights of experience in the experience storehouse) in the experience storehouse with the decision-making judged result;
Experience in the knowledge and experience storehouse in the reconstruct decision-making submodule use knowledge base is carried out reasoning to the current environment status data, and whether the variation that the analysis and judgement current environment takes place, decision need triggering to use reconstruct and which kind of application scenarios code of reconstruct.
Referring to Fig. 3, introduce support environment self adaptation of the present invention and use the wireless sensor network system of reconstruct and realize that self adaptation uses five stages and the concrete operations steps flow chart thereof of the method for reconstruct:
(1) network and sensor node are carried out initialization operation, comprise following three content of operation:
(11) network topology structure initialization: during on-premise network, plan the SN node location earlier, at its periphery a plurality of RN nodes are set at random again, and make each node know the information of adjacent node around it by the inundation method, make the SN node jump as bunch head and one or the double bounce scope in the RN node constitute a reconstruct bunch, by the SN node administration and store self and the reconstruct administered bunch in the RN node application scenarios code that may need;
(12) sensor node knowledge base initialization: when disposing SN and RN node,, manually in advance the knowledge in related application field is arranged in the knowledge base of node according to the different demands in sensor application field; Wherein application knowledge is sensor network need be monitored or the various environmental abnormality event column of user's interest are enumerated, extract the environmental data that may cause taking place these anomalous events again, the corresponding relation of this environmental data and anomalous event is exactly a knowledge, adopt rule format to represent it: P → Q, or IF P THEN Q; In the formula, prerequisite P is the environmental data condition, and conclusion Q is the environmental abnormality incident; If P sets up, environment anomalous event Q then takes place.For example: knowledge " when ambient temperature (promptly is higher than 40 degree) unusually, is lower than 2 if find the ratio of ambient humidity and temperature, can judges that so the ring that is monitored has the danger of breaking out of fire " and can be expressed as:
IF (ratio of unusual and humidity of ambient temperature and temperature is lower than 2) THEN (fire alarm)
Wherein the environmental data condition is " ambient temperature unusual and ratio ambient humidity and temperature be lower than 2 ", and conclusion environmental abnormality incident is " danger of breaking out of fire is arranged ".
(13) sensor node operating state initialization: according to the different types of data of sensor node sampling, sample frequency with to the different disposal method of sampled data, select the application corresponding scripted code, be in the application scenarios code of different operating state as sensor node; Simultaneously, adopt finite-state automata to represent the kind of the application scenarios code of the current operation of each operating state of this node, the mutual transforming relationship under the varying environment condition, the initialization state (referring to Fig. 4) of each sensor node is set then.
Fig. 4 has showed a kind of worker state machine of sensor node: the initial work state of node is WS0 (a general work state); When ambient data changes (" environmental condition 1 " take place), variation (is the WS1 state from the WS0 state-transition) has just taken place in the operating state of node; When surrounding environment changes (" environmental condition 2 " take place) once more, the operating state of node then is changed to WS2 by WS1.
(2) sensor node perception environmental change: the environmental data that the sensor node collection is monitored, and utilize the experience that accumulates in the predefined domain knowledge and experience storehouse in the knowledge base that environmental data is analyzed, judge whether environment changes; Concrete steps are as follows:
(21) gather environmental data: sensor node is regularly gathered corresponding environmental data according to the present located operating state;
(22) whether testing environment changes: the knowledge that sensor node calls earlier in the knowledge base is carried out the rules-based analysis reasoning to the current environment data, if can only obtain unique conclusion, promptly next operating state that changes over to according to finite-state automata is unique, and then directly execution in step (3) triggers the operation of using reconstruct; If conclusion is not unique, then utilize the experience in the experience storehouse, next operating state of selecting the most probable generation is as new operating state, simultaneously, judged result is stored in the node experience storehouse as experience, and recomputates each regular confidence level weights, execution in step (3) then.
Concrete grammar based on the analysis ratiocination of knowledge is as follows:
1. utilize finite-state automata to realize knowledge reasoning
The computing capability of considering sensor node is limited, can not use the complicated search algorithm based on condition, so the present invention uses the finite-state automata model to realize rule-based knowledge reasoning process on the node.The initial condition of this automaton is " init state ", a transfer action of every corresponding automaton of knowledge, wherein Gui Ze former piece P produces state by one in the automaton and a jump condition is formed, a state transitions that changes in the pairing operating state automaton of state so knowledge: IF (ratio of unusual and humidity of ambient temperature and temperature is lower than 2) THEN (fire alarm) in the corresponding automaton of the conclusion Q of rule is moved as shown in Figure 5.
Fig. 5 has showed the corresponding relation of knowledge and operating state automaton, shows: the environmental data condition that node is current just can obtain next possible operating state of node as the input of automaton.But, if identical environmental data condition might cause different operating states, when promptly its conclusion is not unique, also to utilize the experience in the experience storehouse, select next operating state that most probable takes place as new operating state.
Referring to Fig. 6, under the temperature normal condition, when temperature is higher than 40 when spending, might be temperature temporarily higher (such as noon in summer some surface temperature just be higher than 40 the degree), it also might be fire alarm (such as the outdoor temperature in winter), the two kinds of different conclusions that have been same environmental data condition prerequisite correspondence, at this moment, only with of the input of the current environmental data condition that collects as the operating state automaton, can't obtain next operating state of unique node, at this time need to utilize experience in the experience storehouse to carry out analysis ratiocination based on experience.
2. based on the reasoning of experience
Because in some cases, same environmental data condition may meet many knowledge, promptly may obtain a plurality of knowledge reasoning conclusions, the experience that just needs the utilization node to obtain in running at this time selects most probable (being confidence level weights maximum) one to be taken place as next operating state in next possible operating state set.Simultaneously, make at every turn one correct judge after, sensor node just is stored in this judged result in the node experience storehouse as experience.Because node resource is limited, the rule of correspondence of The reasoning results is several times only write down recently in the experience storehouse, and calculating: the rule of write down, add up the frequency of utilization of every rule in the current record at least respectively, using the access times of the rule of use and last time in the recent period continuously to these regular confidence level weights, with these results by after setting weights and handling, the increment that obtains is a weighted value, the current confidence level weights sum of this weighted value and every rule is exactly the new confidence level weights of each rule, is used for next analysis ratiocination.
(3) sensor node triggers and uses reconstruct: according to the variation of environment, sensor node judges whether to need to trigger application reconstruct, trigger if desired and use reconstruct, then obtain the type coding of reconstruction applications script and revise the experience storehouse, order is carried out subsequent operation then; Otherwise, return step (2);
(31) reconstruct decision-making: sensor node compares its next operating state and current working state because of the environmental change initiation, judges whether to use reconstruct; If both are inequality, order is carried out subsequent operation; Otherwise, need not use reconstruct, return step (2);
(32) revise the experience storehouse: sensor node obtains corresponding relation between this environmental data and its next operating state according to the conclusion of environmental data and reconstruct decision-making, and concerns confidence level weights regular in the modification experience storehouse according to this;
(33) type coding of acquisition reconstruction applications script: sensor node is according to the table of comparisons of node operating state in the internal memory and node application scenarios type of code, the application scenarios type of code of the application reconstruct that judgement need be carried out.
(4) sensor node obtains the application scenarios code: comprise following operating procedure:
(41) preparatory function: judge the local application scenarios code that whether has had next operating state correspondence earlier, if having, redirect execution in step (5); If there is no, judge again whether the dump energy of this node reaches the setting threshold value, if carry out the operation of obtaining required application scenarios code; Otherwise, directly return step (2);
(42) request down load application scripted code: the RN node sends request down load application script message to SN node and/or the SN node in its reconstruct bunch respectively to other SN node, comprises the type number of the application scenarios code of request in this message;
(43) application scenarios code response: after the SN node is received the request Download Script message of the RN node that it is managed, inquire about its local application scenarios code library, if the application scenarios code of RN node request is arranged, just this application scenarios code is sent to the RN node of request; Otherwise, to this application scenarios code of the SN of other bunches node limited number of time ground inquiry, inquiry times depends on the size and the residue energy of node of network node quantity, reconstruct bunch, if obtain required scripted code, then this scripted code is sent to the RN node (the dotted line first half of Fig. 7 has been showed the interacting message sequential chart of this process) of request; Perhaps SN node analysis RN node upload data after, initiatively the application corresponding scripted code is downloaded to corresponding RN node; And/or
After other SN nodes are received the request Download Script message of this SN node, inquire about its local application scenarios code library,, just this application scenarios code is sent to the SN node of request if the application scenarios code of SN node request is arranged; Otherwise, to this application scenarios code of the SN of other bunches node limited number of time ground inquiry, inquiry times depends on the size and the residue energy of node of network node quantity, reconstruct bunch, if obtain required scripted code, then this scripted code is sent to the RN node (the dotted line Lower Half of Fig. 7 has been showed the interacting message sequential chart of this process) of request.
(5) sensor node is carried out the application scenarios code: sensor node is carried out new application scenarios code, realized the reconfiguring of application task after, return step (2).
Using the detailed implementation of reconstructing method in order to specify environment self-adaption of the present invention, is the concrete steps that embodiment describe environment self adaptation is used reconstructing method with an intelligent building fire monitoring system below.
The operating state transition diagram of the sensor node RN of intelligent building fire monitoring system wireless sensor network (being finite-state automata) as shown in Figure 8, wherein, the operating state of sensor node has three kinds: monitoring temperature state, temperature and humidity monitor state and temperature cigarette sense monitor state.
The knowledge that wherein relates to has:
Knowledge 1:IF (t
Env＜40 ℃ of AND s
Working=monitoring temperature) THEN (s
Working_next=monitoring temperature), in working order in the automaton (referring to shown in Figure 8) corresponding state transitions for 1.;
Knowledge 2:IF (t
Env〉=40 ℃ of AND s
Working=monitoring temperature) THEN (s
Working_next=temperature and humidity monitor), in working order in the automaton (referring to shown in Figure 8) corresponding state transitions for 2.; T in the above-mentioned formula
EnvBe current environmental temperature, s
WorkingBe the work at present state of node, s
Working_nextNext operating state for node.
The step of the application reconstruct of embodiment is as follows:
(1) sensor network nodes initialization: the operating state of each node initializing is monitoring temperature state (as shown in Figure 8), these state lower sensor node collecting temperature data, and sample frequency is 1 time/second.
(2) the RN node is gathered the data of institute's monitoring environment according to the requirement of node work at present state;
(3) the RN node is transferred to the operating state automaton with the temperature data value, when the temperature around the node that collects is lower than 40 ℃, according to knowledge 1 (be among Fig. 8 state transitions 1.), obtain next operating state and still is s
Working_next=monitoring temperature, therefore, this moment, the operating state of node remained unchanged, i.e. execution in step (2);
(4) (be t if temperature is higher than 40 degree
Env〉=40 ℃), then according to the operating state automaton of node as can be known, next operating state of node is s
Working_next=temperature and humidity monitor or s
Working_next=cigarette sense monitoring;
(5) the RN node is rule of thumb judged the state that most probable takes place; for example among this embodiment; it is not that fire is (such as being summer now that the ambient temperature that node occurred in the past is higher than 40 degree situations; noon, local temperature was higher than 40 degree through regular meeting); NextState when therefore this moment, node just can rule of thumb be judged this condition should be temperature and humidity monitor, i.e. s
Working_next=temperature and humidity monitor rather than cigarette sense monitoring (referring to Fig. 9).
(7) the RN node that is in the temperature and humidity monitor state needs monitoring temperature and humidity data simultaneously;
(8) RN judges whether this node has the needed application scenarios code of the humidity data of collection, if having, then directly moves this script, returns step (2); Otherwise execution subsequent operation;
(9) RN judges whether the dump energy of this node reaches specified threshold, if reach, sends application scenarios code request message to its management node SN, if do not reach, returns step (2);
(10) RN receives the humidity control application code of SN response, moves this application scenarios code, returns step (2).
Above step is exactly that a sensor network with environment self-adaption ability is used the embodiment of reconstruct, among this embodiment, sensor node can be according to the variation of surrounding environment, the application scenarios code of its execution is adjusted on dynamic self-adapting ground, to reach accurate, intelligent data acquisition and fire hazard monitoring.
Claims (10)
1, a kind of support environment self adaptation is used the wireless sensor network system of reconstruct, include: a plurality of sensor nodes, convergence node and Control Node, wherein adopt wireless mode to communicate by letter between the sensor node and between sensor node and the convergence node, adopt Internet or other legacy networks to communicate by letter between convergence node and the Control Node; It is characterized in that: described sensor node has two kinds: script sensor node SN and reconstruct sensor node RN, both have dynamic perception environmental change and according to the function of application scenarios code on the environmental change self-adapting reconstruction node; And described system adopts following level framework:
Control Node is positioned at the superiors, sensor network system is managed and controls by this node for user or administrative staff;
The convergence node, be positioned at the second layer, interface layer as legacy network and sensor network, promptly the new application scenarios code that the user disposes by Control Node is transferred to each sensor node, and the convergence of each sensor node perception, collection is transferred to Control Node by this node layer;
Script sensor node SN, be positioned at the 3rd layer, be used to deposit the needed application scenarios code of each RN node in self and the range of management thereof, be provided with the application scenarios code and carry out engine, variation that can its environment that is monitored of perception is also carried out new application scenarios code, communicate with the convergence node: application scenarios code of receive downloading and storage, and upload after the sensing data that the RN node sends converged fusion treatment; , communicate during reconstruction applications in environmental change: receive their application scenarios code request message, and pass the application corresponding scripted code down, perhaps directly application corresponding scripted code initiative part is deployed to the RN node with the RN node;
Reconstruct sensor node RN is positioned at the bottom, is provided with the application scenarios code and carries out engine, and variation that can its environment that is monitored of real-time perception is also carried out new application scenarios code; If RN node this locality does not need the application scenarios code carried out, with the application scenarios code that initiatively please look for novelty to its SN node of management.
2, wireless sensor network system according to claim 1 is characterized in that: described SN is the high-performance sensors node, and its place that is provided with is an advance planning; The RN that quantity is maximum in system, density is maximum is the low performance sensor node, and its setting is at random, does not need advance planning; The Application in Sensing scripted code that described sensor node is carried out includes but not limited to the monitoring program of temperature, humidity, cigarette sense.
3, wireless sensor network system according to claim 1, it is characterized in that: the Control Software of described SN node and RN node also has respectively the reconstructed module that is connected with data acquisition module with routing module except the routing module that comprises traditional sensors, data acquisition module, data processing/convergence module, I/O interface module; This reconstructed module is made up of reconstruct decision-making module, experience accumulation module, four submodules of knowledge base and experience storehouse, wherein:
Knowledge base is used to deposit with rule and represents and at the domain knowledge of netinit phase deployment to the node, according to the environmental data of the current collection of knowledge analysis wherein, obtains the contingent change information of environment for sensor node;
The experience storehouse is used for depositing the experience that this sensor node forms at running, i.e. the probability of happening of the rule of certain environmental data of representing with weights environmental change that may cause, and weights are high more, and the probability that respective change takes place is high more; The experience storehouse is empty during initialization, and along with the operation of sensor node, the experience storehouse constantly obtains and the preservation experience by the experience accumulation submodule: the confidence level weights that each is regular;
The experience accumulation submodule is responsible for the formation experience, after each sensor node is reconstructed decision-making, all will revise the confidence level weights of the experience in the experience storehouse with the decision-making judged result;
Experience in the knowledge and experience storehouse in the reconstruct decision-making submodule use knowledge base is carried out reasoning to the current environment status data, judges the variation that current environment takes place, and whether decision needs to trigger application reconstruct and which kind of application scenarios code of reconstruct.
4, a kind of support environment self adaptation is used the method for work of the wireless sensor network system of reconstruct, it is characterized in that: comprise the steps:
(1) network and sensor node are carried out initialization operation;
(2) sensor node perception environmental change: the environmental data that the sensor node collection is monitored, and utilize the experience that accumulates in the predefined domain knowledge and experience storehouse in the knowledge base that environmental data is analyzed, judge whether environment changes;
(3) sensor node triggers and uses reconstruct: according to the variation of environment, sensor node judges whether to need to trigger application reconstruct, trigger if desired and use reconstruct, then obtain the type coding of reconstruction applications script and revise the experience storehouse, order is carried out subsequent operation then; Otherwise, return step (2);
(4) sensor node obtains the application scenarios code: judge the local application scenarios code that whether has had next operating state correspondence earlier, if having, and redirect execution in step (5); If there is no, judge again whether the dump energy of this node reaches the setting threshold value, if carry out the operation of obtaining required application scenarios code; Otherwise, directly return step (2);
(5) sensor node is carried out the application scenarios code: sensor node is carried out new application scenarios code, realized the reconfiguring of application task after, return step (2).
5, the method for work of wireless sensor network system according to claim 4 is characterized in that: described step (1) further comprises following content of operation:
(11) network topology structure initialization: during on-premise network, plan the SN node location earlier, at its periphery a plurality of RN nodes are set at random again, and make each node know the information of adjacent node around it by the inundation method, make the SN node jump as bunch head and one or the double bounce scope in the RN node constitute a reconstruct bunch, by the SN node administration and store self and the reconstruct administered bunch in the RN node application scenarios code that may need;
(12) sensor node knowledge base initialization: when disposing SN and RN node,, manually in advance the knowledge in related application field is arranged in the knowledge base of node according to the different demands in sensor application field;
(13) sensor node operating state initialization: according to the different types of data of sensor node sampling, sample frequency with to the different disposal method of sampled data, select the application corresponding scripted code, be in the application scenarios code of different operating state as sensor node; Simultaneously, adopt finite-state automata to represent the transforming relationship of each operating state of this node under the varying environment condition, and the initialization state that each sensor node is set.
6, the method for work of wireless sensor network system according to claim 5, it is characterized in that: the application knowledge in the described step (12) is that sensor network need monitor or the various environmental abnormality incidents of user's interest by enumerating, extract the environmental data condition that may cause taking place these anomalous events again, the corresponding relation of this environmental data condition and anomalous event is exactly a knowledge, and adopt rule format to represent it: p → Q, or IF P THEN Q; In the formula, prerequisite P is the environmental data condition, and conclusion Q is the environmental abnormality incident; If P sets up, Q as a result then takes place.
7, the method for work of wireless sensor network system according to claim 4 is characterized in that: described step (2) further comprises following content of operation:
(21) gather environmental data: sensor node is regularly gathered corresponding environmental data according to the present located operating state;
(22) whether testing environment changes: the knowledge that sensor node calls earlier in the knowledge base is carried out rules-based analysis to the current environment data, if can only obtain unique conclusion, promptly next operating state that changes over to according to finite-state automata is unique, and then directly execution in step (3) triggers the operation of using reconstruct; If conclusion is not unique, then utilize the experience in the experience storehouse, next operating state of selecting the most probable generation is as new operating state, simultaneously, judged result is stored in the node experience storehouse as experience, and recomputates each regular confidence level weights, execution in step (3) then.
8, the method for work of wireless sensor network system according to claim 4 is characterized in that: described step (3) further comprises following content of operation:
(31) reconstruct decision-making: sensor node compares its next operating state and current working state because of the environmental change initiation, judges whether to use reconstruct; If both are inequality, order is carried out subsequent operation; Otherwise, need not use reconstruct, return step (2);
(32) revise the experience storehouse: sensor node obtains corresponding relation between this environmental data and its next operating state according to the conclusion of environmental data and reconstruct decision-making, concerns confidence level weights regular in the modification experience storehouse according to this;
(33) type coding of acquisition reconstruction applications script: sensor node is according to the table of comparisons of node operating state in the internal memory and node application scenarios type of code, and judgement need be used the application scenarios type of code of reconstruct.
9, according to the method for work of claim 7 or 8 described wireless sensor network systems, it is characterized in that: the computational methods of described each regular confidence level weights are: the rule of write down, add up the frequency of utilization of every rule in the current record at least respectively, using the access times of the rule of use and last time in the recent period continuously, with these results by after setting weights and handling, the increment that obtains is a weighted value, the current confidence level weights sum of this weighted value and every rule is exactly the new confidence level weights of each rule, is used for next analysis ratiocination.
10, the method for work of wireless sensor network system according to claim 4 is characterized in that: described step (4) further comprises following content of operation:
(41) preparatory function: judge the local application scenarios code that whether has had next operating state correspondence earlier, if having, redirect execution in step (5); If there is no, judge again whether the dump energy of this node reaches the setting threshold value, if order is carried out subsequent operation; Otherwise, directly return step (2);
(42) request down load application scripted code: the RN node sends request down load application script message to SN node and/or the SN node in its reconstruct bunch respectively to other SN node, comprises the type number of the application scenarios code of being asked in this message;
(43) application scenarios code response:
After the SN node is received the request Download Script message of the RN node that it is managed, inquire about its local application scenarios code library,, just this application scenarios code is sent to the RN node of request if the application scenarios code of RN node request is arranged; Otherwise, to this application scenarios code of the SN of other bunches node limited number of time ground inquiry, inquiry times depends on sensor network nodes quantity, reconstruct bunch size and residue energy of node, if obtain required scripted code, then this scripted code is sent to the RN node of request; Perhaps SN node analysis RN node upload data after, initiatively the application corresponding scripted code is downloaded to corresponding RN node; And/or
After other SN nodes are received the request Download Script message of SN node, inquire about its local application scenarios code library,, just this application scenarios code is sent to the SN node of request if the application scenarios code of SN node request is arranged; Otherwise to this application scenarios code of the SN of other bunches node limited number of time ground inquiry, inquiry times depends on the size and the residue energy of node of network node quantity, reconstruct bunch, if obtain required scripted code, then this scripted code is sent to the RN node of request.
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