CN101431442A - Node movement distributed planning method for wireless sensor network - Google Patents
Node movement distributed planning method for wireless sensor network Download PDFInfo
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- CN101431442A CN101431442A CNA2008103049955A CN200810304995A CN101431442A CN 101431442 A CN101431442 A CN 101431442A CN A2008103049955 A CNA2008103049955 A CN A2008103049955A CN 200810304995 A CN200810304995 A CN 200810304995A CN 101431442 A CN101431442 A CN 101431442A
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Abstract
A distribution activity programming method aiming at nodes energy consumption optimization in wireless sensor network wherein the method comprises two major steps: step 1, starting information collection process by any one of the sensor nodes located in the network. Starting node broadcasts to neighbor nodes inside its communication cover area through wireless channel and exchanges information; step 2, all nodes acquires updated cover dominating value of itself and all neighbor nodes when information collection process over. Nodes with higher cover dominating value acquire priority to be active nodes through checking cover dominating value list. Cover dominating value adopted in decision making process is combined by two variables, namely energy level index owned by nodes and numbers of neighbor nodes covered by sense area of the node, and is decided together by experience weight. Synthetic consideration to energy consumption speed and laying density of nodes optimizes nodes activity programming and improves survival time of wireless sensor network.
Description
Technical field
The invention belongs to the wireless sensor network technology field, be specifically related to the distributed activities law of planning of optimizing at node energy consumption in a kind of wireless sensor network.
Background technology
Wireless sensor network is made up of the sensor node of One's name is legion usually.Single sensor node designs at a certain specific data acquisition task usually, for example gathers the special event of environmental aspect data and perception appointment.As a rule, it is little, in light weight that sensor node has a volume, adopts characteristics such as powered battery.Under the situation of no any Activity On the Node planning management, the battery continued power time of a sensor node, or be referred to as life span, will be very of short duration.
Because the single-sensor node only has limited perception and area coverage, so in a typical monitoring system based on wireless sensor network, need numerous sensor node cooperative cooperatings, wider area coverage and more outstanding systematic function are provided.Therefore, in the global design of system, important requirement is when considering energy consumption, by Activity On the Node is planned, and the monitoring area coverage of maximum overall network as far as possible.
Algorithm research at the problems referred to above mainly designs consideration from several aspects at present.When the covering of considering guarded region, mainly adopt the analysis means of area coverage.When the paving mode of considering node was selected, the main employing determined type node laying method, and promptly the position of network belonging sensor node is more fixing relatively.Existing method is also most uses centralized planing method, and forms node by part in the hypothetical network and have stronger calculating, communication and perception, thereby helps network to carry out area dividing and planning.Yet there is more defective in these algorithms in the practical application in the complex environment comparatively.For example the analysis means of area coverage need rely on the third party and participate in observation, and for wireless sensor network self, its distributed characteristic makes individual node be difficult to know the monitoring area coverage information of total system.Determine that type node laying rule is owing to uncertainty of node position and mobility in numerous practical applications lack broad applicability.Simultaneously, centralized law of planning has been run counter to the distributed nature of wireless sensor network, has greatly expended communication, the computational resource of network, and has reduced the survival ability of network.The traditional algorithm spininess has heterogeneous wireless sensor network to node, and has limited range of application.Adopt the homogeney network can reduce hardware cost, system complexity and later maintenance cost significantly.
The present invention is based on the considering of wireless sensor network with following notable feature.The present invention is applicable to the network system with homogeney node, and the wireless communication distance of its single node is greater than the twice of its sensor sensing distance.The position that planning algorithm of the present invention is formed node with network serves as to cover reference point.The present invention is applicable to the wireless sensor network of laid at random, also can directly apply to the network of determining that the type laying method is set up simultaneously.
Summary of the invention
The present invention has taken all factors into consideration the requirement of above-mentioned wireless sensor network node planning, has proposed a kind of brand-new Activity On the Node planing method at the massive wireless sensor that is applied to monitor purpose.The present invention is applicable to the homogeney wireless sensor network, and node paving mode and network size are not had particular restriction.The present invention makes the partial redundance node keep electricity-saving state by planning the cycle of activity to node, guarantees to increase substantially network lifetime under the maximized prerequisite of monitoring area coverage thereby be implemented in.
The present invention carries out the realization of Activity On the Node planing method by following steps:
In the described infonnation collection process, arbitrary neighbor node also simultaneously carries out independently infonnation collection process as new initiation node to the zone that it covered when being waken up and participate in infonnation collection process.
In the described infonnation collection process, arbitrary node calculates the unique parameter that himself is used for programmed decision-making according to its collected information of neighbor nodes, is referred to as to cover the advantage value among the present invention.
Described parameter urgently covers the advantage value and comprises two decisive factors: the neighbor node quantity that remaining energy grade index that node had and node induction region can cover.Described covering advantage value is calculated by the linearity or the nonlinear combination of described two decisive factors.The present invention does not relate to the selection of concrete compound mode, only provides example illustrated in execution mode.
Step 2 is referred to as decision process.Decision process of the present invention finishes the back in infonnation collection process to be carried out, and adopts covering dominating integral method to make a strategic decision.Arbitrary node and its neighbor node after infonnation collection process finishes, should accurately know himself cover the advantage value with and the covering advantage value of all neighbor nodes.When arbitrary node was inspected its information of neighbor nodes of knowing, if himself cover the advantage value greater than all covering advantage values that neighbor node had that is positioned at its induction range, this node was selected to live-vertex; Otherwise when the neighbor node that is positioned at its induction range arbitrarily had higher covering advantage value, this node was selected to the inertia node.
Described live-vertex is in running order node.Live-vertex is carried out the induction monitoring task by the transducer that carries to the institute overlay area, and serves as necessary network data transmission task as the composition node of multihop network.
Described inertia node promptly is in the node of electricity-saving state.The inertia node does not participate in network data transmission and induction monitoring activity.The inertia node is monitored wireless channel according to the setting regularity of its onboard clock, participates in next round activity planning after receiving wake-up signal.
The every complete execution of the above step once promptly is referred to as an execution cycle.Primary distribution is carried out in the activity of node planning again under the overall network in each execution cycle, obtains new distributions.The planing method execution cycle of the present invention has adjustability, according to network and use and actually rationally adjust.
Compare with prior art, the present invention has following innovation part:
The present invention has adopted the sensor sensing model of circular indifference induction region as node, and the laying method and the network size of node are not had particular restriction, and is applicable to the wireless sensor network of determining that type and stochastic pattern are laid simultaneously.The present invention has adopted the distributed decision making method, has improved the robustness of total system.The present invention proposes node distributed decision making mechanism and has adopted brand-new covering dominating integral method, and relatively conventional method has enlarged the scope that individual node in the algorithm obtains neighbor information, with the node program results of more being optimized.Periodic network upgrades and makes the overall network energy consumption be able to more balanced distribution, thereby makes that the network survivability phase is prolonged.
Description of drawings
Fig. 1 is that sensor node of the present invention distributes and illustraton of model.
Fig. 2 is a nodal information collection process schematic diagram of the present invention.
Fig. 3 is infonnation collection process step signal of the present invention.
Fig. 4 is decision process step signal of the present invention.
Embodiment
Below in conjunction with the drawings and specific embodiments the present invention is done more detailed description.
Shown the node random distribution situation of a unconfined large-scale wireless sensor network of scale in a little localized area among Fig. 1, wherein the solid dot of black has been represented sensor node.With this zone internal labeling is N
1Node be example, its distance of reaction is labeled as R
s, the induction region that is covered is represented with the circle of dashed lines labeled.N
1The communication distance R of node
cDouble R as shown in the figure
s, i.e. R
c2 * R
s, represent with the circle of solid marks.Another vertex ticks is N in this zone
2It is in N
1Air line distance D between the node
Less than N
1Communication distance R
cSo, N
1Node and N
2Node has direct wireless communication link.
As shown in Figure 2, in the infonnation collection process of node planing method step 1 of the present invention, be labeled as N
1Node initiate this and take turns infonnation collection process, and to all neighbor node broadcast messages exchange requests that are positioned at its communication coverage area shown in the solid line circle.After receiving information exchange requests, N
1One of neighbor node promptly be labeled as N
2Node begin N immediately
2All node broadcasts belong to N in the dashed circle communication zone that is covered
2Information exchange requests.In like manner, this process progressively extends to whole network.
Shown among Fig. 3 that in infonnation collection process of the present invention, individual node is carried out the detailed step of this process.Judge from as after initiating node that when certain node promptly begin its neighbor node is carried out periodic broadcast, information exchange is carried out in request.This process should continue till its all neighbor nodes all participate in this infonnation collection process.After finishing the renewal that self covers the advantage value when this initiation node, the covering advantage value of its renewal should be distributed to its all neighbor nodes.
Each node calculates the covering advantage value of himself according to its collected neighbor information, is labeled as M
iAs previously mentioned, cover the neighbor node quantity that remaining energy grade index that the advantage value depends on that this node has and node induction region are covered.Present embodiment provides the linear combination computing formula of two kinds of concrete covering advantage values, but protection scope of the present invention is not limited to described two kinds of computational methods.
1, by setting up the model based on empirical value, the covering advantage value of a node can directly be calculated by its remaining energy grade index P and the neighbor node quantity N that is positioned at its induction overlay area, and formula is as follows:
M
i＝α·P+β·N
In the described formula, α and β can adjust according to concrete applied environment and application conditions as empirical parameter.
2, the computation model of another kind of complexity is based on the calculating of 1 pair of initial covering advantage value of above-mentioned method, and it finally is used for the final covering advantage value of comparison
Calculate by following formula
In the described formula, ∑ M
jFor all are positioned at the covering advantage value sum of the neighbor node of its induction overlay area.
As shown in Figure 4, in the decision process of node planing method step 2 of the present invention, each node all has the covering advantage value list that comprises himself and neighbor node after infonnation collection process finishes.Described decision process requires it that collected covering advantage value list is inspected.As find have arbitrary neighbor node to have higher covering advantage value in its induction overlay area, this node promptly enters electricity-saving state, is labeled as the inertia node.Otherwise this node then enters operating state immediately, becomes live-vertex.
Beginning until infonnation collection process next time with finishing of step 1 of the present invention and step 2 is a complete execution cycle.The wireless sensor network scale that the length of this execution cycle can be laid according to application-specific, the concrete model of node and the decision of other correlative factors.Protection scope of the present invention is not limited to the selection of concrete Cycle Length.
The present invention has broken through the restriction to sensor network nodes paving mode and network size on the distributed decision making mechanism of Activity On the Node planning, be applicable to that wireless sensor network is used widely.Because adopt distributed decision making, the present invention has improved the robustness of total system.The brand-new covering dominating integral method that the present invention proposes, enlarged the scope that individual node in the algorithm obtains neighbor information, and the energy consumption speed of node and the overall balance mechanism of node laying density have been considered simultaneously, the node program results of more being optimized, thereby the life cycle of having improved wireless sensor network.
Claims (8)
- The distributed activities law of planning of optimizing at node energy consumption in [claim 1] a kind of wireless sensor network, its feature may further comprise the steps:Step 1: initiate infonnation collection process by any sensor node that is arranged in this network.Initiate node and the neighbor node in its communication coverage is carried out continuation broadcasting, and carry out information exchange, finish the renewal that it covers the advantage value parameter by wireless channel.Step 2: all nodes obtain covering advantage value of upgrading and the covering advantage value list of setting up its all neighbor nodes after infonnation collection process finishes.To arbitrary node, must inspect its neighbor node and cover the advantage value list, and with self cover the advantage value and compare.Node with higher covering advantage value obtains to become the priority of live-vertex.
- The distributed activities law of planning of optimizing at node energy consumption in [claim 2] wireless sensor network according to claim 1, its feature comprises that described wireless sensor network belongs to the homogeney random network, is specially:All nodes that are subordinated to described wireless sensor network possess close physical characteristic, comprise operational capability, radio communication, and sensing capability, and energy consumption characteristics etc.Described wireless sensor network can adopt stochastic pattern node laying method, but this invention is equally applicable to adopt the wireless sensor network of determining type node laying method.
- The distributed activities law of planning of optimizing at node energy consumption in [claim 3] wireless sensor network according to claim 1, its feature comprises, all are subordinated to 2 times of the communication coverage distances of node of described wireless sensor network to its actual induction distance.
- The distributed activities law of planning of optimizing at node energy consumption in [claim 4] wireless sensor network according to claim 1, its feature comprise, are initiated by any sensor node that is arranged in this network in the described infonnation collection process; Its neighbor node also carries out independently infonnation collection process as new initiation node to the communication zone that this neighbor node covered, and makes infonnation collection process progressively extend to whole network participating in its infonnation collection process simultaneously.
- The distributed activities law of planning of optimizing at node energy consumption in [claim 5] wireless sensor network according to claim 1, its feature comprises, the arbitrary node of described wireless sensor network independently carries out the activity programmed decision-making according to the covering advantage parameter value of its collected self and its neighbor node.
- The distributed activities law of planning of optimizing at node energy consumption in [claim 6] wireless sensor network according to claim 5, its feature comprises, the combination of two variablees of neighbor node quantity that described covering advantage parameter is covered by remaining energy grade index that this node had and this node induction region, and the experience weights determine jointly.
- The distributed activities law of planning of optimizing at node energy consumption in [claim 7] wireless sensor network according to claim 5, its feature comprises, in decision process, the covering advantage parameter of the arbitrary node of described wireless sensor network is known it self and neighbor node is inspected.Concrete decision-making technique is:If this node self covers the advantage value greater than all covering advantage values that neighbor node had that is positioned at its induction range, then this node is selected to live-vertex; Otherwise when the neighbor node that is positioned at its induction range arbitrarily had higher covering advantage value, then this node was selected to the inertia node.
- The distributed activities law of planning of optimizing at node energy consumption in [claim 8] wireless sensor network according to claim 1, its feature comprises, described planing method can periodically be carried out, the length in cycle can be according to the scale of wireless sensor network, the concrete model of affiliated node and the decision of other correlative factors.
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| CN102547759A (en) * | 2011-12-23 | 2012-07-04 | 无锡虹业自动化工程有限公司 | Self-organization covering method of wireless sensor network based on biological competition |
| CN101860981B (en) * | 2010-02-05 | 2012-07-04 | 深圳先进技术研究院 | Routing method and system of wireless sensor network |
| CN102821122A (en) * | 2011-06-09 | 2012-12-12 | 财团法人工业技术研究院 | Method and apparatus for node distribution and computer program product |
| WO2013000148A1 (en) * | 2011-06-30 | 2013-01-03 | Renesas Mobile Corporation | Method and apparatus for improved wireless sensor network interactions |
| CN103813377A (en) * | 2014-01-20 | 2014-05-21 | 北京科技大学 | Method for obtaining total cover area of multiple circular regions |
| CN104270414A (en) * | 2014-09-12 | 2015-01-07 | 苏州合欣美电子科技有限公司 | Electronic product production line dust monitoring point optimization method |
| CN104540194A (en) * | 2014-12-16 | 2015-04-22 | 余凤莲 | Energy saving method for distributed type zigbee network nodes |
| CN105959341A (en) * | 2016-04-12 | 2016-09-21 | 时建华 | Method for improving existing fire fighting system |
| CN109068401A (en) * | 2018-09-19 | 2018-12-21 | 东莞方凡智能科技有限公司 | Foreign-going ship intelligent monitor system |
| CN109120456A (en) * | 2018-09-06 | 2019-01-01 | 江苏佳源科技有限公司 | Controller switching equipment state intelligent monitoring system |
| CN117075802A (en) * | 2023-08-04 | 2023-11-17 | 上海虹港数据信息有限公司 | Distributed storage method based on artificial intelligence power |
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| Publication number | Priority date | Publication date | Assignee | Title |
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| CN101860981B (en) * | 2010-02-05 | 2012-07-04 | 深圳先进技术研究院 | Routing method and system of wireless sensor network |
| CN102821122A (en) * | 2011-06-09 | 2012-12-12 | 财团法人工业技术研究院 | Method and apparatus for node distribution and computer program product |
| WO2013000148A1 (en) * | 2011-06-30 | 2013-01-03 | Renesas Mobile Corporation | Method and apparatus for improved wireless sensor network interactions |
| CN102547759A (en) * | 2011-12-23 | 2012-07-04 | 无锡虹业自动化工程有限公司 | Self-organization covering method of wireless sensor network based on biological competition |
| CN103813377B (en) * | 2014-01-20 | 2017-05-17 | 北京科技大学 | Method for obtaining total cover area of multiple circular regions |
| CN103813377A (en) * | 2014-01-20 | 2014-05-21 | 北京科技大学 | Method for obtaining total cover area of multiple circular regions |
| CN104270414B (en) * | 2014-09-12 | 2018-01-02 | 徐岩军 | A kind of electronic product assembly line dust monitoring point optimization method |
| CN104270414A (en) * | 2014-09-12 | 2015-01-07 | 苏州合欣美电子科技有限公司 | Electronic product production line dust monitoring point optimization method |
| CN104540194A (en) * | 2014-12-16 | 2015-04-22 | 余凤莲 | Energy saving method for distributed type zigbee network nodes |
| CN105959341A (en) * | 2016-04-12 | 2016-09-21 | 时建华 | Method for improving existing fire fighting system |
| CN109120456A (en) * | 2018-09-06 | 2019-01-01 | 江苏佳源科技有限公司 | Controller switching equipment state intelligent monitoring system |
| CN109120456B (en) * | 2018-09-06 | 2019-06-14 | 江苏佳源科技有限公司 | Controller switching equipment state intelligent monitoring system |
| CN109068401A (en) * | 2018-09-19 | 2018-12-21 | 东莞方凡智能科技有限公司 | Foreign-going ship intelligent monitor system |
| CN117075802A (en) * | 2023-08-04 | 2023-11-17 | 上海虹港数据信息有限公司 | Distributed storage method based on artificial intelligence power |
| CN117075802B (en) * | 2023-08-04 | 2024-05-10 | 上海虹港数据信息有限公司 | Distributed storage method based on artificial intelligence power |
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Open date: 20090513 |