CN108401233A - One kind dividing matched compound event cognitive method based on most authority two - Google Patents
One kind dividing matched compound event cognitive method based on most authority two Download PDFInfo
- Publication number
- CN108401233A CN108401233A CN201810047838.4A CN201810047838A CN108401233A CN 108401233 A CN108401233 A CN 108401233A CN 201810047838 A CN201810047838 A CN 201810047838A CN 108401233 A CN108401233 A CN 108401233A
- Authority
- CN
- China
- Prior art keywords
- compound event
- sensing node
- authority
- event
- compound
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Granted
Links
Classifications
-
- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04W—WIRELESS COMMUNICATION NETWORKS
- H04W4/00—Services specially adapted for wireless communication networks; Facilities therefor
- H04W4/30—Services specially adapted for particular environments, situations or purposes
- H04W4/38—Services specially adapted for particular environments, situations or purposes for collecting sensor information
-
- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04W—WIRELESS COMMUNICATION NETWORKS
- H04W52/00—Power management, e.g. TPC [Transmission Power Control], power saving or power classes
- H04W52/02—Power saving arrangements
- H04W52/0209—Power saving arrangements in terminal devices
-
- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
- Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
- Y02D—CLIMATE CHANGE MITIGATION TECHNOLOGIES IN INFORMATION AND COMMUNICATION TECHNOLOGIES [ICT], I.E. INFORMATION AND COMMUNICATION TECHNOLOGIES AIMING AT THE REDUCTION OF THEIR OWN ENERGY USE
- Y02D30/00—Reducing energy consumption in communication networks
- Y02D30/70—Reducing energy consumption in communication networks in wireless communication networks
Landscapes
- Engineering & Computer Science (AREA)
- Computer Networks & Wireless Communication (AREA)
- Signal Processing (AREA)
- Information Retrieval, Db Structures And Fs Structures Therefor (AREA)
Abstract
The invention discloses one kind based on most authority two to divide matched compound event cognitive method, wherein this method includes：1) perception data of several sensing nodes being deployed in monitoring region in its sensing range is collected；2) according to perception data, sensing node is matched for the compound event in monitoring region；3) compound event and the matching problem of sensing node are subjected to bipartite graph modeling, and are that compound event matches optimal sensing node by most authority bipartite graph matching algorithm.By means of the invention it is possible to which rational management heterogeneous nodes carry out collaborative perception to different compound events so that perception efficiency maximizes, and then saves resource consumption, and effectively extend sensing node uses duration.
Description
Technical field
The present invention relates to Internet of Things field, more particularly to one kind dividing matched compound event perception side based on most authority two
Method.
Background technology
Accurate comprehensive observation to physical world is that Internet of Things (IOT), the basic of information physical emerging system (CPS) are appointed
Business.By be deployed in monitoring region in all kinds of sensing nodes come omnibearing observation, accurately to obtain physical world information, information
Physics emerging system (CPS) generally comprises the wireless sensor network of several isomeries, these heterogeneous networks include different type
Sensor node, and have different perception, calculating and communication capacity.How to make what the sensor node of isomery cooperateed with to go
The complex process for monitoring physical world is a particularly significant and urgent problem to be solved.
Invention content
The present invention provides one kind and dividing matched compound event cognitive method based on most authority two, being capable of rational management isomery
Node carries out collaborative perception to different compound events so that perception efficiency maximizes, and then saves resource consumption.
According to an aspect of the invention, there is provided one kind dividing matched compound event cognitive method based on most authority two,
Include the following steps：1) perception data of several sensing nodes being deployed in monitoring region in its sensing range is collected；
2) according to perception data, sensing node is matched for the compound event in monitoring region；3) by of compound event and sensing node
Bipartite graph modeling is carried out with problem, and is that compound event matches optimal sensing node by most authority bipartite graph matching algorithm.
Preferably, above-mentioned steps 3) bipartite graph modeling method be：Bipartite graph modeling is expressed as G=(V, S, E),
Middle V indicates that the set of the compound event in monitoring region, S indicate the set of multi-modal sensing node, and monitoring has m in region
Compound event, k class sensing nodes are different from per the quantity of one kind sensing node, share n sensing node, and E indicates compound
Between event and sensing node can matched link set and the side e=(v, s) in bipartite graph, e ∈ E, v ∈ V, s ∈
S, each edge have weights, and the weights on side are matching degree.
Preferably, above-mentioned steps 3) in by most authority bipartite graph matching algorithm be compound event match optimal perception
Node includes the following steps：Most authority augmenting path is found using greedy strategy in bipartite model, is expanded matched
The quantity on side；The maximum weight matching figure of compound event and sensing node is established according to most authority augmenting path；From maximum weight matching
It is obtained in figure and the matched optimal sensing node of compound event.
Preferably, most authority augmenting path is found using greedy strategy in bipartite model, expands matched side
Quantity includes the following steps：Breadth-first search BFS is carried out one by one to the unmatched point in bipartite model, finds weights most
Big matches side；Most authority augmenting path is generated according to the form of alternating path.
Preferably, after step 3), this method is further comprising the steps of：According to the matched optimal sense of compound event
The perception data for knowing node, judges whether compound event has met occurrence condition；If compound event has met occurrence condition,
The indicator light then controlled in monitoring region is glittering.
Preferably, after step 1), the composition rule of synthesis compound event input by user is obtained；Wherein, synthesis rule
It include then the atomic event of synthesis compound event；Compound event is synthesized according to composition rule.
Compared with prior art, beneficial effects of the present invention are as follows：
Through the invention, divide matching algorithm to be that compound event matches rational sensing node using most authority two, keep its right
Compound event carries out collaborative perception so that perception efficiency maximizes, and saves resource consumption, effectively extends the use of sensing node
Duration, while collaborative perception is carried out to compound event, also perceived effect is optimized, improve the detection to compound event
Precision.
Description of the drawings
Attached drawing described herein is used to provide further understanding of the present invention, and is constituted part of this application, this hair
Bright illustrative embodiments and their description are not constituted improper limitations of the present invention for explaining the present invention.In attached drawing：
Fig. 1 is a kind of stream dividing matched compound event cognitive method based on most authority two according to the ... of the embodiment of the present invention
Cheng Tu；
Fig. 2 is the bipartite graph of compound event and sensing node；
Fig. 3 is a kind of flow chart dividing matched compound event cognitive method based on most authority two according to embodiment one；
Fig. 4 is coverage diagram of the perception radius to compound event of sensing node；
Fig. 5 is collaborative perception figure of the multi-modal sensing node to compound event.
Specific implementation mode
Below in conjunction with attached drawing of the present invention, technical solution of the present invention is described, but described embodiment is only
A part of the embodiment of the present invention, based on the embodiments of the present invention, those of ordinary skill in the art are not making creative labor
The every other embodiment obtained under the premise of dynamic, shall fall within the protection scope of the present invention.
An embodiment of the present invention provides one kind to divide matched compound event cognitive method, Fig. 1 to be bases based on most authority two
A kind of flow chart dividing matched compound event cognitive method based on most authority two of the embodiment of the present invention, as shown in Figure 1, packet
Include following steps：
Step S101：Collect perception number of several sensing nodes being deployed in monitoring region in its sensing range
According to；
Step S102：According to perception data, sensing node is matched for the compound event in monitoring region；
Step S103：Compound event and the matching problem of sensing node are subjected to bipartite graph modeling, and pass through most authority two
Component matching algorithm is that compound event matches optimal sensing node.
In implementation process, after step slol, the synthesis rule of synthesis compound event input by user can be obtained
Then；Wherein, composition rule includes the atomic event for synthesizing compound event；Compound thing is further synthesized according to composition rule
Part.
In step s 103, the method for bipartite graph modeling is：Bipartite graph modeling is expressed as G=(V, S, E), and wherein V is indicated
The set of the compound event in region is monitored, S indicates the set of multi-modal sensing node, and monitoring there are m compound things in region
Part, k class sensing nodes, per one kind sensing node quantity be different from, share n sensing node, E indicate compound event and
Between sensing node can matched link set and the side e=(v, s) in bipartite graph, e ∈ E, v ∈ V, s ∈ S, every
There are weights on side, and the weights on side are matching degree.
In step s 103, it is that compound event matches optimal sensing node by most authority bipartite graph matching algorithm, wraps
Include following steps：Most authority augmenting path is found using greedy strategy in bipartite model, expands the number on matched side
Amount；The maximum weight matching figure of compound event and sensing node is established according to most authority augmenting path；From maximum weight matching figure
To with the matched optimal sensing node of compound event.
Further, most authority augmenting path is found using greedy strategy in bipartite model, expands matched side
Quantity, include the following steps：Breadth-first search BFS is carried out one by one to the unmatched point in bipartite model, finds weights
It is maximum to match side；Most authority augmenting path is generated according to the form of alternating path.
After step s 103, can sentence further according to the perception data of the matched optimal sensing node of compound event
Whether disconnected compound event has met occurrence condition；If compound event has met occurrence condition, the finger in monitoring area is controlled
Show that lamp is glittering.
Through the above steps, divide matching algorithm to be that compound event matches rational sensing node using most authority two, make it
Collaborative perception is carried out to compound event so that perception efficiency maximizes, and saves resource consumption, effectively extends making for sensing node
With duration, while collaborative perception is carried out to compound event, also perceived effect is optimized, improves the inspection to compound event
Survey precision.
In order to keep technical scheme of the present invention and implementation method clearer, below in conjunction with preferred embodiment to it
Realization process is described in detail.
Embodiment one
Dividing matched compound event cognitive method based on most authority two the present embodiment provides a kind of, that is, by compound thing
The matching problem of part and sensing node is converted into most two points of matching problems of authority, divides matching algorithm to be compound by most authority two
The rational sensing node of event matches so that perception efficiency maximizes.
Fig. 3 is that according to embodiments of the present invention one a kind of dividing matched compound event cognitive method based on most authority two
Process for using figure, includes the following steps：
Step S301：Master controller collects several sensing nodes being deployed in monitoring region in its sensing range
Interior perception data；
In the embodiment of the present invention, as shown in figure 4, having been deployed in advance in monitoring region a variety of different types of multi-modal
The quantity of sensing node, different types of sensing node differs, the sensing range of different types of sensing node also not phase
Together, several sensing nodes that each type includes are uniformly distributed in monitoring region, and monitoring region memory is compound at several
Event, each compound event are combined by several atom things, and the composition rule of compound event is needed according to application
Structure is sought, main includes that the required condition met is synthesized between meeting given atomic event, monitors in region and also sets up center
Controller, master controller with monitoring region in sensing node communicate to connect, master controller also with monitoring region in answering
Event communication connection is closed, the sensing node in monitoring region is allowed to feel existing compound event in its sensing range first
Know, then the data of perception are sent to master controller, so that master controller carries out analyzing processing to perception data, it is multiple
The generation that the suitable sensing node of event matches goes detection compound event is closed, the precision of detection compound event is further increased；
Optionally, when user needs to judge whether some compound event in monitoring area can occur, so that it may to incite somebody to action
Synthesize the type input center of each atomic event of the compound event and the necessary sensing node of each atomic event of perception
Controller, master controller is after the atomic event for receiving synthesis compound event input by user, by each atomic event
It is combined into a compound event, the type further according to the sensing node for perceiving the atomic event that compound event includes is multiple
Close event matches necessity sensing node；
Step S302：Master controller matches sensing node according to perception data, for the compound event in monitoring region；
Optionally, master controller classifies the perception data of different composite event after receiving perception data
Storage calculates the matching degree of the sensing node and the compound event that can perceive compound event, if same type of sense
Know that node there are multiple sensing nodes while perceiving the compound event, then the sensing node for selecting matching degree high and the compound event
It is matched, various types of sensing nodes carry out collaboration matching so that the perception efficiency of compound event gets a promotion；
Optionally, master controller can give the different cost constraint of different types of sensing node and overall cost
C is constrained, wherein the cost constraint for multiple sensing nodes that same sensing node includes also differs, calculates best collaboration
Cognitive method so that under conditions of constraining C no more than overall cost, system can obtain maximum perception efficiency, maximum sense
Know that the computational methods of efficiency are：I=1,2, L, k, ni∈ { 0,1,2, L },
In：
Optionally, since multiple sensing nodes of perception compound event are different to the perceived quality of the compound event, so
With regard to needing the cooperative awareness model in advance according to compound event to optimize configuration to each sensing node and compound event,
So that whole compound event perception efficiency maximizes；The perceived quality of compound event isAnd
Si={ j1,j2,...,jl, the perceived quality of compound event is determined by the perceived quality for synthesizing the atomic event of compound event,
δjiIndicate the perceived quality or confidence level of corresponding atomic event, the composition rule according to synthesis compound event calculates compound thing
The perceived quality of part；
Lack at least one necessary sensing node when for example, matching collaborative perception node for some compound event
When can not form collaborative perception, just abandon matching collaborative perception node to some compound event, and be a certain with this
A matched sensing node of compound event selects other suitable compound events to be matched；As shown in figure 5, compound event E2
Lack ScSensing node covers, therefore it can not form collaborative perception, and it can be considered to abandon to SaAnd SbSensing node
Matching.In this wayIt can remove matching E1,Remove matching E3, so that whole compound event perception efficiency maximizes；
Further alternative, master controller can be arranged according to the distribution situation of the sensing node around compound event
Compound event is to the attraction of necessary sensing node, specifically, can be the reward that Ω is arranged in compound event E, compound event root
Sensing range according to different sensing nodes around it is different, and different rewards is arranged for different sensing nodes, if perception section
The distance between point and compound event farther out, then configure larger reward for the sensing node, so that compound event itself
It perceives efficiency to maximize, at least one necessary sensing node is lacked when matching collaborative perception node if it is compound event can not
When forming collaborative perception, the reward of the compound event is just set as 0, so that the perception efficiency of whole compound event is maximum
Change；
Step S303：Compound event and the matching problem of sensing node are carried out bipartite graph modeling by master controller；
In the embodiment of the present invention, master controller converts the matching problem of compound event and sensing node to bipartite graph
Matching problem further divides matching algorithm to be that compound event matches most suitable sensing node by most authority two；
Optionally, above-mentioned most authority two divides the implementation procedure of matching algorithm to be：
If bipartite model is G=(X, Y), cum rights bipartite graph generates two fraction matrix W (xi,yj), it enables
Two points of matching set M (S, T)；By X, each element desired value is initialized during Y gathers, the desired value of each element in enabling X gather
Q(xi)=max (wi), each element desired value Q (y in enabling Y gatherj)=0；
To from x0→xmIn each node execute：Most authority augmenting path expansion algorithm based on greedy strategy searches augmentation
Path xiyj；xiyjMeet wij=max [wi], whereinUse xiyjAugmentation M；If failing to find augmenting path, X, Y collection are changed
Each element desired value in conjunction；Calculate Δ=min { Q (xi)+Q(yj)-wij}；To xi∈ S have： Q(xi)=Q (xi)-Δ；To yj∈T
Have：Q(yj)=Q (yj)-Δ；If there is no M- to expose vertex in X；Obtain maximum weight matching M.
Optionally, the method for bipartite graph modeling is：Bipartite graph modeling is expressed as G=(V, S, E), and wherein V indicates monitoring section
The set of compound event in domain, S indicate the set of multi-modal sensing node, and monitoring in region has m compound event, k class senses
Know node, be different from per the quantity of one kind sensing node, share n sensing node, E indicates compound event and sensing node
Between can matched link set and the side e=(v, s) in bipartite graph, e ∈ E, v ∈ V, s ∈ S, each edge all have the right
Value, the weights on side are matching degree；
Step S304：Master controller finds most authority augmenting path in bipartite model using greedy strategy, expands
The quantity on matched side；
Optionally, master controller finds the specific of most authority augmenting path in bipartite model using greedy strategy
Embodiment is：Breadth-first search BFS is carried out one by one to the unmatched point in bipartite model, that finds maximum weight can
Match side；Most authority augmenting path is generated according to the form of alternating path；
Specifically, above-mentioned alternating path refers to from a unmatched point, successively by non-matching in, matching, it is non-matching
The path of side ... formation, above-mentioned augmenting path refer to from a unmatched point, walk alternating path, if approach another do not match
Point (point that sets out not counting), then this alternating path be known as augmenting path, in augmenting path it is non-matching while than matching more than one；
Optionally, master controller runs breadth-first search from a unmatched point by Hungary Algorithm and calculates
Method (BFS) walks alternating path and carries out augmentation, until cannot extend again, while needing to tie when being extended by augmenting path
It closes Greedy idea all maximum weights of search in search augmenting path every time and matches side, can just search out most authority augmentation in this way
Path；
Step S305：Master controller establishes compound event and the most authority of sensing node according to most authority augmenting path
Matching figure；
Step S306：Master controller obtains and the matched optimal sensing node of compound event from maximum weight matching figure；
Step S307：Master controller judges multiple according to the perception data of the matched optimal sensing node of compound event
Whether conjunction event has met occurrence condition；If so, thening follow the steps S308；If not, terminating this flow；
Step S308：Indicator light in master controller control monitoring region is glittering.
In the embodiment of the present invention, if compound event has met occurrence condition, master controller can control prison
The indicator light surveyed in region is glittering, prompts user's compound event can to occur with this.
As it can be seen that it can be that compound event matching is most closed by most authority bipartite graph matching algorithm to implement the embodiment of the present invention
Suitable sensing node so that the utilization rate of sensing node is improved, and has been saved resource, has effectively been extended making for sensing node
With duration, while different types of sensing node carries out collaborative perception to compound event and perception efficiency can be made to maximize, and improves
Detect the precision of compound event.
Claims (6)
1. one kind dividing matched compound event cognitive method based on most authority two, which is characterized in that include the following steps：
1) perception data of several sensing nodes being deployed in monitoring region in its sensing range is collected；
2) according to the perception data, sensing node is matched for the compound event in monitoring region；
3) compound event and the matching problem of the sensing node are subjected to bipartite graph modeling, and pass through most authority bipartite graph
Matching algorithm is that the compound event matches optimal sensing node.
2. according to the method described in claim 1, it is characterized in that, the method for the bipartite graph modeling of the step 3) is：
Bipartite graph modeling is expressed as G=(V, S, E), and wherein V indicates that the set of the compound event in monitoring region, S indicate multimode
The set of state sensing node, monitoring has m compound event in region, k class sensing nodes, and the quantity per one kind sensing node is not
It is identical, share n sensing node, E expression compound event and sensing node between can matched link set and bipartite graph
In side e=(v, s), e ∈ E, v ∈ V, s ∈ S, each edge has weights, and the weights on side are matching degree.
3. according to the method described in claim 2, it is characterized in that, passing through most authority bipartite graph matching algorithm in the step 3)
Optimal sensing node is matched for the compound event, is included the following steps：
Most authority augmenting path is found using greedy strategy in bipartite model, expands the quantity on matched side；
The maximum weight matching figure of the compound event and the sensing node is established according to the most authority augmenting path；
It is obtained from the maximum weight matching figure and the matched optimal sensing node of the compound event.
4. according to the method described in claim 3, it is characterized in that, described found most in bipartite model using greedy strategy
Authority augmenting path expands the quantity on matched side, includes the following steps：
Breadth-first search BFS is carried out one by one to the unmatched point in bipartite model, that finds maximum weight matches side；
Most authority augmenting path is generated according to the form of alternating path.
5. further comprising the steps of according to the method described in claim 1, it is characterized in that, after the step 3)：
According to the perception data of the matched optimal sensing node of the compound event, judge whether the compound event has met
Occurrence condition；
If the compound event has met occurrence condition, the indicator light controlled in monitoring region is glittering.
6. further comprising the steps of according to the method described in claim 5, it is characterized in that, after the step 1)：
Obtain the composition rule of synthesis compound event input by user；Wherein, the composition rule includes synthesizing the compound thing
The atomic event of part；
The compound event is synthesized according to the composition rule.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201810047838.4A CN108401233B (en) | 2018-01-18 | 2018-01-18 | Composite event perception method based on maximum weight binary matching |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201810047838.4A CN108401233B (en) | 2018-01-18 | 2018-01-18 | Composite event perception method based on maximum weight binary matching |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN108401233A true CN108401233A (en) | 2018-08-14 |
| CN108401233B CN108401233B (en) | 2020-12-29 |
Family
ID=63094667
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201810047838.4A Active CN108401233B (en) | 2018-01-18 | 2018-01-18 | Composite event perception method based on maximum weight binary matching |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN108401233B (en) |
Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN110866687A (en) * | 2019-11-07 | 2020-03-06 | 中盈优创资讯科技有限公司 | Task allocation method and device |
| CN112953759A (en) * | 2021-01-27 | 2021-06-11 | 上海七牛信息技术有限公司 | Node optimal resource coverage analysis and adjustment method and device and computer equipment |
Citations (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN103517437A (en) * | 2013-10-21 | 2014-01-15 | 中国科学技术大学 | Method and system for distributing a plurality of relays and power of relays in cellular network |
| US20160125289A1 (en) * | 2014-10-30 | 2016-05-05 | International Business Machines Corporation | Mapping graphs onto core-based neuromorphic architectures |
| CN107483587A (en) * | 2017-08-21 | 2017-12-15 | 清华大学 | A kind of power telecom network cache optimization method of content oriented |
-
2018
- 2018-01-18 CN CN201810047838.4A patent/CN108401233B/en active Active
Patent Citations (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN103517437A (en) * | 2013-10-21 | 2014-01-15 | 中国科学技术大学 | Method and system for distributing a plurality of relays and power of relays in cellular network |
| US20160125289A1 (en) * | 2014-10-30 | 2016-05-05 | International Business Machines Corporation | Mapping graphs onto core-based neuromorphic architectures |
| CN107483587A (en) * | 2017-08-21 | 2017-12-15 | 清华大学 | A kind of power telecom network cache optimization method of content oriented |
Cited By (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN110866687A (en) * | 2019-11-07 | 2020-03-06 | 中盈优创资讯科技有限公司 | Task allocation method and device |
| CN112953759A (en) * | 2021-01-27 | 2021-06-11 | 上海七牛信息技术有限公司 | Node optimal resource coverage analysis and adjustment method and device and computer equipment |
| CN112953759B (en) * | 2021-01-27 | 2023-10-03 | 上海七牛信息技术有限公司 | Node optimal resource coverage analysis adjustment method and device and computer equipment |
Also Published As
| Publication number | Publication date |
|---|---|
| CN108401233B (en) | 2020-12-29 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN107566194B (en) | Method for realizing cross-domain virtual network mapping | |
| CN110138764B (en) | Attack path analysis method based on hierarchical attack graph | |
| Guo et al. | On the role of communications plane in distributed optimization of power systems | |
| CN102869084A (en) | Methods and devices for performing synchronization and compensating clock drift among communication devices | |
| CN106998295B (en) | Optimized routing and spectrum allocation method and system based on special protection combined fault probability constraint | |
| Ghosh et al. | A cognitive routing framework for reliable communication in IoT for industry 5.0 | |
| Liao et al. | Cognitive balance for fog computing resource in Internet of Things: An edge learning approach | |
| Ashraf et al. | TOPSIS-based service arbitration for autonomic internet of things | |
| CN105848241A (en) | Clustering method and system of mobile ad hoc network | |
| CN108401233A (en) | One kind dividing matched compound event cognitive method based on most authority two | |
| CN103281708A (en) | Wireless sensor node deploying method | |
| CN106095579A (en) | Container resource allocation methods and device | |
| CN112492583A (en) | Software defined wireless sensor network management method based on cloud edge-side cooperation | |
| Lu et al. | Security-aware routing protocol based on artificial neural network algorithm and 6LoWPAN in the internet of things | |
| CN105898873A (en) | Data frame distribution method and device and data transmission method and device | |
| CN103746752A (en) | Intelligent spectrum sensing method based on hierarchical Dirichlet process | |
| CN105207905B (en) | Route selection method and device | |
| CN113411766A (en) | Intelligent Internet of things comprehensive sensing system and method | |
| CN111556090B (en) | Function aggregation self-organization system and method of intelligent Internet of things | |
| Sun et al. | Intelligent flood adaptive context-aware system: How wireless sensors adapt their configuration based on environmental phenomenon events | |
| Song et al. | Wireless Sensor Network Coverage Optimization Based on Fruit Fly Algorithm. | |
| CN106304178A (en) | The QoS assurance of a kind of electrically-based heterogeneous wireless network and system | |
| CN105871606A (en) | Mapping method for enhancing survivability of virtual network based on dividing-conquering strategy | |
| CN105636228A (en) | Wireless sensor network child node data transmission method based on multiplexing | |
| Cheng et al. | An approximate bandwidth allocation algorithm for tradeoff between fairness and throughput in WSN |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| CB02 | Change of applicant information | ||
| CB02 | Change of applicant information |
Address after: 510000 No. 293, Zhongshan Avenue, Tianhe District, Guangdong, Guangzhou Applicant after: GUANGDONG POLYTECHNIC NORMAL University Address before: 510665 Zhongshan West Road, Guangdong, Guangzhou, No. 293, No. Applicant before: GUANGDONG POLYTECHNIC NORMAL University |
|
| GR01 | Patent grant | ||
| GR01 | Patent grant |